Senior Lecturer, School of Mechanical Engineering
University of Western Australia
Centre for Neuromuscular and Neurological Disorders
Australian Neuromuscular Research Institute

Abstract
Loss of manual dexterity can cause serious difficulties for individuals attempting to complete everyday tasks. To rehabilitate the hand, accurate quantification of skill can be used to rank the patient against agreed norms and help to develop more targeted rehabilitation programs. Current tools can be expensive, cumbersome, and test only a few aspects of hand skill. This paper presents a prototype system that harnesses current technology but is both economical and portable. An application was created to run on an iPhone
™ or iPod touch ®
, the user can choose from three tests, whilst a force transducer captures the contact force. The system records the accuracy, time between movements and force of the actions recording results in a patient file. Individual, sequential and coordinated finger movements of both hands will be assessed. This system will provide clinicians and patients with quantitative results to improve the rehabilitation of the hand and has huge potential for future development.
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Alison Barnes
9A Princess Rd
Crawley, WA, 6009
26th October, 2009
Professor David Smith
Dean
Faculty of Engineering, Computing and Mathematics
University of Western Australia
35 Stirling Highway
Crawley, WA, 6009
Dear Professor Smith;
I am pleased to submit this thesis, entitled “
A novel system to analyse and improve the accuracy of finger dexterity in patients with conditions affecting the hand
”, as part of the requirement for the degree of Bachelor of Engineering.
Yours Sincerely
Alison Barnes
10427432
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Acknowledgments
I would like to sincerely thank my supervisor, Adrian Keating, for his support, knowledge, encouragement and most of all his enthusiasm for the project throughout the year. I would also like to thank Gary Thickbroom, for his time and insight into the clinical aspects of this system and Vera Riley for her expertise and help in recruiting patients. Lastly, huge thanks to my friends and family for their support during the year.
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0.
1.
CHAPTER 1 -INTRODUCTION AND LITERATURE REVIEW .................... 1
1.1. I
NTRODUCTION AND
P
ROJECT
O
BJECTIVES
.......................................................... 1
1.2. REVIEW OF C URRENT LITERATURE ....................................................................... 2
1.3. O
RIGINAL
D
ESIGN OBJECTIVES
............................................................................. 8
1.4. S YSTEM DIAGRAM ................................................................................................ 9
2.
CHAPTER 2- APPLICATION DEVELOPMENT AND DESIGN
APPROACH .................................................................................................................. 10
2.1. D ESIGN CRITERIA ............................................................................................... 10
2.2. W HY APPLE ........................................................................................................ 10
2.3. D EVELOPMENT OF AN A PPLE A PP ....................................................................... 11
2.4. I
NTERACTION WITH THE DEVICE
-D
ISPLAY AND FEEDBACK ISSUES
..................... 12
2.5. T
ASK
D
ESCRIPTIONS
........................................................................................... 13
2.5.1.
Task1-Single finger tapping test ................................................................. 13
2.5.2.
Task 2-Sequences ........................................................................................ 14
2.5.3.
Task 3-Pinching .......................................................................................... 14
2.6. P
ROGRAM FLOW
................................................................................................. 14
2.7. D
ATA ACCESS AND RETRIEVAL STORAGE
........................................................... 15
2.8. S
OFTWARE TESTS
............................................................................................... 16
3.
CHAPTER 3-FORCE TRANSDUCER DEVELOPMENT DESIGN
APPROACH .................................................................................................................. 17
3.1. R
ANGES OF FORCE
.............................................................................................. 17
3.2. D
ESIGN CRITERIA
............................................................................................... 18
3.3. P
OSSIBLE SOLUTIONS
.......................................................................................... 18
3.4. A CTUAL CHOICE ................................................................................................. 18
3.5. L OAD CELL ......................................................................................................... 19
3.6. S TRAIN GAUGE AMPLIFICATION .......................................................................... 20
3.7. A RDUINO M ICROCONTROLLER ........................................................................... 21
3.1. D ATA A CQUISITION ............................................................................................ 22
3.2. I NTERFACING WITH APPLICATION ....................................................................... 23
3.3. D EVICE HOLDER ................................................................................................. 23
3.4. O UTER C ASING ................................................................................................... 25
3.5. S
AFETY
............................................................................................................... 25
3.5.1.
Safety of the force transducer and casing ................................................... 25
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3.5.2.
Safety of the application ............................................................................. 26
3.6. F
INAL
S
YSTEM
S
CHEMATIC
................................................................................ 27
4.
CHAPTER 4- USER FEEDBACK ....................................................................... 28
4.1. E
THICS APPLICATION
.......................................................................................... 28
4.2. S
UBJECTS
........................................................................................................... 28
4.3. T
ESTING PROCEDURES
........................................................................................ 28
4.4. S
AMPLE
D
ATA
.................................................................................................... 29
5.
CHAPTER 5- RESULTS AND DISCUSSION ................................................... 34
5.1. D EVELOPMENT OF THE I R EHAB APPLICATION ..................................................... 34
5.2. P ERFORMANCE OF THE SOFTWARE APPLICATION ................................................ 34
5.3. J AILBREAKING .................................................................................................... 34
5.4. P ERFORMANCE OF LOAD CELL : L OAD CELL RESPONSE AND CHARACTERISTICS .. 35
5.4.1.
Impulse Response ........................................................................................ 35
5.4.2.
Dampening .................................................................................................. 36
5.4.3.
Warm up time .............................................................................................. 36
5.4.4.
Calibration Curve ....................................................................................... 37
5.4.5.
Sequential tapping at various speeds.......................................................... 38
5.4.6.
Repeatability ............................................................................................... 41
5.4.7.
Noise Sensitivity .......................................................................................... 42
5.4.8.
Calibration .................................................................................................. 43
5.4.9.
Size and Weight ........................................................................................... 44
5.4.10.
Data Transfer ............................................................................................ 44
5.5. S
URVEY
R
ESULTS
............................................................................................... 44
5.6. O
BSERVATIONS OF USERS
................................................................................... 45
5.6.1.
Application .................................................................................................. 45
5.6.2.
System ......................................................................................................... 47
5.7. C
OST ANALYSIS
.................................................................................................. 48
5.8. L IMITATIONS OF THE SYSTEM ............................................................................. 49
5.8.1.
Application .................................................................................................. 49
5.8.2.
Force Transducer ....................................................................................... 49
5.8.3.
User Feedback Group ................................................................................. 50
6.
CHAPTER 6- CONCLUSIONS........................................................................... 51
6.1. R EFLECTION UPON ORIGINAL OBJECTIVES AND DESIGN CRITERIA ....................... 51
6.2. C
LOSING
T
HOUGHTS
.......................................................................................... 53
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7.
REFERENCES ....................................................................................................... 54
8.
APPENDICES ........................................................................................................ 57
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Chapter 1-Introduction and Literature Review
HAPTER
NTRODUCTION AND
ITERATURE
EVIEW
1.1.
I NTRODUCTION AND P ROJECT O BJECTIVES
The Australian Neuromuscular Research Institute (ANRI) expressed the need for a system that could evaluate manual dexterity, a system, which can provide an accurate assessment of hand and finger motor skills. Such a system will help patients who have reduced hand function (due to stroke, Parkinson‟s disease, or injury) by tracking their recovery in their current rehabilitation programs, helping clinicians to design more specialised programs.
This thesis gives details for the development of such a system, shown below in Figure
1-1. This system is to be used by clinicians working primarily with stroke and patients
with Parkinson‟s disease (PD) but will also be suitable for other users with reduced hand function. The system is to be used for assessment of finger dexterity and contact force and also as a rehabilitation tool, to help improve accuracy of finger movements.
The patient will be guided by the system to perform certain movements with his/her fingers using one or both hands, the application will analyse the accuracy and time between movements whilst a force transducer captures the force of the actions, saving a report on the patients‟ performance. Individual, sequential and coordinated finger movements of both hands will be assessed. This system will provide clinicians with data on how accurate the users‟ responses are, and also a summary of the forces generated.
The system was designed to be portable so that it could be used as a rehabilitation tool in the home. The objective of this research was to design and implement a system that would enhance the recovery process for patients, enabling them to regain fine motor control of their fingers to complete everyday tasks.
Patient
System
?
Feedback/Comparison to previous and normal scores
Results
Clinician
Figure 1-1: This thesis presents a solution for a system able to asses hand skill, making data available for clinicians to analyse users’ skill, and provide feedback to the user.
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Chapter 1-Introduction and Literature Review
This thesis will first present a review on various analytical and rehabilitation systems that are either commercially available or still in development, and explore how to design an effective rehabilitation device. Chapter Two details the design and development of an Apple Software Application, hereon nicknamed “iRehab”. iRehab presents the user with three tasks, assessing various aspects of hand skill to be viewed on an Apple iPhone
™ or iPod touch ®
.
Chapter Three explores the problems associated with capturing finger forces and explains the design, construction and interfacing of a force transducer with the iPhone
™ or iPod touch ®
.
Chapter Four discusses how user feedback was obtained, 24 control and 10 Parkinson‟s disease, stroke and hand injury subjects were recruited and their results to the tests and survey were recorded. This provides valuable insight into the performance of the system and a framework for future work. User data is also presented illustrating interesting differences between the different users Chapter Five presents the results of the system testing, user feedback study and discusses some of the limitations and prospects of the current system.
This thesis presents a detailed review of the steps taken to create this system from the conceptual design through to clinical trials. This required research, feasibility studies, software development, mechanical and electronics design and assembly as well as product research through user studies. Finally presenting a prototype system, including analysis of its capabilities and failings from real user feedback, directing the reader to the opportunities for future work in this exciting field.
1.2.
REVIEW OF C URRENT LITERATURE
We rely on our manual dexterity to be able to carry out day-to-day tasks, such as writing, dressing and cooking. Problems with motor skills of the hand can be caused by stroke, Parkinson‟s disease, hand injuries and a myriad of other conditions affecting the neuromuscular system and can severely affects ones quality of life. In rehabilitation of the hand, accurate quantification of dexterity can be used to „rank‟ the patient compared to the agreed norms and show areas of weakness and strength. This aids in the development of targeted rehabilitation exercises. Further, as treatment progresses, relative levels of improvement need to be measured accurately, to evaluate the success of the program.
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Chapter 1-Introduction and Literature Review
Parkinson‟s disease (PD) affects ones ability to control the movement of the muscles.
PD patients may experience rigidity, hypokinesia (difficulty in initiating movements), bradykinesia (slower, smaller movements than desired) and involuntary tremors.
Various drugs and surgeries are available to help control the symptoms of PD.
Assessment of hand skill; through tests such as the single finger tapping test is commonly used to track the progression of the disease.
A cerebrovascular accident, commonly known as a stroke, cause deprivation of blood to a part of the brain (Bear, Connors & Paradiso 2007). If this occurs in the motor cortex, a patient may have difficulty in initiating and controlling movements in the contra-lateral side of the body, which can severely debilitate them and cause frustration. The adult brain has some degree of plasticity, and with practice and execution of repetitive movements, the cortex is capable of creating new connections to take over the function that the damaged cortex previously performed (Krakauer 2006). This drives the need for interesting and effective rehabilitative techniques as many repetitions are required to induce change in the synaptic density (the number of connections between neurons).
Function in the hand will often return first as whole hand movements, and work needs to be done with the patient to relearn how to isolate individual fingers. The average age of a patient with Parkinson‟s disease or a stroke will generally be higher than patients presenting with muscle or tendon injuries.
There are many tests currently used by clinicians in assessing finger dexterity, some are
shown below in Figure 1-2, three common tests are the reach-to-grasp, grip and release
and single finger tapping test (Kandori et al. 2007). The single finger tapping test, requires the user to tap a button as many times as they can in ten seconds, and displays
the number of taps, a machine used to asses this is shown below in Figure 1-2a and
costs US $170. Many tests are timed motor-manipulation tests e.g. The Nine Hole Peg
Test, Minnesota rate of manipulation, O‟Connor Tweezer Dexterity (Hammond, Shay &
Szturm 2009). The Nine Hole Peg Test involves the user placing nine wooden dowels in
a 3x3 array of holes as quickly as they can, the Minnesota rate of manipulation (Figure
1-2b) requires the user to move the round blocks to different areas of the board and the
O‟Connor Tweezers Dexterity (Figure 1-2c) requires the user to move a set of pins into
small holes (1/16 inch diameter) with a set of tweezers. For each test, the time taken to complete the exercise is used as the score. Although a time score from a test may allow
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Chapter 1-Introduction and Literature Review comparison of the patients‟ performance to the agreed norms, it only provides a gross estimate of their hand function. a) b) c)
Figure 1-2: Some commonly used assessment tools, a) The Single Finger Tapping Test
(Western psychological services), b) The Minnesota rate of manipulation and c) the
O’Connr Tweezer Dexterity test (pictures sourced from www.rehaboutlet.com)
Questionnaires are also a common assessment tool, the Fugl-Meyer assessment of motor recovery after stroke is a highly recommended test, (Gladstone, Danells & Black
2002), it is a stroke-specific, performance-based impairment index, designed to assess motor function, balance, sensation and joint functioning in hemiplegic post-stroke patients where various tasks are staff assessed on a three point scale. Some questions and tasks included in this assessment include asking the patient to repeat a series of movements, like making rotational actions with the hand, gripping objects whilst the clinician attempts to pull them away and flexing and extending the wrist and elbows.
This test, along with many other questionnaires involves some sort of observational grading, which could introduce variety in diagnosis between patients. In 2009, Van de
Ven-Stevens et al., completed a review on the clinimetric properties of 23 instruments to assess activities in patients with hand injury and found none of the instruments had a positive rating for all the clinimetric properties for the quality criteria as described by
Terwee et al . in 2007. Suggesting that the current technologies and methods used to assess hand skills are not good enough, there is therefore a lot of room for improvement in the field of hand assessment and rehabilitation.
Advancements in technology and the introduction of robotics to the rehabilitation industry have introduced many new possibilities for instruments and bring change to rehabilitation programs, though this comes with increased costs. Robots can precisely record trajectories taken by patients as they complete their tasks and calculate joint
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Chapter 1-Introduction and Literature Review forces (Huang & Krakauer 2009). Actuators are proving to be useful in training severely affected patients whose muscles may be weak. Robots can perform actions consistently with minimal fatigue, which may alleviate the therapist from performing repetitive tasks
with the patient. (Hesse 2007). Figure 1-3a shows part of HWARD a robotic device that helps guide ones hand through the grasping motion. Cyber gloves, Figure 1-3b, are also
receiving a lot of attention, they have the ability to track the hand and finger position, and can include small actuators to help move the fingers (Dipietro, Sabatini & Dario
2008). a) b)
Figure 1-3: a) HWARD (Takahashi et al 2005), b) CyberGlove II. Immersion
Corporation
Virtual reality is also another technology that is bringing old rehabilitation practices into the 21 st
century. No longer just playing with putty in your hand, now you can control different objects on screen. Similar to video games, users are forced to make certain movements with their hands to complete a task on screen in another reality, bringing the potential to make repetitive rehabilitation exercises more fun.
Research in the field of hand assessment and rehabilitation has revealed many different
devices the technology use; some of the technologies reviewed are detailed in Table 1-1
with the tasks they present and skills they assess.
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Chapter 1-Introduction and Literature Review
Technology used Description of task Skill assessed Author




Software
PC
Two tri-axial accelerometers
Touch sensor
Patient tap 4 different keys on a keyboard following program cue,
„1‟‟2‟ or „x‟‟z‟

Time delay between taps

Response time
Tap index and thumb together

Finger tapping interval

Finger velocities

Number taps in 60s
(Kiziltan, Barut
& Gelir 2006)
(Yokoe et al.
2008)

Magnetic oscillation coil

5 detection coils(one on each finger, one on wrist
Grip and release tests

Grip and release of a 30mm diameter rod
(Kandori et al.
2007)


Passive markers
Video camera
Finger tapping test, drum finger of both hands little finger first

Speed and regularity of taps

Vertical position of fingers assessed
(Jobbagy et al.
2005)

4 stainless steel touch pads

Oscillator under palm
 LED‟s for stimulus
Paced and un-paced tapping test. With and without weights




PC, mouse
Excentre with variable amp and freq
Software program
One tri-axial accelerometer

Frequency of taps to frequency of pacing

Phase space plots

Tap number vs Tap interval
Patient moves mouse to track and object on screen
Patients tap in rhythm to auditory cues

RMS between target and follower,

Lag, optimal correlation coeff,

Hpyo/perkinesia

Reaction time

Movement time

Time between taps,

Regulatory index
(Muir et al.
1995)
(Calautti et al.
2006;
Machetanz et al.
1993)
(Calautti et al.
2006)
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
Electro-goniometer,

Custom software

Minibird 6OF motion sensor
Patient tips a wine glass, rotate a cork, use a pen to push object on screen
Chapter 1-Introduction and Literature Review

Rotation and displacement history of movement vs. a reference trajectory
(Hammond,
Shay & Szturm
2009)

Touch screen

Custom software
Patient taps of letters or shapes amongst man distracter shapes on the screen

Path taken

Speed of completion
(Rabuffetti et al.
2002)

5 stainless steel pads

MOSFET connected to each touch pad
Subject asked to tap each finger as many time in 30s

Number of taps in 30s

Pinch glove/Cyber glove survey

Various techniques used
Subjects wear a glove and are asked to do certain things

Capture hand movements very precisely, a lot of calibration required
(Lum et al.
2004)
(Dipietro,
Sabatini &
Dario 2008)

Electronic dynamometer

PC
Subject to complete three motor tasks: sustained squeezing, repetitive squeezing, and index finger tapping

Force capabilities of the hand

Force capabilities of the index finger
(Cramer et al.
1997)
Table 1-1: Summary of current systems used to assess finger tapping/force, grip force and hand movements.
From the table it is evident that each device is only capable at looking at a few attributes of hand skill, it would seem that a system assessing more skills would save time, space and money. While robotics and electronics have exciting potential in the data they could capture, they can be at times a little intimidating to the user. For some of the robotic technologies, some patients may not feel entirely comfortable being constrained and forced to move under an externally controlled piece of equipment.
Part of the system described in this thesis involves a use of a touch screen. Touch screens have been effectively used to assess visuo-motor exploratory skills as a
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Chapter 1-Introduction and Literature Review derivation of the well known paper-and-pencil cancellation test, (users are required to search though a page of letters or shapes and cross out certain ones) (Rabuffetti et al.
2002) and tracing letters exercises (Lum et al. 2004). Utilising the iPhone
™ or iPod touch
®
, means that the system inherits many capabilities that the technology already has, such as: large processing power, multi-touch touch screen, Wi-Fi and an internal accelerometer, it is also a programmable and upgradable system. Mobile phones have previously been used been used for sequence action recognition by harnessing the abilities of the inbuilt accelerometer (Baek & Yun 2008) . To date no finger motor skill analysis systems are known that utilise the multi-touch screen on a portable device which could be so easily distributed, or combine the tests included in the application.
Substantial research exist on the interaction of man and machine with touch screens
(Karat, McDonald & Anderson 1986; Sears 1991; William, Ralph & Peter 1985; Jukka
& Topi 2004; Ivan & Shigeaki 2003), mobile phones (Ängeslevä, Oakley & Hughes
2003; Jukka & Topi 2004), and importance of tactile feedback (Eve, Stephen & Jody
2008; Ivan & Shigeaki 2003). Consideration was given to all of these issues in the design of an approachable and ergonomic system in terms of displaying the information, the testing environment and feedback supplied to the user.
It has been shown that patients with portable rehabilitation devices have better recovery rates than those who only use the device under supervision in a clinic (Yuxiang et al.
2006). Willmann et al.
(2007) are conducting pilot trials of a home unit, the Stroke
Rehabilitation Exerciser. The system coaches the patient through a sequence of neurological motor exercises, which are prescribed by the physiotherapist and uploaded to a patient unit. A wireless inertial sensor system records the patient‟s movements. The data is automatically analysed for deviations from a personal movement target and patient and therapist are provided with adequate feedback. However it must be ensured that the technology will work reliably, away from the eyes of the experienced clinician, calibration and technical difficulties may lead to inaccurate data collection.
(Willmann et al. 2007)
1.3.
O
RIGINAL
D
ESIGN OBJECTIVES
These original design objectives were identified as important in the creation of a successful rehabilitation and assessment tool and were the driving force behind the decisions in the design and construction of the system
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Chapter 1-Introduction and Literature Review

Low cost - The system is to be affordable for an everyday user.

Small and portable -Possible for user to take the system home to complete their exercises.

Assess many aspects of hand skill - To try and give the best value for money and save space.

Provide quantitative and meaningful data to clinicians - So that clinicians and therapists can clearly identify areas of weakness and design more specialised programs, make it easier to track improvements and remove observational grading.

Novel and appealing to potential users - To encourage use of the system to ensure quicker recovery rates
To achieve these goals and provide a development platform a software application was created to act as the Graphical User Interface (GUI) for the system, whilst a force transducer was constructed to capture the force of each contact.
1.4.
S YSTEM DIAGRAM
Based on the literature review and discussion with clinicians at ANRI, the unknown
functions of the system shown earlier in Figure 1-1 is expanded on. Figure 1-4 presents
the system described in this thesis, designed to assist in hand assessment and rehabilitation.
Software application
Force Transducer
Mechanical holder/case
Signal Processing
Figure 1-4: Identifying the different parts of the system
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Chapter 2-Application Development
HAPTER
PPLICATION DEVELOPMENT AND DESIGN APPROACH
In order to satisfy some of the original design objectives of the project it was decided to design a software application to run on the Apple iPhone
™ or iPod touch ®
, commonly known as an „app‟. This choice was largely due to its size, low cost, functionality already available within the device, multi-touch touch screen and ease of distribution of the software application through the Apple App store. A mobile phone or gaming device with a LCD display, and that can run a software application makes for a small, light weight and portable system. This thesis intends to harness state of the art technology, and turn a multimedia and communication device into a rehabilitation device.
2.1.
D
ESIGN CRITERIA
The software application was designed with the following features in mind:

It will present a GUI for the user to interact with, requesting them to complete certain tasks suitable for assessing hand motor skill

It will provide feedback to user with results- Important for motivation

It will create a report of results to be stored in users file For the application to access previous scores, and for clinician to review in detail later

It will be possible to interface with external accessories- Such as the force transducer

It will have some degree of flexibility to hand size and disability level The system should have the ability to cater for different users
2.2.
W
HY APPLE
Research into various multi-touch touch screens has found the cheapest and most effective way of designing a portable device was to use a mobile phone. Samsung,
Nokia, Blackberry and other leading phone manufactures have devices that have multi touch capabilities; however Apples‟ iPod Touch® provides the most cost effective solution, at $269 AU (Apple® 2009b) and is lighter and thinner than the iPhone (see
Table 3-1 for more details). Both devices have a 3.5 inch (diagonal) LCD multi-touch
capacitive touch-screen. These devices are hugely popular at the moment with over 50 million iPhone
™ or iPod touch ® users around the world (Apple® 2009a) .
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Chapter 2-Application Development
Apple‟s App Store has also just celebrated its two billionth app download. 125, 000 software developers all over the world have created more the 85, 000 apps that can be downloaded onto one‟s personal device (Apple® 2009a) . What this means for this system is that potential users from all over the world could download “iRehab” online onto their personal device to use. This has massive advantages over other technologies in terms of distribution and cost, also the potential to collect statistical data from users all over the world. The use of a portable electronic device helps to log the time the user has spent doing their rehabilitation exercise and with the built in Wi-Fi, results could even be emailed directly to their doctor.
2.3.
D
EVELOPMENT OF AN
A
PPLE
A
PP
The software application, iRehab, was written in objective-C using Apples‟ iPhone
Software Development Kit (SDK). The iPhone SDK for iPhone Operating System (OS)
3.0 includes support for developing iPhone OS 3.0 applications, and includes an iPhone
Simulator. Figure 2-1 shows screen shots of the simulator for the entry page and each of
the three test pages of iRehab, this is particularly useful in development if the developer does not have a device to test on. The iPhone SDK includes the complete Xcode 3.1.3
(Apple's premiere development environment for Mac OS X) and other developer tools for Mac OS X development as well as the SDK components for iPhone OS development. A developer is however limited into what areas they can access, and the
Software developer license does not allow you to interface external hardware accessories to the iPhone unless you pay an additional US $200 to become a „Made for iPod, works with iPhone developer‟.
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Chapter 2-Application Development
Figure 2-1: Screen shot of iRehab application and the three test pages, the view from the front of screen (and iPhone).
2.4.
I
NTERACTION WITH THE DEVICE
-D
ISPLAY AND FEEDBACK ISSUES
Various studies read examine interaction between man and machine and illustrate different factors that need to be considered, such as the shape of the keys on the touch screen, and the importance of sound and tactile feedback to the user (Ivan & Shigeaki
2003; van den Heever, Schreve & Scheffer 2009). These factors were taken into consideration when designing the tests as the way in which the task is presented to a user could influence their performance.
The use of a touch screen means there will be no mechanical resistance to the users movement, touch screens have been known to cause some confusion as to whether the user is confident that have completed a tap, particularly with older users who have not had as much exposure to such technologies (Sears 1991), (William, Ralph & Peter
1985), (Wood et al.
2005). Haptic feedback was delivered to the user by other means, buttons will change colour or shape upon contact; sound and vibrations are also used to provide feedback about the users‟ performance. Due to the nature of the capacitive touch screen, the user must use their finger to select objects, as the screen will not respond to fingernails or a stylus pen. The iPod touch does not have a speaker and so is unable to play sounds like the iPhone can; a possible solution is to connect the audio output (headphone jack) to a small set of speakers.
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Chapter 2-Application Development
2.5.
T ASK D ESCRIPTIONS
The software application was written with the original design objectives in mind:
The tests will:

Evaluate individual finger performance, specifically speed and accuracy

Test the users ability to move fingers forward and backward

Test the ability to complete sequential and synchronised actions

Test the pinching ability of the fingers

Require use of both hands separately and simultaneously
The role of the application was to allow users to try various tasks, complete them, and view their results allowing clinicians to measure patient performance. Each of the three tasks were developed with the assistance of Gary Thickbroom, to address various finger movements. Three tests are completed in this version with the system capable of handling many more pending their creation
The tests presented in this version are:

Single finger tapping test (SFTT)

Sequences test

Pinching test
These tests are defined in detail in the following sections.
2.5.1.
Task1-Single finger tapping test
The single finger tapping test (SFTT) has been used to assess the motor skill of the fingers since the early 19 th
century (Hollingworth 1914). In Parkinson‟s patients, the tapping test is used to estimate the severity of the disease (Jobbagy et al. 2005; Muir et al. 1995; Rao et al. 2003). Various methods have been used to perform the tapping test, such as the keyboard (Kiziltan, Barut & Gelir 2006), passive markers (Jobbagy et al.
2005), accelerometers (Calautti et al. 2006; Yokoe et al. 2007), stainless steel touch pads (Muir et al. 1995) or just a simple button (Christianson & Leathem 2004).
The fastest tapping frequency achievable is influenced by hand dominance, gender and most importantly in the context of thesis this, the mechanical properties of the tapping key. The finger tapping test is one of the original tests introduced and is commonly used as a simple measure of motor speed and control. Also known as the finger
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Chapter 2-Application Development oscillation test, it tests the maximum number of taps possible by the index finger in ten seconds of both the dominant and non-dominant hand. Interpretation of the available published norms in Strauss et al. (2006) and Christianson and Leathem, (2004) is complicated by the variety of testing devices available and administration techniques.
One of the most frequently used devices is a tapping lever mounted with a key driven counter where 400 g of pressure required to depress the key by 0.5 inch, through a 30 degree angle (Strauss, Sherman & Spreen 2006). Digital versions are also available, electronic self-contained timer with a digital display; this requires only 80 g of pressure to depress a lever 0.13 inch. The Rennick method is the most common administration technique; this involves taking the mean of five consecutive 10-second trials, within the range of five taps. The mean scores of different groups are most commonly comparing the results of the index finger. It would be however easy to extend the test to require the assessment of other fingers.
2.5.2.
Task 2-Sequences
The sequence test requires a user to repeat a random sequence of four numbers between one and four, testing the speed of response of each finger individually, and the whole hand to produce a coordinated movement. Sequence tests have been carried out in a number of different ways, using a computer and mouse, touch panels (Karat et al.,
1986) and passive markers (Jobbagy et al. 2005). This test is particularly valuable for stroke patients to encourage and assess movements of individual movements.
2.5.3.
Task 3-Pinching
The pinching test requires the user to bring two fingers (thumb and index) together, mimicking the common action of picking something up or grasping. This is a very important movement to master for everyday tasks. Some technologies used so far to asses this action include accelerometers (Yokoe et al. 2007), cyber-gloves (Dipietro,
Sabatini & Dario 2008), the HandNavigator: a ball of pressure sensors that allow interaction with a virtual reality (Kry et al. 2008) and HWARD, a three degree of freedom pneumatically –actuated robotic device that assists in the grasping and releasing movement (Takahashi et al. 2005).
2.6.
P
ROGRAM FLOW
A video of a user moving through each of the tasks is available online at http://www.youtube.com/watch?v=kZdz1kk7jJs , or on the Mechanical Engineering
server, along with a copy of the complete source code. Figure 2-2 below shows a flow
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Chapter 2-Application Development diagram of the iRehab application. Some of the important features of the application are the ability to log in as a new or existing user, or just go straight to the tasks. The application can create, store and recall patient files,
Figure 2-2 Program structure of iRehab application
2.7.
D ATA ACCESS AND RETRIEVAL STORAGE
Each user must have a unique username and password; this ensures results are stored to the correct file and protects the patients‟ results. As the user completes a task, relevant information is recorded into a patient file to be recalled later. The user name, date and test name is the title for easy access. Upon completion of the SFTT, the user can select the „view results‟ button, this displays the number of taps, min, max, and average time between taps and display the previous scores achieved. This is useful is providing feedback to the user on their progress, hopefully encouraging them to practice more to improve their scores. Test data can be stored and viewed by the clinician by connecting the iPhone
™ or iPod touch ® to a computer via the supplied USB cable.
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Chapter 2-Application Development
The file is viewed best through Property List Editor on a Macintosh, or by notepad on a
PC. Below in Figure 2-3 is an example for the SFFT, Appendix 1 show output files
from the pinching and sequences test.
Figure 2-3: File generated by iRehab application, storing data about the single finger tapping test by user AVL.
Figure 2-3 shows how the information is stored, and the data retrieved from the test.
Item 8, tap times is an array of the time period between each tap, useful in monitoring fatigue.
2.8.
S OFTWARE TESTS
The application was tested by the author through a series of pass/fail tests to ensure it would behave correctly for all possible user inputs and that the application could correctly store and retrieve patient information.
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Chapter 3-Force Transducer Development and Design Approach
HAPTER
ORCE TRANSDUCER DEVELOPMENT DESIGN APPROACH
Whilst the user is completing the tasks in the application, a force transducer captures the force of each touch. This is of use to help identify any weakness present in individual fingers and track a patients‟ improvement or decline. The hand is composed of 29 independent muscles, ligaments and tendons and is capable of the slightest of touch to forces up to 20 N (Jones & Lederman 2006). The arm and hand often work together to create movements, the tests presented in iRehab wish to look at the hand as an isolated system, thus why the test prompt for the user to restrain their wrist with their other hand. Given the large dynamic range of forces of the hand, care had to be taken in choosing the right force transducer; there were many options, some of which are
discussed in Section 3.3.
3.1.
R ANGES OF FORCE
As mentioned, the hand is capable of generating a large range of forces, mainly depending upon what muscles are engaged. It was important to estimate what range would be required to complete the tasks presented in the iRehab application. Kinoshita and Aoki report on forces generated by one finger, double fast tapping and whole hand tapping in speed tests. They used four miniature strain gauges (model not specified) two rated at 15 N were used (for index and middle) 0.03 N resolution, and two rated at 5 N
(for ring and little finger) with 0.01 N resolution. With the wrist constrained, the forces generated ranged from 0.4 N to 2.19 N, but were commented upon being smaller than expected, as it was a speed test. Inui and Hatta explored the coupling of force variability in bimanual finger tapping sequences (two fingers of each hand tapping at the same time). With the wrist constrained, subjects were asked to try and tap to meet a desired force, forces measured (using a Kyowa model LUB 5 kg load cell) ranged from around
1 N up to 5.5 N (subjects target was 1-4N) (Inui & Hatta 2002).
Whilst these previous studies helped to give an idea to the magnitude of forces to expect for the tapping test, literature reporting the forces for a pinching and sequences test was not found, most likely because this is a fairly novel way of assessing such actions.
Several participants were invited to complete the actions required by iRehab, instructed to complete the actions “as soft” and “as hard” as possible, with a restrained wrist to get
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Chapter 3-Force Transducer Development and Design Approach an idea of the likely dynamic range, the softest contact was recorded at 0.3 N and the hardest just over 4 N.
3.2.
D ESIGN CRITERIA
The force transducer and casing was designed with the following criteria:

Accurately capture forces capable of being generated by a human hand to do the tasks presented.

It will interface with the iPhone ™ or iPod touch ® both mechanically and electronically

It will be ergonomic and facilitate comfortable use of the system
3.3.
P
OSSIBLE SOLUTIONS
Various transducers could be used to satisfy the design criteria. The iPhone
™ and iPod touch
® both have an internal accelerometer, useful in the development of games. From
Internet tear down reports of the iPhone
™ and iPod touch ® it is believed to be a three axis accelerometer +/- 2, 8 g model number LIS302DL. An actual device to confirm this was not taken apart for this thesis due to the cost involved. A problem identified with using the accelerometer is that the output is dependent upon the movement allowed by the base that the device is sitting on. A possibility could be to manufacture a platform that is able to move only in one plane, or use a rubber material with a known spring and dampening coefficient.
Pressure sensors were also considered, Tekscan has the Flexi Force
®
pressure sensor that is only 0.203 mm thick, with a 9 mm sensing area. This variety of pressure sensor is fairly expensive, US $65 for four sensors. The force ranges available are 0-4.4 N or 0-
110 N. Tekscan claim their sensors to have been used in the assessment of grip forces
(Tekscan 2009).
3.4.
A
CTUAL CHOICE
A simple cantilever load cell, with a strain gauge assembly was chosen, due to its low cost and the authors‟ familiarity with the device, and design. A holder was designed and manufactured that holds the iPhone
™ or iPod touch ® and connects it to the load cell. A microcontroller receives the output voltage from the amplification circuit and sends it serially to a PC to be processed. The system is encased in a plastic container to reduce
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Chapter 3-Force Transducer Development and Design Approach air movement, which can add noise to the load cell, cover the cables and also serve as a
wrist support. A schematic of the system is shown below in Figure 3-1
Figure 3-1: System schematic of the force transducer inside an outer casing.
3.5.
L OAD CELL
The load cell shown below in Figure 3-2 has dimensions 25x25x140 mm, is made from
6060 aluminium and is a cantilever type load cell, with two hinge sites. The load cell used was manufactured for the 2008 Mechatronics Design unit at UWA. It draws on the design from US Patent 4432247 “Load cell having thin film strain gauges”. As seen in
Figure 3-2 the load cell is simply elevated from the base by washers, turning it into a
cantilever, as load is applied, the load cell will bend in a way so that the hinges experience strain, the load cell is attached to the base plate via an M6 screw. The load cell will bend linearly due to applied force up to its load limit. To protect the load cell from damage a protective washer has been placed under the load end, which the load cell with come into contact when a load of 10 N is applied. The load cell was loaded with one kilogram and washers were inserted between the base and the load cell till they were just touching, but checking to ensure this did not affect the output voltage. The washers were fixed to the base plate; therefore any further load will cause the cell to come into contact with the base so it is unlikely the cell could be strained into the material‟s plastic deformation region.
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Chapter 3-Force Transducer Development and Design Approach
Figure 3-2: Picture of actual load cell used, side view
3.6.
S
TRAIN GAUGE AMPLIFICATION
Strain gauges were used to measure the mechanical strain at the hinge sites of the load cell and an amplification circuit was built to process the change in resistance seen by the strain gages. Four strain gauges were arranged on the load cell, at the hinge sites in a
Wheatstone bridge configuration as shown below in section A of Figure 3-3 Circuit
Diagram, two gages were used for each hinge. The strain gauges used were from Vishay
Micro Measurements, 120
 
0.3% with a gage factor of 2.1

0.5%. As each hinge bends, the strain gage will flex with it, resulting in a change of its internal resistance.
The gages may not all have the same resistance at rest of 120 Ω, and/or they may have been damaged in the process of attaching them to the load cell, therefore a balancing circuit is used to account for any initial discrepancies. Three variable resistors and two fixed resistors were used in this circuit. The two side balancing resistors are 10 kΩ, with the middle one at 1K. The balancing resistors are also used for calibration of the load cell to set the initial output to zero, for no load. This provides large adjustments for different weights by the addition of the holder and device (iPhone/iPod), and then fine tuning, by using the middle 1kΩ. The output from the Wheatstone bridge configuration is a very small voltage due to the difference in resistances in the Wheatstone Bridge,
this is first amplified using an INA125 amplifier (Section B Figure 3-3) with a gain of
9061 then a second stage operational amp LF353 (Section C Figure 3-3), gain of ten
used to improve the sensitivity to forces less than 1 N. The circuit is powered by an external

12 VDC power supply and draws just over 80 mA. The output from the two amplifiers is scaled down from ±12 V to ±5 V and clipped using 5.1V zener diodes
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Chapter 3-Force Transducer Development and Design Approach
shown in Section D of Figure 3-3, as the analog inputs on the microcontroller can only
accept voltages between -0.7-5.5 V.
Figure 3-3: Circuit schematic showing section A: Electromechanical region, strain gauges arranged in a Wheatstone Bridge configuration on top of load cell. B:
Instrumentation Amplifier, amplifying the small voltage difference seen by the
Wheatstone Bridge. C: Operational amplifier, second stages of amplification. D: The two analog voltages from the first and second stages of amplification are scaled and clipped to be read by microcontroller.
3.7.
A RDUINO M ICROCONTROLLER
A microcontroller is used to accept the output voltages from each stage of the amplification circuit, shown as V
1
and V
2
above in Figure 3-3 and below in Figure 3-4.
The microcontroller used was the Arduino Decimillia, manufactured by SmartProjects .
It has a ten bit analog to digital convertor, and can accept inputs from -0.7 to 5.5V, the analogRead(PIN NUMBER) command will return an integer value from 0-1023 representing the voltage read on the pin selected within the range of 0-5 V, therefore
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Chapter 3-Force Transducer Development and Design Approach each integer represents 4.88mV. This is a limitation on the accuracy of the reading, but is sufficient for the tasks presented. The microcontroller is pre-programmed, and once connected to any computer; the program will start and continuously output A1 and A2, which are digital versions of the analog voltages V
1
and V
2
. Two programs are available
for the microcontroller; these are shown in Appendix 2 and Appendix 3. Appendix 2
shows the encoded version, with data being sent in hex format for increased speed of
transmission, Appendix 3 shows the program used to print the reading in ASCII format,
useful for quick debugging and calibration.
Figure 3-4: Schematic of amplification circuit. V
1
and V
2
are the two analog voltages representing the strain in seen by the load cell. A
1
and A
2
are the digital outputs from the microcontroller, which are sent to a PC for processing. Sections A, B, C and D
correspond to the circuit details seen above in Figure 3-3
3.1.
D ATA A CQUISITION
Data is sent though serial USB connection at 151200 baud to the computer, with embedded coding to allow error detection. Transmitting in binary format allowed minimal transmission delays and hence high speed sampling at 1.66 kHz. The contact interval of a tap is approximately 10 ms, therefore a high sampling rate is required to ensure that the maximum magnitude of the contact is recorded. A computer connected to the USB cable is able to read the incoming data on the serial port using a hyperterminal or Matlab (Appendix 4) to filter out any errors, save the data to an excel file as well as graph it instantaneously, displaying a force vs. time graph. Technical problems during user trial period meant that the raw force data had to be collected by running the program in Appendix 3 on the microcontroller, capturing the incoming data via hyperterminal and manually save it into an excel spread sheet then import the data into
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Chapter 3-Force Transducer Development and Design Approach
Matlab to plot, instead of just through Matlab. Obviously in future would be preferable for the force transducer to „talk‟ directly with iRehab application to bypass these steps.
3.2.
I NTERFACING WITH APPLICATION
Difficulties were encountered in trying to interface an external accessory, (the microcontroller) to the iPhone
™ or iPod touch ®
. This was an initial design objective, linking the force value to finger responsible for it in the application Possible means of data transfer could be via the 30 Pin Dock, with pin 7 and 8 as the data in and out pins, or via Bluetooth. To do either of these options, a developer must enrol in the „Made for iPod Works with iPhone‟ program, develop communication protocol and have it approved by Apple before it is allowed, time, lack of expertise and money prevented this avenue being pursued this year. Another option is to jailbreak the device, (see
Chapter 5.3 Jailbreaking, for more details). Alternatively information could be
conveyed to the iPhone ™ or iPod touch ®
with touch, i.e. a small tapping machine, entering data in a morse code approach, or the iPhone could talk to an external device by emitting a sound, vibration or use of an optical encoder. Currently the magnitude of each touch is seen by viewing the output from Matlab as the user progresses through the tasks, and it is the timestamps that allow the clinician to link the force values to the patient files. The patient files created by the iRehab application and stored on the iPhone
™ or iPod touch ® can be viewed in the Xcode organiser once the device is connected to the computer.
3.3.
D EVICE HOLDER
As discussed, the iRehab App, can be run on an iPhone
™ or iPod touch ® of various generations, provided it is running the iPhone Operating System 3.0 or higher (OS updates are available free online). Each generation has slightly different dimensions and weights, and considering its current success, Apple is sure to release newer versions of the iPhone
™ or iPod touch ® in the future. It is a fairly safe assumption the screen size will stay constant, or close to its current dimensions, as all applications previously designed rely on the defined dimensions of the 3.5 inch display. The weight and other dimensions may decrease in the future; Figure 3-5 below shows a picture of the device and the defined dimensions, Table 3-1 shows the possible devices that could be used to run the iRehab app and the differences in size and weight.
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Chapter 3-Force Transducer Development and Design Approach
Height
Depth
Width
Figure 3-5: Nomenclature of dimensions, (image taken from www.apple.com)
Device iPhone
™ iPhone 3G
TM iPhone 3GS
TM iPod Touch
®
1 st
generation iPod Touch
®
2 nd
generation
Width
(mm)
61
62.1
62.1
61.8
61.8
Height
(mm)
115
115.5
115.5
110
110
Depth
(mm)
11.6
12.3
12.3
8
8.5
Weight
(g)
135
115
133
120
115
Display (diagonal mm)
81 (480x320pixel
163ppi) 3.5”
81 (480x320pixel
163ppi) 3.5”
81 (480x320pixel
163ppi) 3.5”
81 (480x320pixel
163ppi) 3.5”
81 (480x320pixel
163ppi) 3.5”
Table 3-1: Dimensions of various devices that could be used to run the iRehab application (http://www.apple.com/iphone/specs.html)
The difference in width, depth and height vary between generations and models 0.3, 3.6 and 5.5 mm respectively. A holder was designed to fit either an iPhone
™ or iPod touch
® of any generation. As the device is to lay flat on the support, the range in depth is of importance. A prototype holder was designed by the author (Appendix 5) and then manufactured by the UWA mechanical workshop. There are two possible support bars that can be used depending if you are using the iPhone
™ or iPod touch ®
. The holder allows for the device to be slid in then secured down with six screws, this is to ensure that the device cannot move around in the holder and the force of the tap is transferred to the load cell. The holder is attached to the load cell by a M6 screw.
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Chapter 3-Force Transducer Development and Design Approach
3.4.
O UTER C ASING
The load cell is enclosed in an outer casing to protect the electronics from noise and
damage; the user will only see the LCD screen and holder, see Figure 3-6 for a picture
of the actual system. For this prototype a PVC box from Jaycar Electronics was selected for the casing of the system. The box dimensions measure 260x160x90 mm. Two holes were drilled into the casing for the power, USB cable and another small hole in the top to allow access to the potentiometer for calibration. This is not an ideal housing for shielding or ergonomics however time limited the construction of a more suitable casing.
Figure 3-6: Picture of actual system, gray casing covers load cell assembly. Black pads are for wrist and arm support.
Details of the load cell capabilities and results to various tests are discussed in Chapter
5.4 Performance of load cell: Load cell response and characteristics
3.5.
S AFETY
Emergency contact
UWA emergency phone number is: 2222
Australian Emergency number: 000
3.5.1.
Safety of the force transducer and casing
A large amount of time was spent in the UWA mechanical engineering labs to build various parts of the system, personal safety and ensuring the safety of others was of
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Chapter 3-Force Transducer Development and Design Approach great importance at all stages. A safety induction form was submitted and approved by the UWA mechanical engineering department and lab safety introduction, conducted by
Adrian Keating, was completed for the two laboratories that were to be used, G:19 and
G:55. The laboratories were regularly checked to ensure all emergency equipment was available. Safety procedures (contacts, evacuation procedures) were visible and clearly understood for each room. Person protective equipment in the form of enclosed shoes was worn at all times, and safety glasses were required for particular tasks, such as soldering.
Approval of designs for all electrical work was received before building of the circuit began all electrical work. Manufacture of the holder and shaping of the casing were done by members of the UWA mechanical workshop. The ±12 VDC power supply has a UWA approved electrical sticker. The casing used has no sharp corners and a lid to cover and protect the electrical components from damage, and also to protect the user.
No hazards, incidents or injuries were experienced during the year. Should one of these occur, it is vital it is reported investigated and resolved. An incident report form must be filed to the UWA safety and health office within 24 hours of its occurrence.
3.5.2.
Safety of the application
Safety was considered in this section primarily to do with the safety of data collection.
Results should only be stored under a users name if it is indeed the actual user. The application will only accept a new user if the user name is different to the previously stored values, users are then prompted to enter a password to use; upon completing tasks the results will be stored under each user name. If returning as an existing user, you must enter the correct username and password combination to gain access.
The application does not ask for nor store any identifying information, such as contact details, it is up to the clinician to make the link between user name and patient file. It is possible to copy the results from the iPhone
™ or iPod touch ® to an external computer, however new files cannot be added to the device.
Human Ethics approval was required for the user trials. This is a measure to protect the participants in the study and ensure that no one is taken advantage of. All procedures
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Chapter 3-Force Transducer Development and Design Approach and forms were reviewed and authorised by the committee. No deviations could be made from these approved procedures once the trials commenced Safety of their consent and survey forms was important in case at anytime a participant wished to be removed from the study.
3.6.
F INAL S YSTEM S CHEMATIC
1.iPod- Displays iRehab application
4. Strain Gages- Arranged in a Wheatstone bridge (WB) configuration. Resistance changes linearly with bending of the load cell .
2. Holder- This will attach the iPod to the load cell
5. Amplification Circuit-
To amplify the output from the WB.
Power Supply-
Constant

12 VDC
3. Load Cell-
Bends when load is applied
CasingEncases load cell assembly and base plate, only devices screen is visible
6. Microcontroller-
Converts analog voltages from amplification circuit into a digital value.
7. USB to PCProcesses incoming data, plots force vs time graph
Figure 3-7: Final system schematic and review of how the magnitude of a tap is recorded.
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Chapter 4-User Feedback
HAPTER
SER FEEDBACK
In order to evaluate the success of the proposed system, participants of different ages, gender, and hand skill were recruited to trial the system. Users were required to complete each of the tasks four to five times with each hand and fill in a short survey.
Observing users navigate their way through the application and around the apparatus proved very valuable in identifying the advantages and disadvantages of the system.
4.1.
E
THICS APPLICATION
As this work required data collection from potential users, an application for human ethics approval was submitted. Human ethics approval from the UWA Human Ethics
Committee was received. Reference number RA/4/1/2487 (Appendix 6) for the project titled, “ Exploring the feasibility of using a software application on the iPhone
TM
to assess hand motor skill and act as a rehabilitation device”.
4.2.
S UBJECTS
Participants were split into three groups for analysis purposes, either male control, female control or reduced hand function. 24 „healthy‟ control subjects males (n=14 mean age 30.2, age range 21-61) females (n=10, mean age 30.8 , age range 18-60) , and two injury seven Parkinson‟s disease (PD) patients and one stroke patient (females n=4, males n=6, mean age 63.9, age range 50-79) participated in this study. No subject had history of mental illness and all were over 18. All subjects gave their written informed consent after the explanation of the experiment protocol, as approved by the UWA
Human Ethics Committee.
Majority of the control participants were students and staff from the University of
Western Australia, although a number of other older control participants were also recruited from the staff or partners of patients at ANRI. Patients with PD attending the clinic at ANRI and stroke patients were recruited to evaluate the success of the system with participants with known movement problems.
4.3.
T
ESTING PROCEDURES
After reading the information sheet and signing the consent form the subjects were invited to interact with the system. The total test took 15 minutes to complete. Each task was completed at least four times for each hand, sometimes more if the participant had difficulties getting used to the apparatus, or they wished to try again. Subjects were then
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Chapter 4-User Feedback asked to complete a survey (see Appendix 7), to obtain feedback on their perspective of the system.
4.4.
S AMPLE D ATA
Whilst this thesis is not a study on the differences in hand skill, some results are presented for interest of the reader and to also exhibit what data can be extracted with this system. Scores from the single finger tapping test show a clear difference between the female control, male control and reduced hand function group. The user with the lowest score, with only six taps was from a female, age 79, who had suffered a stroke only four days prior to being assessed. The stroke affected her right hand side, (the dominant side); however she only achieved a mean of 10 taps on her left side. So whilst the stroke affected her dominant side scores more so, her age and condition may have also reduced her mean scores, more age matched controls are needed to confirm this.
The fastest female was a dentist, and the fastest males were either guitar or piano players, illustrating a potential (and somewhat expected) relationship between
occupation and hobbies with hand dexterity. Figure 4-1 below shows the difference in
scores of the dominant hand between the three groups. With the males, the fastest tappers achieving a mean of 60.53 taps compared to the females mean of 54.18. The users with reduced hand function had a mean of 40.25 but a very large spread, standard deviation of 15.71. This is due to the large range of disability in the group and males and females are grouped together due to the small sample sizes. In future it would be more desirable to compare users who have been determined to have approximately the same level of hand dexterity to compare their scores with this system. Also separation of gender and cause of reduced hand function would be valuable.
-29-

Chapter 4-User Feedback
μ = 40.25 σ=15.71
μ = 54.18 σ= 6.72
μ =60.53 σ=4.93
Figure 4-1: Average score from the users’ dominant hand in the single finger tapping tests. Subjects were grouped to either be male control, female control or reduced hand function due to PD, injury or stroke.
Comparison of the mean scores for the two control groups to the available normative data is difficult due to the small sample size in this study for each age bracket. A study by Christianson and Leetham in 2004, reviewed different types of equipment used in the single finger tapping test, this study used the same 86 people, requiring them to do the test on four different machines (results from their study shown in Appendix 8). Mean scores for male dominant hand are higher than the females at all ages for all testing machines. A high correlation between the scores obtained from the different machines was found, meaning the mechanics of each machine did not alter the users tapping rate significantly. The mean scores achieved by the single finger tapping test on iRehab also correlate well to this normative data. Direct comparison has not been made between each age group due to sample size; however the average score for female dominant hand was 53.55 across all machines and all users, compared to the 54.18 achieved in these user trials. For the males, an average of 58.7 was achieved compared the mean of 60.53.
Comparison to other data available in Strauss et al . (2006) show the scores from iRehab to be slightly higher, perhaps due to the lack of mechanical resistance of the button compared to the other devices. However comparison of iRehab results to those of
Christianson and Leetham are fairly similar perhaps due to the large range and small sample size.
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Chapter 4-User Feedback
The forces generated in the single finger tapping test were around what was anticipated,
lower forces around 0.5 N (20 yr old female) and highest 4 N (64 yr old male). Figure
4-2 clearly shows the difference between a control male age 55 (part a and b) and a user
with PD, age 63 (part c and d). Using Matlab to evaluate the data it is shown that the force from the control user is kept relatively constant, μ=2.63 N σ=0.399. Observations from most of the control users show that the force generated by the index finger will
increase and decrease slightly as they tap through the ten seconds. Figure 4-2 (part c and
d) shows a PD patient fatiguing as he progresses through the task, as the magnitude of the force decreases (μ=2.13 N σ=0.566), and the time between each of the taps increases. To further explore the fatigue, one can fit a linear curve to the peak force of
each touch and use the gradient to compare rate of force decline, Appendix 9 shows
such plots. For the control, the gradient of this line is 0.0015 and for the PD -0.03, meaning his force is decreasing on average by 0.03 N with every tap. The iRehab application is also capturing the time period between each tap in an array (recall the
single finger tapping test file in Figure 2-3), examination of this data would also reveal
the rate the user gets faster or slower as they move through the test, figures are shown in
Appendix 10 for interest of reader. a) b) d)
μ = 2.63
σ= 0.399 c)
μ = 2.13
σ= 0.566
Figure 4-2: Data from the SFTT, comparison between a control male age:55 (part a-
10s test and part b-Histogram of peak forces) and CIV, male with Parkinson’s disease
(PD) age:63(part c and d).
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Chapter 4-User Feedback
The force data received from the pinching test shows different pinching profiles for
each user (Figure 4-3). In general the older users would press on the touch screen harder
(average 3 N) than the younger users (average 1 N), perhaps due to familiarity with the style of device. Two examples are shown below again a male control age 55 and a male
PD user age 64. Two things are interesting about the user; firstly, as he attempts to control his tremor he completes the movement with a lot more force than the control user. The PD user has gone over 10 N, and it is clear the data is being clipped as the load cell comes into contact with the protective stopper. Secondly his tremor is evident as the force oscillates wildly about 8-10 N, he has also lost contact with the screen at t=13s.
Figure 4-3: Force data from pinching test. a) Three pinches from a control male b) Two pinches from the PD male.
Sequences test results shown in Figure 4-4 disply the lowest forces, again with the
younger users using a lighter touch, less than 1 N. Compared to user BON, who has
PD, who touches the screen much more forcefully (up to 7.6 N) as he executes his movements.
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Chapter 4-User Feedback
Figure 4-4: Force data from sequences test a) control male aged 20 b) control male aged 55 c) PD male aged 64
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ESULTS AND DISCUSSION
Chapter 5-Results and Discussion
5.1.
D EVELOPMENT OF THE I R EHAB APPLICATION
The task of creating an apple application proved to be quite challenging even with the documentation available in the SDK. The development of the iRehab application in such a short time with no previous experience limited the number of tests and functionality available within the app and therefore may have affected the first impressions of the system of some users. However, with more time or by involving a developer with more experience in creating Apple applications, iRehab could be extended to include more tests and solve some of the problems identified with the current application.
5.2.
P
ERFORMANCE OF THE SOFTWARE APPLICATION
The permission to exchange data between the device (iPhone ™ or iPod touch ®) and external accessories, (an original design objective to link the force of each contact to the device data stream) was not completed, due to time, money and experience. The force of each touch is not displayed on the iPhone
™ or iPod touch ® screen, each touch is simply time stamped. An Arduino microcontroller is available from SparkFun with a
Bluetooth emitter, which could be substituted into the system once a communication protocol is created and approved. Future work on this system should endeavour to exploit this capability or consider other ways in which data could be transferred between the load cell and the device. A bug in the sequences test was found in the user trials that needed to be fixed, but otherwise the application behaved as expected. It was noted that ladies with long fingernails had difficulty in completing the pinching task as they would get in the way during the motion and the capacitive touch screen does not respond well to fingernails or if there is moisture present on the screen.
5.3.
J
AILBREAKING
„Jailbreaking‟ is the act of modifying the official firmware in order to run applications not approved by Apple. It is very commonly done and many owners will jailbreak their device to get extra applications that they cannot get legitimately through the Apple App store. Apple claims that jailbreaking the iPhone ™ or iPod touch ® is a copyright infringement and a Digital Millennium Copyright Act violation. Seeing as the exchange of data between the force transducer and the iPhone is a failing of the current system, a possible solution is to jailbreak‟ the device. This would however mean that the iRehab app would not be able to be distributed legally through the Apple App Store and would
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Chapter 5-Results and Discussion require all potential user to jailbreak their device, something that could potentially void the warranty. This is not desirable for distribution of the system, but may be a solution until an approved protocol for data transfer is created.
5.4.
P ERFORMANCE OF LOAD CELL : L OAD CELL RESPONSE AND CHARACTERISTICS
To meet the design criteria the force transducer must be able to accurately and repetitively output values associated with the ranges of forces expected to complete the tasks presented. It must also capture successive taps, for example in the single fingertapping test.
5.4.1.
Impulse Response
Initial impulse response tests showed that the time for resonance to fade to steady state dramatically increased when mass was added, due to the weight of the holder and device. The resonant frequency was calculated by running a Fast Fourier Transform in
Matlab. Table 5-1 below shows the change in resonant frequency and time for output to
reach 5% of steady state. Figure 5-1 below shows the impulse response of the final
system. This data was collected by sampling V
1 the analog output voltage from the amplification circuit (prior to scaling and clipping) with an Agilent Oscilloscope
(sampling at 5 kHz), it is important to know the resonant frequency of the system to ensure repetitive tapping will not excite this fundamental frequency. An impulse test to find the resonant frequency was also conducted, the results of this test show that the resonant frequency, of 90 Hz is much higher than could be excited by a user.
Extra weight (g)
Resonant frequency (Hz)
Time to reach 5% of steady state value (s)
Load cell 0 169 0.093
Load cell + holder 240 83 0.113
Load cell + holder + iPhone
Final setup-Load cell +holder + iPhone+dampening material+casing
375
375
66
90
0.224
0.054
Table 5-1: Changes in resonant frequency and time to reach 5% steady state due to added weight of holder and device prior to dampening and after dampening
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Chapter 5-Results and Discussion
5.4.2.
Dampening
Dampening of the load cell was required to decreases the time taken for the impulse response to reduce to less than 5% of the peak value in less than 0.166 s (period of 6
Hz) so that subsequent taps could be recorded with the confidence that the previous
pulse was not interfering. As seen above in Table 5-1, the load cell was still oscillating
due to the impulse after 0.224 s. Dampening was achieved by experimenting with different materials placed between the base plate and the load end on the cantilever.
Various materials were tried such as a sponge, cloth but in the end a piece of soft rubber proved to be most effective at dampening the system. A final impulse response of the
system is shown below in Figure 5-1. It takes 0.054s for the impulse to reach within 5%
of its steady state value; theoretically this means that input frequencies less than 18 Hz could be captured with confidence the resonance from the previous contact is not affecting the next peak by more than 5%.
2.50
2.00
1.50
1.00
0.50
0.00
-0.50
0.00
-1.00
(0.048, 0.04)
0.05
(0.054, 2.16)
0.10
(0.099, 0.08)
0.15
0.20
Time (s)
Figure 5-1: Impulse Response of the damped system
CH1 Volt
5% Max
5.4.3.
Warm up time
The systems response may vary initially until it has come to thermal equilibrium. To estimate how long the system should be on before it is used, the output, with no load
was recorded for an hour and a half, shown below Figure 5-2. Stage 2 (A
2
) starts at 700 and evens out at 140, therefore taking 65 minutes to reach 5% of the steady state (SS) value 168, and 80 minutes to reach steady state. Meaning that the system needs to be connected to the power for a long time before accurate measurements can be made.
Once 65 minutes has passed, the system can be re-zeroed to zero by turning the middle resistor on the Wheatstone bridge, made accessible by a hole in the roof of the casing.
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Chapter 5-Results and Discussion
800
700
600
500
400
300
200
100
0
0
Stage 2
Stage 1
20 40 60
Minutes after power turned on
80
Figure 5-2: Warm up time. Stage 1(A
1
) and Stage 2(A
2
)values from the microcontroller are displayed from the time the power was turned on until the values have reached steady state.
5.4.4.
Calibration Curve
A calibration curve was needed to find the relationship between added mass and output voltage at various stages to estimate what the force of each contact was. For this test various masses were added and the output from A
1
and A
2
of the microcontroller were
recorded. The results are shown below in Figure 5-3. The minimum and maximum
weights applied were 1.5g and 1300g. Well below and above the expected input force
range discussed previously in Chapter 3.1. A
1
shows to have a linear relationship,
Output = 84.112*Applied Force, with a R
2 value of 0.99804, similarly A
2
is linear for forces between 0 and 1.35N, with an Output = 708.45*Applied force, R
2
= 0.99508. A
2 levels out with a reading of 1023 after 1.5 N as the input voltage reaches its maximum of 5 V. A
1
levels out at 820 as the load cell comes into contact with the protective washer and is no longer able to bend due to the applied load.
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Chapter 5-Results and Discussion
A2 =708.45*Force
R² = 0.99508
A1 = 84.112*Force
R² = 0.99804
Figure 5-3: Calibration curve between applied weights and output from the microcontroller.
Calibration of the load cell Figure 5-3 shows a strong linear relationship between
applied force and the output from the microcontroller. The force transducer responds linearly for applied forces up to 10 N for A1 and 1.35 N for A2. It must be remembered that the output of the microcontroller is correlated to an applied weight that is placed on the load cell for 20 s, this is very different to how the force will be applied for a tap, as the duration of contact will last for potentially less than 0.1s. Each integer from the microcontroller corresponds to an increase in force of approximately 0.0125N.
5.4.5.
Sequential tapping at various speeds
The ability of the transducer to accurately record the magnitude of sequential contacts
was examined by building a tapping machine (Figure 5-4) that would tap the device
with a constant force and frequency and then examining the systems representation of the input. The tapping rig used a small motor and a four bar linkage to create a constant force and frequency contact onto the touch screen. A rubber tip was used on the end to simulate a finger.
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Chapter 5-Results and Discussion
Force
Figure 5-4: The tapping machine, and schematic of the motor driving the four bar linkage that taps the screen on the device
The response to a humans fast tapping was also explored. Force vs. time plots of a
human and the lego machine are shown below in Figure 5-5 and Figure 5-6, the forces
exerted by the tapping machine were on the lower end of the range expected by a human, also the contact period was less than 6.2 ms for some taps, as opposed to the contact period of a human at 9.4ms, with a sampling rate of 1.4 kHz, the peak force was not necessarily captured, resulting in the spread of the force values between 0.4 and 0.6
N. The values of the forces were calculated by substituting the integer value retrieved from the microcontroller into the calibration equations, from the calibration curve shown above. Only the readings for A
1
were required to plot the results.
The difference between response of the system to the tapping machine and the response of the system to a human finger is different and should be noted, below is a zoom in on the response to the tapping machine and also to a user tapping fast. Firstly the force is a little smaller in the tapping machine secondly the period contact for the tapping machine is only 6.1 ms as opposed to 9.4 ms for a finger. The impulse response looks a little different. This would be due to the way the fat pad on the finger would contact the screen as opposed to an eraser, the increased speed and kinematics of a tapping action by the four bar linkage vs. a human.
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Chapter 5-Results and Discussion a) b) c)
Figure 5-5: Human fast tapping, sampling from stage 1 (A
1
). a) Each spike representing an individual tap, over 12 seconds, b) Histogram of the peak force achieved by each tap. C) Zoom in on two taps to show the resonant properties of the tap and time for impulse to decay to 5%. a) b) c)
Figure 5-6: Lego machine fast tapping stage 1(A
1
) a) 10 Seconds of continuous tapping at just over 10Hz. b) Histogram of the peak value. c) Zoom in on three contacts.
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Chapter 5-Results and Discussion
Figure 5-6: Lego machine fast tapping stage 1(A1), shows a histogram of the max force
recorded for 114 sequential taps, ideally they should all be the same, the reason for the spread could be due to the sampling rate of the microcontroller not being fast enough to capture the true maximum force, seeing as the tapping interval has been reduced or, more likely, this can be attributed to the tapping machine being unable to deliver a constant force, as it was built from Lego.
The impulse from each tap is seen to drop below 5 % of steady state within 0.101 s, showing the system could capture repetitive input tapping force for frequencies up to
10Hz, which is higher than would be expected from a user, expected maximum tapping speed of a human is around 6-7 Hz (Christianson & Leathem 2004). But lower than the
18 Hz expected from the impulse response, perhaps due to the continual excitement of the repetitive tapping. However the sampling rate should be increased to ensure the maximum magnitude of the tap is being captured for taps with shorter contact intervals.
5.4.6.
Repeatability
To examine the repeatability of the load cell to accurately output the same value for the
same force, a 345g weight as placed on and off the load cell 13 times. Shown in Figure
5-7.
Load applied
Load removed
Figure 5-7: Repeatability test. 345 g weight placed on and off the iPhone.
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Chapter 5-Results and Discussion
It is clearly seen that the response of the force transducer changes with time. The force value increases as the weight is left on the load cell for a couple of seconds, at a rate of
0.06 N/s. This is perhaps due to the dampening material; the effect is also seen as the weight is removed. There is the trend for the load cell „no load‟ output to increase over time, as the output begins to move further away from the 0 N line where it started. This was further examined for rapid application and removal of a force, such as in the
tapping test. Below in Figure 5-8a, is the output from a single finger tapping test. At this
scale (0-2 N) it appear that after each tap the output is returning to zero in time for the next tap, however if we zoom in to 0-0.1 N, it can be seen that the output does not return to the no load position close to zero, it has moved from 0.01 N to 0.035 after the ten second period, adding an error of 2.5% to the reading. a) b)
Figure 5-8: Changes in the baseline during a single finger tapping test.
5.4.7.
Noise Sensitivity
Background electromagnetic radiation can induce small currents in the wires leading from the strain gauge to the amplifying circuitry, leading to undesirable noise in the signal. This noise can be reduced by twisting opposite signal lines together so that noise is cancelled out. In the wiring, such lines were kept next to each other, similar to in a ribbon cable. Fluctuations in the power were also smoothed out with two 0.1 µF
capacitors between the power supply and ground. Close ups of the output in Figure 5-9
(part a and b), with no load, the output from A
1 ranges from 0 to 0.012 with spikes up to
0.035 N, and A
2 range 0-0.058N. For the 140 g, (part c and d) load the output of A1
ranges from 1.5-1.52 N initially, then increased to 1.552-1.62 N after 6 seconds (Figure
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Chapter 5-Results and Discussion
5-9), the range of A2 is less, perhaps because it is reaching its limits (max force A2 can accurately represent is 1.35 N). This test showing the inaccuracies of the reading added by the noise are ±0.04 N. This is most likely attributed to electrical noise and 50 Hz from power. The system is quite sensitive to external vibrations such as vibrations desk on which it rests. Rubber mats were placed on the outer casing to reduce the effects of airflow, and the movement of the hand around the outer casing has on the outputs. a) c) b) d)
Figure 5-9: Noise present in system
5.4.8.
Calibration
It is desirable to have the output of the system equal to zero for no load, prior to testing begins. Due to the large changes in the output during warm up it is necessary to wait until the system has reached steady state before one resets the system to zero. It is also important that the output for A1 and A1 are not both zero as this could mean you are starting with an undesirable negative offset. Using program 2, (Appendix 3) on the microcontroller and a hyper terminal to view the outputs, one can zero the bridge using the middle potentiometer until A1, the first reading is showing 0 and A2, the second number is above zero, but below ten. In general, movement of the system will mean that
-43-

Chapter 5-Results and Discussion it will need to be re-zeroed most times it is used. A limitation of the system is the inability of the microcontroller to report negative voltages; this is due to the analog to digital convertor (ADC), input voltages to the ADC less that 0 V will give an output from the microcontroller of 0. It is therefore best to make sure the system has reached
SS with the microcontroller output giving reading greater than zero, before calibrating the system. This method of calibration is undesirable for the system, as it requires skill to upload a program to the microcontroller, and open a hyper terminal. It would be better to have a digital way in which to re-zero the system.
5.4.9.
Size and Weight
It is felt the size of the force transducer is too large, weighing in over 1 kg, and is responsible for the majority of the volume and weight of the system. Future work on the system may wish to include design of a smaller force transducer, perhaps by exploring
the smaller pressure sensors found in Chapter 3.3 Possible solutions, or redesign or
purchase a smaller load cell, to help to reduce the height and weight of the system.
5.4.10.
Data Transfer
The lack of communication between the force reading and the application makes the process of examining patient results much more time consuming than is desirable. In order for a clinician to make the most out of such a system the synthesis of the results and analysis needs to be done primarily by the system. This will involve developing more code to sort through the incoming signal to find maximum, minimum and average forces and allow comparison between the users‟ previous scores as well as perhaps between other users.
5.5.
S URVEY R ESULTS
Feedback from the user trials and professionals in the industry has been very positive sparking real interest and reason for this work should be continued. The results from the survey on the questions pertaining to its fitness, functionality and form are shown below
in
Table 5-2. See Appendix 7 for the full survey questions.
Question
Possible answers and percentage selected
Fun
Not
Very
6% Ok 26% Interesting 42% Fun 26%
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Chapter 5-Results and Discussion
Usefulness
Originality
Not
Useful
Not very
6%
0%
Not overly useful
OK
7%
Useful at times
Very
Useful
3% Interesting 26%
Very
Original
71%
Size
Too small
SFFT ease of completion
Sequences ease of completion
Difficult
Difficult
Pinching Test ease of completion
Seen something like this before
Difficult
Yes
26%
3%
Somewhat
Difficult
13%
Somewhat
Difficult
16%
Somewhat
Difficult
0%
OK
No
74%
10%
16%
22%
100%
Too Big
Pretty
Easy
Pretty
Easy
Pretty
Easy
55%
0%
32%
45%
36%
Very
Easy
Very
Easy
Very
Easy
32%
58%
26%
23%
Any text to small? Yes 6% No 94%
Buttons to small? Yes 10% No 90%
Would use it as a rehabilitation tool
No 10% Yes 61% Maybe 29%
Table 5-2: Results from the survey (n = 31). Question, possible answer and percentage of users that chose that answer are shown.
Overall the response to the system was very positive, majority of users found it fun and useful which is important for motivational purposes. Users generally were able to complete the tasks with ease; however a few modifications will be made to the app to enhance its useability. The size of text and buttons were considered ok, however a few users did say they had to use their glasses. Given the size constraints of the LCD display, increases to the size of the text and graphics are somewhat limited. No one had seen anything like this before, and users found it interesting (26%) and very original
(71%).
5.6.
O
BSERVATIONS OF USERS
5.6.1.
Application
From observing users navigate their way through the application valuable lessons were learnt. As expected there was a huge difference in the way that younger participants
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Chapter 5-Results and Discussion handled the touch screen vs. the older users. This is predominantly due to familiarity with such a device. Use of a multi-touch touch screen does take a little while to get used to, however most users really seemed to enjoy navigating their ways though the thee tasks, and only one participant showed negative response, primarily because she had nerve damage to her fingers and so had problems feeling the screen and she also had long fingernails which obstructed her fingers contacting the screen correctly.
It was noted the „Back‟ button was too small and got in the way of the sequence task for the left hand as would often be hit my users with bigger hands. In general users with large hands had difficulty only with the sequences task, as they would obstruct the buttons as they attempted to complete the sequence. It future versions of iRehab, it would be desirable to have a scaling function available for hand sizes, or find a device with a slightly larger screen. Different tests should be developed that are more suitable to the screen size available. The screen can be affected by the glare of the sun, so care was taken to ensure users could see the display properly
PD patients often experience uncontrollable tremors; this causes a lot of difficulties with a touch screen as users would accidentally select buttons without meaning to, as little force is required. The force value from the transducer could be useful in this respect to identify, meaningful actions vs. tremor induced selections. One PD participant had very advanced Parkinson‟s, he was experience severe rigidity and bradykinesia (slowness in the execution of a movement), at the time of completing the tasks, and was unable to complete the sequence and pinching test, showing that this system is not suitable for patients with such reduced motor skill. Unfortunately only one stroke patient was recruited, due to availability of patients and the lady that participated received the lowest scores. She had had recently suffered from a stroke and was also the oldest participant which may have also affected her scores. She had quite significant lack of control over her individual finger moments and so found completing the tests quite difficult.
In general users were very impressed with the technology and positive towards using it as rehabilitation device; especially the iPhone/iPod touch alone as it is small and portable, 91 % of participants said yes (61%) or maybe (30 %) when asked if they would use the system if it were presented to them as a rehabilitation device. An interview with Vera Riley, a senior occupational therapist from Sir Charles Gardiner
Hospital highlighted other potential user groups and tests that would be suited to the
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Chapter 5-Results and Discussion system. Vera was very confident that her patients would embrace the technology as a more appealing option than some other available technologies. Vera explained patients respond well to task orientated technology orientated therapies, it is believed younger patients would enjoy using the iPhone
™ or iPod touch ® as a rehabilitation tool more so than older users as it is a particularly relevant piece of technology to them. This suggests that future software upgrades perhaps require development of more task related tests. In terms of older users, Vera explained sometime the difficulty in completing a task would be to do with the cognitive skill and difficulty with the technology as opposed to lack of hand dexterity. She expressed the system would be suited more to users under 60, and could be particularly effective with younger users. The next set of patient trials should target a younger users group to see how they respond to the system
(Mrs Vera Riley 2009, pers. comm., 1 October).
5.6.2.
System
As mentioned in Chapter 3.4 Outer Casing, an optimal casing was not achieved. In
general it was better if the user was sitting quite high in a chair so that they were looking over the screen and system, not across. One user mentioned that a tilted screen would have helped her to see a little more clearly. A rounded casing with a moveable yet secure arm rest would have provided slightly easier use of the system, as users would have to move the arm rest around to position themselves for the different tests, of different hands. PD patients often complete movements with more force than a control subject, and at times would displace the system. Some sort of grip system, perhaps rubber to secure the system to the desk so it could not slide around during testing, remembering that the screen position needs to be able to swivel to allow different arm
orientation. A preferred design is shown below in Figure 5-10. This should be explored,
improved and built in future work. iPod- Sits in middle of casing
Arm Rest Can be easily slide around casing
Casing- Hold iPod and covers force transducer
Figure 5-10: Design of a more ideal casing
Figure 5-10: Design of a more ideal casing
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Chapter 5-Results and Discussion
5.7.
C OST ANALYSIS
An original design objective was to design a low cost system. Review of the current
technology highlighted how expensive some of the current technology is, Table 5-3
below outlines the costs to create the system.
Item
Become an iPhone developer* iPod Touch new
Cost
US $99
Source www.apple.com
Comments
Once a year*
AU $269 www.apple.com Assuming 8 GB iPod Touch 2 nd
hand AU $152 www.ebay.com Assuming 8 GB iPhone 3G
Cost to distribute
Cost to buy iRehab
Force transducer parts
AU $759 www.optus.com.au
Also available on phone plans, for AU $49 /month
Free www.apple.com
Provided you are a registered developer
Free
≈AU $60 www.apple.com
UWA Electrical
Workshop
Depends upon price set,
Apple takes 30%
Depends on volume parts are purchased at
Microcontroller
(Arduino)
US $29.95 www.sparkfun.com
Holder
Case
AU $50
AU $ 30
UWA Mechanical
Workshop
Jaycar Electronics
Manufactured by UWA
Mechanical Workshop
Purchased from Jaycar electronics
Total cost to develop iRehab and build load cell transducer
Total cost for a user to run iRehab Application on a device
AU $268.95
AU $152
Total cost for user to run iRehab and load cell AU $322
Table 5-3: Cost Analysis
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Chapter 5-Results and Discussion
It is free for a registered developer, to submit and sell an app in the Apple App store, and a developer may choose the price they see fit, but Apple will take 30% of the selling price. There is a large assembly time for the strain gage assembly, which has not been included as it was the authors own time, this should also be taken into consideration for actual distribution. The cost for the end user would just be the cost of the device to run it on, the cheapest being a second hand iPod touch. The cheapest device to run the app would be a second hand iPod touch at around AU $150.
The costs to develop this system totalled to just under AU $270, and the cost of a user to just start with the iRehab application on their own device could be zero, providing they already own an iPhone
™ or iPod touch ® as they could download the application for free off the internet.
5.8.
L
IMITATIONS DURING DEVELOPMENT AND OF THE FINAL SYSTEM
5.8.1.
Application
The skill and time required to develop an application limited the number of features and number of tests that were developed. Effort was put in to try and exhibit the capabilities of the device. However there were other features that, if they had been developed may have enhanced the users experience and performance. The authors‟ lack of experience in the area of hand assessment and rehabilitation meant a lot of trust was put on the literature review and industry professionals to assist in the development of appropriate tests.
5.8.2.
Force Transducer
The collection of force data manually through Matlab limits the portability of the system, as an experience operator with a computer would need to be involved to capture force data. Currently the force transducer still needs to be manually calibrated, which means a user really should not take it home as this could cause confusion and inaccurate collection of data. An over-arching program that collaborated, filtered and displayed the data would also be useful for quick analysis. Tests revealed a large warm up time is required and also the response of the system varies depending how long the load is applied, reducing the accuracy of the readings. The dynamic range of the force transducer needs to be increased after one user managed to exert more than 10 N.
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Chapter 5-Results and Discussion
5.8.3.
User Feedback Group
The user study was not truly representative of the population of potential users. The average scores also are from only a small number form each subgroup, PD, Stroke, young old, male female. Further work should look at recruiting more subjects with reduced hand function due to injury. In particular, younger subjects who are attending occupational therapy may be particularly suited to this system.
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Chapter 6-Conclusions
HAPTER
ONCLUSIONS
6.1.
R
EFLECTION UPON ORIGINAL OBJECTIVES AND DESIGN CRITERIA
Comparison between the final system and the original design criteria outlined in Section
2.1 and Section 3.2 are discussed below.
Design Criteria,
Low costiRehab, could, theoretically be free for potential users. The main costs reside in the device used to run the application, the cheapest device being the iPod touch
®
.
However compared to other systems, the iRehab app has the advantage that it can be updated easily to include more tests or software revisions, at no extra cost to the user.
The addition of the force transducer does increase the costs significantly and so future work should focus on a better solution.
Small and portable- A key reason for the iPhone
™ / iPod touch ® being selected was due to the fact it is such a small and portable device. The choice of force transducer is not yet a suitable solution, however it could reside in the clinician office and be used at appointments to track improvements after user has practiced at home on the iPhone
Asses many aspects of hand skill – iRehab currently offers three tests looking at speed, accuracy and coordination of individual and synchronised movements. Improving upon the current systems available that are only capable of assessing a few actions.
Provide quantitative and meaningful data to cliniciansThe results from the tests present quantitative information about the users finger movements to the clinician. For example, the single finger tapping test can now look at the fatigue of the patient through the time between each tap and the force generated.
Novel and appealing to potential users – Product research was conducted through patient and control trials and very positive feedback was received on the system. The system scored highly in its review of fun, originality and usefulness ratings as well as a large number of users saying yes (61%) or maybe (29%) to using the system as a rehabilitation device.
Software Application
Present a GUI for the user to interact with, requesting them to complete certain tasks suitable for assessing hand motor skill – The Apple SDK proved a powerful tool
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Chapter 6-Conclusions to create a fun and interesting, yet powerful GUI for the user to interact with . Addition of a movie in the instructions section would add value to the system.
Provide feedback to user through results – The system developed is able to retrieve previous scores for each user, these are displayed in the single finger tapping test, and sequences test. This aspect of the system could be further improved to present the previous scores graphically on the screen to help motivate the user to improve on previous performances.
Create a report of results to be stored in users file- iRehab accurately stores the users‟ results in a file, on the device after each test is completed. These are stored in a patient data file with the users name, date and test as the file name, allowing for easy retrieval, a separate filing system would be easy to develop in the future if required
It will be possible to interface with external accessories- Whilst the iPhone™ has the ability to communicate to external accessories via Bluetooth or the USB cable, this objective was not completed due to cost, time and skill limitations. Future work to develop this would really improve the way in which feedback could be presented to the user, and also allow for the force data to be stored in the same file as the test results.
It will have some degree of flexibility to hand size and disability level The current tests do not yet offer a scaling or skill level option, however the choice of system, (with its large software component) makes this an easy addition.
Force Transducer
Capture forces capable of being generated by a human hand to do the tasks presented. The force transducer is able to capture the input forces from 0-10 N, repetitively with reasonable accuracy however the range needs to be increased as a user was found to exert over 10 N. Use of the tapping machine shows the system can capture tapping frequencies up to 10 Hz, faster than a human is capable of tapping.
Interface with the iPhone
™ or iPod touch ® both mechanically and electronically.
A customised holder was designed and manufactured to hold the iPhone
™ or iPod touch
®
, (fitting all generation sizes). The device is easy to connect to load cell, with one sliding movement and tightened down by screws. Communication between the force
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Chapter 6-Conclusions transducer and the iPhone should be developed so that force feedback can be given live to the user on the screen.
The system will be ergonomic and facilitate comfortable use of the system- The casing developed provided adequate functionality for the tasks required however is not considered to be ideal. Future work should design a more ergonomic casing.
6.2.
C
LOSING
T
HOUGHTS
In conclusion a system capable of assessing hand dexterity has been designed, constructed and tested through clinical trials. An application with three different tests has been completed for an iPhone
™ or iPod touch ®
.
The device can be attached to a force transducer and data from each touch can be viewed on the PC. The iPhone SDK has proved to be a powerful way in which to develop an application many other tests of hand skill should be developed that could be added to the system in future software updates. This project will be continued next year, with continued support from both supervisors and Vera Riley as it shows real potential. This novel prototype system harnesses current popular technologies and shows significant advantages in terms of cost, appeal and portability over alternative technologies to assess and rehabilitate hand skill.
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References
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PPENDICES
Appendix 1: Sample patient test files from iRehab
Pinching Test:
Appendices
Sequences test:
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Appendices
Appendix 2: Arduino program 1
/*Arduino program 1
* This program reads the two values from the amplification circuit, and the time between readings, masks the data and sends the data serially for Matlab to read, a total of 6 bytes for every sample will be sent
8055C021E045....
*/ int firstStage = 2; // define the pin for A1 int secondStage=4; // define the pin for A2 int val1 = 0; int val2 =0; int count =0; unsigned long currentTime; unsigned long lastTime; unsigned long time;
// define masks byte LSBmask1 =B00000000; byte MSBmask1= B10000000;// 0x80 for A1 byte LSBmask2=B00000000; byte MSBmask2 =B11000000; //0xC0 for A2 byte LSBmask3=B00000000; byte MSBmask3 =B01000000; //0xE0 for time void setup() {
Serial.begin(115200); // set baud rate
pinMode(firstStage, INPUT);
pinMode(secondStage, INPUT);
lastTime = micros(); // get first time
} void loop() {
count++;
val1 = int(analogRead(firstStage)); // read the value from the A1
val2 = int(analogRead(secondStage)); // read the value from A2
currentTime= micros();
// Maske the data
byte msb1 = (highByte(val1) | MSBmask1);
byte lsb1 = (lowByte(val1)| LSBmask1);
Serial.print(msb1, BYTE);
Serial.print(lsb1, BYTE);
// Serial.print(val1) // use this to check the value of A1
byte msb2 = (highByte(val2) | MSBmask2);
byte lsb2 = (lowByte(val2)| LSBmask2);
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Serial.print(msb2, BYTE);
Serial.print(lsb2, BYTE);
//Serial.print(val2) // use this to check the value of A2
// Get the time between last reading and current reading
time = currentTime-lastTime;
byte msb3 = (highByte(time) | MSBmask3);
byte lsb3 = (lowByte(time)| LSBmask3);
Serial.print(msb3, BYTE);
Serial.print(lsb3, BYTE);
}
//Serial.print(time); // use this to check the time
lastTime=currentTime;
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Appendices

Appendices
Appendix 3: Arduino program 2
/*
* Arduino program 2
* This program will print A1 (int) and A2 (int) to serialport with time between 1000 readings
*/ int firstStage = 2; // select the input pin for A1 int secondStage = 4; // select the input pin for A2 int val1 = 0; int val2 = 0; int count = 0; // count of output values unsigned long time=0; // value to hold current time unsigned long lastTime=0; // value to hold time of previous reading void setup() {
Serial.begin(115200); // set the baud rate, max
pinMode(firstStage, INPUT); // set the pin on Aduino to be an input pin
pinMode(secondStage, INPUT);
Serial.println("New Session Started ");
} void loop() { count ++; if(count%1000 ==1) {
time = micros();
val1 = int(analogRead(firstStage)); // read the value from A1
val2 = int(analogRead(secondStage)); // read the vlaue from A2
Serial.print(val1); // print value of A1 in ASCII
Serial.print(" ");
Serial.print(val2);
Serial.print(" ");
Serial.println(time-lastTime);
lastTime = time;
} else {
val1 = int(analogRead(firstStage)); // read the value from A1
val2 = int(analogRead(secondStage)); // read the vlaue from A2
Serial.print(val1); // print value of A1 in ASCII
Serial.print(" ");
Serial.println(val2);
}
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Appendices
Appendix 4: Matlab program to read and plot force data
% Program to read data serially and plot force vs time graph, save data to excel file fileName = input('Please enter the user name and test for this record: '); time = input('Please enter the number of seconds you need to record for: ');
T= 0.0006; % T is the time between each reading numSamples= int32((time/T)*6) % should just by 6 for every successful read, therefore numSamples*6 dataLength = int32(numSamples/6) % size of of array data =zeros(dataLength,5); % create an array to store data [A1 A2 time count] column = 1; row = 1; count = 0; count2 =0; num2=0; num3=0; num4=0; notCheckedByte2 =1; notCheckedByte3 =1; notCheckedByte4 =1; byte1=-1; byte2=-1; byte3=-1; byte4=-1; byte5=-1; byte6=-1; s = serial('COM6'); s.BaudRate = 115200; fopen(s);
%timeStarted = fscanf(s);
%for i=1:1:200 while (count < numSamples)
if (byte2 ~= -1 && notCheckedByte2)% if loop broke at 2nd byte
num2=num2+1;
%display('byte2 now byte 1');
byte1 = byte2;
notCheckedByte2 = 0 ;
else if (byte3 ~= -1 && notCheckedByte3)
byte1=byte3;
num3=num3+1;
% display('byte3 now byte1');
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notCheckedByte3 =0;
else if (byte4 ~= -1 && notCheckedByte4)
byte1 = byte4;
num4=num4+1;
%disply('byte4 now byte1');
notCheckedByte4=0;
else byte1=fread(s,1,'char');%get 1st byte, spits out decimal number
count =count +1;
end
end
end
if (byte1>127 && byte1<132) % means it is A1 MSB 0x80 to 0x83
byte1=bitshift(byte1,8); %% remains as dec but shift 8 bits,
byte1msb = byte1; % now should be 0x80xx
byte2=fread(s,1,'char'); %get 2nd byte
count =count +1;
if(byte2>-1 && byte2 <256) %check its valid and A1LSB 0x00 to 0xff
valueA1 = byte1msb + byte2; % add the to dec values together
valueA1 = bitand(uint16(valueA1), uint16(1023)); % get rid of mask
byte3=fread(s,1,'char'); % get 3rd byte
count =count +1;
if (byte3> 191 && byte3<196) % means it is A2 MSB
byte3=bitshift(byte3,8); %% convert to bin, shift bits, returns dec
byte3msb = byte3;
byte4=fread(s,1,'char'); % get 4th byte
count =count +1;
if(byte4>-1 && byte4 <256) %check its valid
valueA2 = byte3msb + byte4; % add the to dec values together
valueA2 = bitand(uint16(valueA2), uint16(1023)); % get rid of mask
byte5=fread(s,1,'char'); % get 5th byte time
count =count +1;
if (byte5> 63 && byte5<79); % means it is A3 MSB
byte5=bitshift(byte5,8); %% convert to bin, shift bits, returns dec
byte5msb = byte5;
byte6=fread(s,1,'char'); % get 4th byte
count =count +1;
if(byte6>-1 && byte6 <256) %check its valid
valueA3 = byte5msb + byte6; % add the to dec values together
valueA3 = bitand(uint16(valueA3), uint16(4095)); % get rid of A3 mask
Appendices
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Appendices
count2=count2+1;
data(row,5)=count2;
data(row,column) = valueA1; %store data 1st two bytes
column=column+1;
data(row,column)= valueA2; %store 2nd two bytes
column = column +1;
data(row,column) = valueA3; %store the time between reads
column = column +1;
data(row,column) = count; %store the incremental count
row=row+1;
column=column-3;
byte1=-1;
byte2=-1;
byte3=-1;
byte4=-1;
byte5=-1;
byte6=-1;
notCheckedByte2 =1;
notCheckedByte3 =1;
notCheckedByte4 =1;
%display('end of reassinging to -1');
end
end
end
end
end
end
% byte1 end
%timeFinished = s xlswrite(fileName, data); % store data to file fclose(s); delete(s); clear s; display('All done!'); subplot(2,1,1); % plot A1 vs time plot( data(:, 4)*0.0006, data(:,1)/0.0118891, ':o', 'MarkerSize', 2); % convert to force force=A1/0.011889 title('Force vs Time A1'); xlabel('Time (s)'); ylabel('Force (N)'); ymax= max(data(:,2)/0.011889); % get max A1 value
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Appendices xmax= time+0.5; % get max time in s axis([0 xmax 0 ymax]); hold; subplot(2,1,2); %plot A2 vs time plot( data(:, 4)*0.0006, data(:,2)/0.001411, ':o', 'MarkerSize', 2); % convert to force force=A1/0.001411 title('Force vs Time A2'); xlabel('Time (s)'); ylabel('Force (N)'); ymax= max(data(:,2)/0.001411) % get max A2 value xmax= time+0.5; % get max time in s axis([0 xmax 0 ymax]) hold;
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Appendix 5: SolidWorks sketch of holder design
Appendices
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Appendices
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Appendices
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Appendices
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Appendix 8: Scores from other single finger tapping test devices
Appendices
Table taken from study by Christianson & Leathem (2004)
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Appendices
Appendix 9: Trends in the peak force of the single finger tapping test for two users
G Male control Age 53
CIV Male PD user Age 63
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Appendices
Appendix 10: Plotting tap times, data from patient file from iRehab application
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