Journal of Medical and Biological Engineering, 26(1): 21-28
21
Multi-transducer Data Logger for Worksite Measurement of
Physical Workload
Yung-Ping Liu
Hsieh-Ching Chen*
Chih-Yong Chen1
Department of Industrial Engineering and Management, Chaoyang University of Technology, Taiwan, 413 ROC
1
Institute of Occupational Safety and Health, Council of Labor Affairs, Executive Yuan, Taiwan, 221 ROC
Received 29 Sep 2005; Accepted 10 Dec 2005
Abstract
This study developed a multi-channel data logger adopting transducers of electromyography (EMG), electrical
goniometry, and accelerometer for onsite measurement of the physical workload of workers. The logger was equipped
with a LCD module for displaying operational information and the real-time waveform of the acquired signal. A
built-in RF receiver allows the user to send digital signals remotely to register events or synchronize the logger with an
external video camcorder. The logger can continuously acquire 14 channels of 16-bit analog signals as well as a digital
signal at a rate of 1000 Hz for over 6 hours when powered by a 2000 mAh Li-ion rechargeable battery. The data
obtained was saved on a CompactFlash (CF) memory card which can be downloaded to a personal computer for future
analysis. This study documents the architecture and capacities of the logger in detail. The assessment of the practical
test demonstrated that the logger is suitable for worksite and field measurement of physical workload.
Keywords: Goniometry, EMG, accelerometer, physical workload
Introduction
Work related musculoskeletal disorders have been
attributed to risk factors such as inappropriate postures,
excessive manual force and a high rate of manual repetitions
[1-5]. Mechanically exposing these risk factors quantitatively
can help in assessing the physical workload of individuals and
in identifying the significant risk factors of work related
hazards [6, 7]. However, performing measurement on worksite
requires some special equipment that is mostly portable or
wearable, light weight, battery powered, and capable of storing
or telemetering data. Consequently, portable data loggers or
telemetry devices are widely applied at worksites to measure
the physical workload of workers performing various
industrial tasks [8-14]. These studies used analog data
collected by loggers or telemetry devices, including joint
angles, heart rate, electromyography (EMG) of measured
muscles, inclination of neck, trunk, upper arms, and so on.
Conventional data loggers have a restricted ability to store
large amounts of data and so are normally limited by problems
of low sampling rate, short sampling period or only storing
periodically processed data. Such loggers are often seen in
clinical applications such as EKG or blood pressure
monitoring, measurement of instrumented shoes, or industrial
applications such as weather monitoring, noise or vibration
dosimeters. Applying data loggers to measure physiological
* Corresponding author: Hsieh-Ching Chen
Tel: +886-4-23323000 ext. 4255; Fax: + 886-4-23742327
E-mail: hcchen@cyut.edu.tw
signals such as EMG generally requires a minimum sampling
rate of 1000 Hz. Acquiring data at such a rate rapidly fills the
data storage space and thus limits the maximum sampling time.
Furthermore, most loggers do not permit users to flexibly
integrate different types of transducers according to the needs
of a specific measurement task. Consequently, a data logger
with adoptability of various transducers and the capability of a
long-period of data collection is more suitable for field or
worksite measurement of physical worker workload.
This study develops a multi-transducer data logger system,
capable of displaying real-time signal waveforms and
collecting data over extended periods. The architecture and
capacities of the logger are documented in detail.
Materials and methods
2.1. Hardware architecture
The logger had dimensions 170mm×160mm×5.5mm, and
weighed 720g, including the battery and a CF memory card
(Fig. 1). The data logger, powered by a 7.2V rechargeable
Li-ion battery, comprises surface mounted circuit boards of
signal acquisition and digital control modules (Fig. 2). This
hardware architecture enables users to simply exchange the
signal acquisition module for adopting different types of
transducers in the long term. The logger can simultaneously
record three types of analog inputs (electrical goniometry,
EMG, and accelerometer). Different types of analog inputs
were processed using a different conditioning circuitry of the
22
J. Med. Biol. Eng., Vol. 26. No. 1 2006
Figure 1. External appearance of the data logger, a biaxial goniometry, an EMG transducer, and a tri-axial accelerometer.
Figure 2. Hardware architecture of the data logger.
signal acquisition module before connecting to an
analog-to-digital (A/D) converter. Analog inputs from external
transducers were connected to the signal acquisition module
via Lemo connectors. Eight 4-pin and two 5-pin connectors
located at the top side of the logger were used to connect
electrical goniometers and/or EMG transducers, and tri-axial
accelerometers, accordingly. These connectors also provided
access to any pre-amplified analogue signals, ranging from 0
to +5V, to an A/D converter. Three other connecters located at
the side of the logger are used to connect the ground reference,
rechargeable battery, and RF antenna, respectively.
An 8-bit microprocessor (C8051F120, Silicon
Laboratories, USA) powered by 3.3V was employed to operate
the logger. The clock frequency of the microprocessor was set
to 98 MHz using a programmable internal oscillator with the
on-chip phase-locked loop (PLL). Since the internal timer
register of the microprocessor triggered the sampling events,
this internal oscillator determined the sampling rate accuracy.
To improve the sampling rate accuracy and avoid data loss, the
simultaneous sampling scheme was employed to concurrently
trigger the data conversion of 2 A/D converters. The timer
register issued the interrupt at a rate of 1 kHz to initiate each
A/D conversion for the first channel, and to minimize the
time-lag between channels. Meanwhile, the sampling of the
Multi-transducer Data Logger
23
Figure 3. Structure of trial data saved on the CF memory card.
succeeding channels was conducted consecutively at the
maximum speed. Each A/D converter (ADS8344, Texas
Instruments Inc., USA) had an 8-channel multiplexer, 16-bit
resolution, and a maximum sampling rate of 100 kHz. The
typical power dissipation of each A/D converter was 10mW at
100 kHz throughput rate and +5V supply. The input range was
set to +5V using a voltage reference (LT1790-5, Linear
Technology Corp., USA) with a drift of 10 ppm/℃.
2.2. Signal acquisition module
The signal acquisition module was powered by ±5V,
where +5V was provided by a positive low dropout regulator
(LT1117-5, Linear Technology Corp., USA) converted directly
from the 7.2V Li-ion rechargeable battery. A monolithic
CMOS switched-capacitor voltage converter (LTC660, Linear
Technology Corp., USA) was used to provide -5V by
converting the +5V supply of the LT1117-5 regulator. Two
analog circuitries, goniometer/EMG and accelerometer, were
built in the signal acquisition module. The analog signal of
each circuit was converted via a separate A/D converter.
A. Goniometer / EMG circuitry:
The circuitry adopts both goniometers and EMG
transducers up to a total of 8 channels. The circuitry provides
+2V excitation voltage for flexible goniometers (SG series,
Biometrics Ltd, UK) and EMG transducers (SX230,
Biometrics Ltd, UK) via two low noise, low dropout regulators
(LT1761-2, Linear Technology Corp., USA). These
strain-gauge based goniometers have an accuracy of ±2° and
repeatability of ±1° measured over a range of 90° [15]. The
gain of the amplifiers (INA118, Texas Instruments Inc., USA)
was set to 500 by setting the corresponding jumper on the
module board to yield a resolution of 0.006°/AD-unit and a
span of ±200°. Unlike the goniometers, the EMG transducer
has an internal circuitry which pre-amplifies the EMG signal
by 1000. Under such a condition, the amplification gain of the
channel was set to 1 by setting the corresponding jumper on
the module board. The signal of each channel was low-pass
filtered individually with an 8th order progressive elliptic filter
(LTC1069-1, Linear Technology Corp., USA) prior to A/D
conversion. The cutoff frequency of the individual filter can be
set via a jumper located on the module board. The cutoff
frequency set for the goniometers was -20 dB at 20 Hz, while
that for EMG was -20 dB at 500 Hz.
B. Accelerometer circuitry:
The accelerometer circuitry adopts two iMEMS
(integrated Micro Electro Mechanical System) tri-axial
accelerometers (LP series, Crossbow Technology Inc., USA),
each consisting of three analog output signals. Since these
accelerometers have built-in circuitry for excitation, low-pass
filtering, and pre-amplification, they were powered directly by
+5V supply and connected to the A/D converter. These
accelerometers behave like inclinometers under quasi-static
conditions [16].
2.3. Digital control module
The digital control module was powered by +3.3V,
provided by a LT1117-3 regulator, and by +5V, provided by a
LT1117-5 regulator, from the 7.2V Li-ion rechargeable battery.
This module consists of digital I/O circuitries for controlling
data storage, LCD module, and RF synchronization.
A CompactFlash memory card (CF card) with a storage
capacity of 512 Mbytes or higher was used. CF memory card
was selected because of being a currently popular removable
mass storage device, roughly the size of a matchbook, and
weighing just 14 grams. The collected data were written to the
CF card byte by byte using 28-bit logical block addressing,
which can address up to 137G bytes of data. The first sector
(512 bytes) of the CF storage was reserved for the trial
allocation table (TAT). Moreover, the starting sector and data
length for each trial was saved using four bytes of TAT sector
sequentially. This allocation table permits trial information to
be stored for up to 64 trials. Data of each trial were saved by a
structure comprising a 32-byte header for storing sensor type
information. Each sample collected for a channel takes two
bytes, and was saved sequentially following the 32-byte header.
Figure 3 illustrates the data structure of each trial. Every data
record comprises 32 bytes, with bytes 1-16 and bytes 17-28
storing data from goniometers/EMGs and tri-axial
accelerometers, respectively. Moreover, bytes 29-30 of each
32-byte record were used to store the digital event, described
below, while bytes 31-32 of the record were used to store a
randomly generated code. This code was generated for each
trial to avoid unintentional data loss, in case of tracing and
recovering trial data that was not properly registered in the
allocation table.
A 128×64 dot graphic LCD module (LMG-SSC12A64,
J. Med. Biol. Eng., Vol. 26. No. 1 2006
24
Table 1. Button functions and information displayed by LCD at different operation modes.
Operation
LCD display
mode
information
A
“Start/Enter”
B
“Stop/Cancel”
C
“Switch”
Main
F.M./Acq. option
Enter
n.f.
Switch F.M./Acq. mode
File Management
1. CF information
2. file # saved
3. ch setup
Enter
Cancel; back to Main
Switch CF information /
erase file
Start; enter Waveform
Cancel; back to Main
n.f.
Switch 4-ch page
(pg0~pg4)
Stop; back to Acquisition
Switch ch0~ch16
(ch0 display page of 4-ch)
Acquisition
1. battery status
2. event status
3. CF space left
Waveform
signal waveform
Button
n.f. denotes ‘no function’
SDEC Technology Corp., Taiwan) was adopted to display the
information of operation modes. With the information
displayed on the LCD module, users can control the logger,
check signal quality, and manage the data files stored on the
CF card manually via the control buttons. For simplicity and to
avoid erroneous operations, only three buttons were used, for
the functions of ‘Start/Enter’, ‘Stop/Cancel’, and ‘Switch’,
respectively. The LCD displays information such as remaining
memory and battery capacity, status of event marker, real-time
signal waveform during data acquisition. Table 1 lists the
functions of the buttons and the information displayed by the
LCD module at different operating modes.
A set of 315MHz RF receiver module (RWS-371-3,
Wenshing Electronics Co. Ltd., Taiwan) and decoder IC
(PT2272, Princeton Technology Corp., Taiwan) was used to
register externally triggered events and synchronize the logger
and video camcorder. A companion 315MHz RF transmitter
(TWS-BS-3, Wenshing Electronics Co. Ltd., Taiwan) was
employed by the user to send event signals encoded by the
encoder (PT2262, Princeton Technology Corp., Taiwan) to the
receiver. The video camcorder can simultaneously record the
event based on the illuminated LED on the RF transmitter.
When collecting analog data, the microprocessor
simultaneously collected the decoded events from the RF
receiver via the digital I/O port. The digital event was
displayed on the LCD, and was saved on the CF card together
with the analog data as the 15th channel. The RF transmitter
and receiver both work at +5V, and have a 30m transmission
distance in an open field.
Operated using a battery, a low-battery detection circuitry
was implemented in the digital control module for maintaining
the quality and safety of the collected data. The
microprocessor automatically stopped data acquisition when
the battery ran low.
2.4. Preliminary data reorganization
Companion software with the following three functions
was designed: (1) Erasing memory cards, using the CF card
reader available on most lap-top computers. (2) Consecutively
organizing the file names on memory cards. (3) Copying data
of selected channels to another file.
Implementation and applications
The data loggers developed here have been successfully
applied in several studies of worksite occupational workload in
combination with ‘Viewlog’ analysis software, to provide a
quantified index of physical workload [17, 18]. Industrial tasks
investigated in this studies included in-line assembly of
desktop sawing machine, automobile engine and chassis,
circuit board examination, and antenna assembly on
communication tower. Besides the above published studies, the
following describes two special applications of the logger
system:
3.1. Application I
A 50-year old truck driver drove a truck 12 hours a day,
6-7 days a week, on unleveled roads. Besides transporting
earth, sand, or stone, the truck was also used to dump waste
pitch or clay. The empty truck weighed about 13 tons, and was
usually loaded up to a total weight of 30 or 40 tons. The driver
frequently dumped 40-60 loads per day. The driver suffered
bilateral numbness of hands and received cervical herniated
intervertebral disc (HIVD), believed to be work related.
To assess the occupational hazard associated with shock
impact during trunk unloading, the data logger and a
camcorder were synchronized to record the dumping process.
Furthermore, an electrical goniometry and two tri-axis
accelerometers were employed to measure the physical
parameters at the head and neck of the truck driver. The driver
was tested with one end of the goniometer attached to C3 of
the posterior neck and the other end to C1, and with the
accelerometers attached to the occipital and C7, respectively,
while the logger was secured on the passenger side seat. Figure
4 illustrates the ‘Viewlog’ analysis environment with
synchronized video and collected data waveforms.
During dumping, the truck head sharply rises to around
88cm above the ground and then suddenly falls following earth
unloading. The neck of the driver exhibited violent vertical
swinging as well as some neck deviation when viewing the
rear-view mirror to oversee this process. The driver also
suffered from bump force during unloading. The measurement
results demonstrated that vibration and shock produced
Multi-transducer Data Logger
25
Figure 4. Synchronized data and video image shown using ‘Viewlog’ software.
Figure 5. Overall head acceleration of the subject during the
measurement period (A: truck begins to move and
unload; B: truck stop bumping)
acceleration of up to 9G involving the head, neck and shoulder
of the driver during this process (Fig. 5). Additionally, the
induced maximum neck flexion was approximately 20 degrees.
Following earth emptying, the driver was dragged forward by
continual up and down swing and vibration for about 2 to 3
seconds following impact. Quantified measurement results
were then provided to a domestic profession of occupational
diseases for conducting further investigation. In this rigorous
case, the logger system proved capable of obtaining
multi-transducer signals for quantifying the critical workload
factors.
3.2. Application II
A 50-year old female punch press operator worked for a
metal processing factory over 10 years. She worked in-line and
pressed around 1200 to 1500 steel wheel rims a day, 6 days a
week. The most strenuous task mentioned by the worker was
grabbing the rim and a metal cover, putting them into a presser,
and pushing the control button. The weight of a rim ranged
from 4 to 10 kg. She was annoyed by the numbness of bilateral
hands and was suffered from trigger-finger believed to be work
related.
To assess the occupational hazard associated with forceful
exertion and repetitive motion of hands, the data logger and a
camcorder were synchronized to record the pressing process.
Two biaxial goniometers were employed to measure both right
and left dorsal-palmer flexion and radial-ulnar deviation of
wrist angles. Four EMG electrodes were placed over the right
and left flexor digitorum and extensor digitorum of the worker
to record the relevant muscular activities. A series of
calibrations were then conducted to obtain individual reference
of wrist angle and the maximal voluntary capacity of each
muscle. The recorded EMG signals were later used to
normalize the EMG signal recorded during task performance
by expressing them as a percentage of the maximal voluntary
capacity (%MVC). For detail on the calibration procedure see
Chen et al. [18].
The logger was carried on a waist belt by the worker
while performing pressing task. Bilateral EMGs and wrist
angles were recorded for a period of 20 minutes (Fig. 6).
During the period over 60 successive work cycles were
recorded. ‘Viewlog’ software was later used to calculate the
mean wrist angle and root mean square value of EMG for
epochs of 0.2s for characterizing wrist movement and
muscular activity. The wrist angle during work was
characterized by the extreme positions, 5th and 95th percentile
of the amplitude probability distribution function (APDF), of
the angular distribution. The 95th percentile APDF of root
mean square EMG was used to describe the peak muscular
load. The APDF of bilateral wrist angles and EMGs were
illustrated in Figure 7 and 8, respectively. The analytical
results demonstrated that the left and right wrists were
operated at an dorsal flexion position for over 97% and 73% of
the period. Notably, the bilateral wrists were both operated at
ulnar position for over 98% of the period. There was 37% left
extensor digitorum EMG and 32% right extensor digitorum
EMG exceeds the 21% MVC limit recommended by Byström
J. Med. Biol. Eng., Vol. 26. No. 1 2006
26
(a)
(b)
Figure 6. The subject (a) grabbed a rim and (b) put the rim into a presser. The logger was carried by her lower back.
100
8
80
Left densit y
7
70
Left cumulative
6
60
Right density
5
Right cumulat ive
50
4
40
3
30
2
20
1
10
0
0
- 30
- 20
- 10
0
10
20
30
40
50
Dorsal
6
Palmer
100
90
5
Cumulative probability (%)
90
Cumulative probability (%)
Probability density (%)
Ulnar
9
Probability density (%)
Radial
10
80
4
Left density
70
Left cumulative
60
Right density
3
Right cumulat ive
2
50
40
30
20
1
10
0
-80
60
-60
-40
-20
0
20
40
60
0
Wrist angle(deg)
Wrist angle(deg)
(a)
(b)
Figure 7. APDF of mean wrist angle in (a) radial-ulnar (b) dorsal-palmer direction.
8
100
5
4
Left cumulative
60
Right density
50
Right cumulat ive
3
40
30
2
20
1
10
0
0
20
40
60
80
0
100
Extensor digitorum EMG(%MVC)
Probabi lity densi ty (%)
Probability densi ty (%)
70
Left densit y
80
12
70
Left densit y
10
60
Left cumulative
8
6
Right density
50
Right cumulative
40
30
4
20
2
Cumulat ive probability (%)
6
90
14
Cumulat ive probability (%)
80
100
16
90
7
10
0
0
20
40
60
80
0
100
Fl exor digitorum EMG(%MVC)
(a)
(b)
Figure 8. APDF of root mean square EMG at (a) extensor digitorum (b) flexor digitorum muscle.
[19] for intermittent tasks. Also, over 20% bilateral flexor
digitorum EMG exceeds that limit.
The quantified workload was found to be higher than that
of several reported cases of carpal tunnel syndrome [17].
Analytical results from this case were provided to the Institute
of Occupational Safety and Health for further investigation.
Results and discussion
Recently, the measurement of physical load at a worksite
has gradually become a new research field. As mentioned,
several researchers have applied data logger to investigate the
workload of various tasks [8-14]. In these studies, quantified
data on EMG activities, repetitiveness of joint movements,
elevation of upper arms, and amplitude probability density
function (APDF) of joint angles were derived for ergonomic
comparison and documenting the measured workload. The
logger system reported in this study can achieve all of the
above parameters.
4.1. System capacity
The power consumption during sampling was 145mA for
the logger without an external load. When loading with four
EMG transducers, four goniometers, two tri-axial
accelerometers, and a 512 Mb CF memory card, the data
logger consumed 190mA at a 1 kHz sampling rate. According
to the test results, a 7.2V battery with 2000 mAh capacity can
support the fully loaded logger in operating continuously for
up to six hours (Table 2). In situations involving a longer
acquisition time, a 7.2V battery with 4000mAh capacity can
fulfill most requirements, though at the cost of increasing
weight. Since the battery is connected to the logger externally,
replacing the battery is a feasible alternative.
Multi-transducer Data Logger
27
Table 2. Outline of the logger specifications and capacity.
Recording capacity
Specifications
capacity
Sampling rate
1000 Hz/channel
Number of channels
14 analog + 1 digital
CF card size
512 Mb
1 Gb
266 min
532 min
The storage capacity of the logger depends on the storage
size of the CF card used. A 512 Mbytes memory card is
sufficient for 266 minutes of recording (Table 2). When the CF
card becomes full, the logger stops recording data
automatically. For extended recordings, the card must be
exchanged or simply replaced with a memory card of higher
storage capacity. Since the recordings generally last for hours,
the exchange of CF cards or batteries, which takes just a few
seconds, does not significantly affect the results.
4.2. Synchronization and event registration
The RF synchronization function of the logger has several
applications. Multiple events can be registered by sending
different encoded signals to the logger remotely. This allows
us to apply the technique reported by Forsman et al. [20] to
synchronize the display of collected data and the recorded
video via of ‘Viewlog’ software to investigate the physical and
biological response of various working methods. With the
synchronization technique, ‘Viewlog’ software can be used to
assign a specified physical workload to work activities based
on video recordings as documented by Engströn and Medbo
[21]. Besides the above functions, the synchronized technique
applied in the logger system reported here permits users to
synchronize several systems and integrate data from multiple
sources. For example, the synchronizing signal can be sent to a
separate logger and a video camcorder with one receiver built
in the logger and the other with LED placed where it can be
easily captured by the camcorder.
4.3. Field measurements
Various practicalities must be considered when applying
the logger to measure actual workplace workload. The
individual taking the measurements must place and connect the
transducers securely. Before taking the measurements, the
quality of the transducer signals should be checked by
observing the LCD waveform of each channel to avoid
problems such as loose connections, noise interference,
transducer failure, bad grounding, wire break off, and so on.
EMG has been reported to have a large inter-individual
variation in the recorded amplitude, owing to, for instance,
differences in the thickness of the subcutaneous fat layer.
Furthermore, heat stress usually causes subjects to sweat
leading to degenerated EMG signals. To avoid unintentional
data loss, signal waveforms shown by the LCD module should
be monitored before and during data recording. In certain cases,
the eye-detected problem can be eliminated by switching
cables, replacing transducers, using proper skin preparations,
and so on.
Adequate trials of signal calibration such as registration
of reference positions and maximum voluntary contractions
should be performed prior to conducting any memoranda and
Power consumption
Li-ion Battery life time
(fully loaded)
2000 mAh
4000 mAh
190 mA
360 min
720 min
detailed protocols. This situation can be stressful, particularly
if the subject is working in a group or on a production line, and
any delay in the preparation of data collection, or trouble
during the recordings, will influence other workers and/or
interfere with the production [22]. Experience demonstrates
that three well-trained persons can apply the transducers, and
record the corresponding calibrations, test contractions and
reference positions, for eight channels of EMG or goniometers,
and two tri-axial accelerometers, in about 40 minutes.
This study demonstrated the presented data logger,
together with the associated analysis software, to be an
adequate tool for measuring worker physical workload via
testing in the field and on several worksites.
Acknowledgements
The authors would like to thank the Institute of
Occupational Safety and Health, the Council of Labor Affairs,
Taiwan (Contract No. IOSH92-H121, IOSH93-H103) and the
National Science Council of the Republic of China, Taiwan
(Contract No. NSC 90-2218-E-324-003) for financially
supporting this research.
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