Poster Knee OA, Tatiana Bejarano

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Study of biomechanical patterns for identifying biomarkers for knee osteoarthritis
Tatiana
1Adaptive
1
Bejarano ,
Dinesh
1
Bhatia ,
Mario
2
Novo ,
Marcos
2
Munoz ,
Denis
2
Brunt ,
Ranu
Neural Systems Lab, College of Engineering & Computing: Department of Biomedical Engineering, 2College of Nursing & Health Sciences: Physical Therapy Department , Florida International University.
Abstract
Experimental Protocol
Osteoarthritis (OA) is a chronic joint disease, the most common musculoskeletal
complaint worldwide, and is associated with significant health and welfare costs.
Previous research indicates that co-activation of muscles may lead to the onset of
knee OA. Therefore, investigation of muscle recruitment patterns and neuromuscular
efficiency in healthy individuals compared to patients with knee OA in simple closed
chain exercises using electromyography (EMG), motion analysis system and force
plates may lead to a better understanding of how knee OA develops (6). The present
studies chosen were in the frontal plane while performing lateral step up and step
down tasks for a 4 inch and 8 inch step height. In the stepping tasks it was discovered
that there is a greater magnitude EMG and ground reaction force (GRF) for 8 inch
rather than a 4 inch step. Additionally, a higher activation of gluteus medius, gluteus
maximus and quadriceps muscles (rectus femoris , vastus lateralis , vastus medius)
was revealed in both the stepping tasks.
Osteoarthritis (OA) is a progressive joint diseases characterized by joint
inflammation, pain and disability leading to loss of function and is one of the top
five most disabling conditions that affects more than one-third of people greater
than 65 years with an average estimation of about 30 million Americans currently
affected by this disease (1). The majority of osteoarthritis cases are observed at
the knee, which is the most commonly affected joint of the lower limb. As has been
previously discovered, different muscle groups work in synchronization to perform
a given task, meaning the activity of one muscle may affect another (2, 3). With
these findings it became evident that investigation of muscle recruitment patterns
and neuromuscular efficiency in healthy individuals compared to patients with
knee OA in simple closed chain exercises might lead to a better understanding of
how knee OA develops (4). Although some studies have reported abnormal
muscle activity in patients with OA, there are no studies that describe the
modulation of this activity due to, for example, a change in velocity or distance of
movement. change in time or distance (7) both in normal control and after OA.
Analysis & Results
Step-up (Figure 1)
Research Goal
Determine the muscle recruitment patterns and
neuromuscular efficiency in healthy individuals
compared with knee OA patients while performing
closed chain exercises in frontal plane.
Data capturing of raw EMG and
GRF data
Signal Processing in Visual 3D
(500 Hz LP, 20 Hz HP, 100 ms RMS)
Event marking and identification
of task phases on the GRF and
EMG data
Data analysis using window
graphing tool in Visual 3D
Lateral Step down
from 8 inch Step
Introduction
Result processing using Excel
sheet
During step down GM was more active during initiation
phase (Figure 2 B)
Figure 1 B shows that the 8 inch step force increased by
200% over the 4 inch step
The intensity of muscle activation increased for all
muscles during the lateral stepping down from an 8 inch
step compared with a 4 inch step (Figure 2)
Subjects completed the 8 inch step in relatively less time
duration
GM EMG activity between 4 and 8 inch task increased by
42% (Figure 2 B)
GM and GMax were more active from initiation to end of
stabilization phase (Figure 1 E)
GMax was active but to a lesser extent after the
quadriceps activity (Figure 2 D)
RF was active from beginning of initiation to end of
contact phase
RF, VL and VM activity from beginning of toe-off to
completion of loading phase increased by 69% in the 8
inch task
SM and GAS showed insignificant activity
BF, SM, and ST activity was quite insignificant throughout
the task.
Mean integral values increased for most muscles
(Figure 1 C - E) by approximately 50%
Quadriceps groups increased in duration of activity
thereby becoming more dominantly active
Electromyography Results
Comparison of average EMG and GFR in 4 inch (dotted) and 8 inch (line)
Step Up/ Step Down task phases:
Vertical GRF
Conclusion
 Higher muscle activity patterns in quadriceps, hamstrings, and hip
abductor/extensor.
 Results provide a baseline standard for understanding lower extremity
muscle group activity patterns in lateral side stepping tasks
 Future studies involving OA subjects could prove to show a notable phase
shift in GRF and muscle activity patterns; which may be useful in defining
kinematic and activation patterns for identifying an early onset of the disease.
Initiation
of
Movement
Toe-off
Contact
References
Stability
1.
Methods
Methods
3.
4.
Three trials per subject were recorded employing dual AMTI force plates for measuring
the GRF and EMG was measured using an 8 channel Motion Lab Corp. system, with both
systems sampled at 1000 Hz (2nd order Butterworth filter with 20-500Hz cutoff).
5.
6.
7.
Age: 23-32 years old
Mean Height: 165 cm
Mean Weight: 75 kg
The subject stepped from one force plate to another with the stance leg being stationary. The
recorded EMG data was averaged across these trials for each subject; full wave rectified and
analyzed employing EMG signal processing techniques (3). The GRF data was used to
identify the different phases of movement and matched with the subsequent EMG data in
Visual 3D software.
www.PosterPresentations.com
Step-down (Figure 2)
8 inch step showed greater increase in slope and peak
GRF than the 4 inch step (Figure 1 A - B)
2.
POSTER TEMPLATES BY:
1
Jung
Figure 1: Comparison of 4 inch (dotted) and 8 inch (solid) Step
Up task phases:
1. Initiation of movement, 2. Toe- off, 3. Contact, 4.Stability
A. Stability Leg (Z) GRF
B. Stability Leg (X) GRF
C. EMG Vastus Lateralis
D. EMG Biceps Femoris
E. EMG Gluteus Maximus
Initiation
of
Movement
Take-off
Rana S. H, Bennel K. L., Metcalf B. R., Crossley K. M., 2002, “Delayed onset of Quadriceps activity and altered
knee joint kinematics during stair stepping in individuals with knee Osteoarthritis” Arch Phys Med. Rehabilitation,
83, pp. 1080-1086.
Bhatia D., Bansal G, Joshi D., Anand S., Tewari R.P. 2011, “Coordination between lower limb muscles in different
locomotion activities” International Journal of Biomedical Engineering and Technology, 6 (2), pp. 23-30.
De Luca, C.J. 1997, ‘The use of surface electromyography in biomechanics’, Journal of Applied Biomechanics,
13 (2), pp.135–163.
Childs J.D., Sparto P.J., Fitzgerald G.K., Bizzzini M., Irrgang J.J., 2004 “Alterations in lower extremity movement
and muscle activation patterns in individuals with knee osteoarthritis” Elsevier Science Direct Clinical
Biomechanics, 19, pp. 44-49.
Likivainio T. and Arokoski J.P.A, 2008 “Physical function and properties of Quadriceps femoris muscle in men
with knee Osteoarthritis” Arch Phys Med Rehabil, 89, pp. 2185-2193.
Rana S. H., Hunt M.A., Creaby M.A., Wrigley T.A., McManus F.J., and Bennell K.L., 2010 “Hip Muscle Weakness
in Individuals with Medial Knee Osteoarthritis” Arthritis Care & Research, 62 (8), pp. 1190-1193.
Pai Y.C., Chang H.J., Sinacore J.M., Lewis J.L., 1994 “Alteration in multijoint dynamics in patients with bilateral
knee osteoarthritis”, Arthritis Rheum. Sep., 37 (9), pp.1297-304.
Acknowledgement
Landing
Loading
Response
Stabilization
Figure 2: Comparison of EMG patterns (average trials of one
subject) in different 4 inch (dotted) and 8 inch (solid) Step
Down task phases:
1. Initiation of movement, 2. Take off, 3. Landing,
4.Loading response, 5. Stabilization
A. Contact Leg step down (Z) GRF
B. EMG Vastus Lateralis, (maximum between 1-2)
C. EMG Gluteus Medius, (maximum between 2-3)
D. EMG Gluteus Maximus, (maximum between 3-4)
 I would like to thank the ANS Lab for allowing me to be a part of this team and gain an
insightful experience that I know will benefit me in my future. I would also like to thank
Dr. Dinesh Bhatia and Dr. Ranu Jung who have been very supportive throughout the
research. Lastly, I would like to thank Dr. Denis Brunt and the Physical Therapy
Department, FIU for providing support during data collection in the human performance
lab and guidance during the research.
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