POSTER TEMPLATES BY: www.PosterPresentations.com Study of biomechanical patterns for identifying biomarkers for knee osteoarthritis Tatiana Bejarano 1,

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POSTER TEMPLATES BY: Study of biomechanical patterns for identifying biomarkers for knee osteoarthritis Tatiana Bejarano 1, Dinesh Bhatia 1, Mario Novo 2, Marcos Munoz 2, Denis Brunt 2, Ranu Jung 1 1 Adaptive Neural Systems Lab, College of Engineering & Computing: Department of Biomedical Engineering, 2 College of Nursing & Health Sciences: Physical Therapy Department, Florida International University. 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. Introduction Methods Conclusion References Comparison of average EMG and GFR in 4 inch (dotted) and 8 inch (line) Step Up/ Step Down task phases: 1.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 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 De Luca, C.J. 1997, ‘The use of surface electromyography in biomechanics’, Journal of Applied Biomechanics, 13 (2), pp.135– 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 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 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 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 Acknowledgement Analysis & Results 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 (2 nd order Butterworth filter with Hz cutoff). 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.  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. 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. Step-up (Figure 1)Step-down (Figure 2) 8 inch step showed greater increase in slope and peak GRF than the 4 inch step (Figure 1 A - B) 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 activityBF, 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 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. 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) 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 Toe-offContactStability Initiation of Movement Take-off Landing Loading Response Stabiliza- tion Mean Weight: 75 kg Mean Height: 165 cm Age: years old  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. Lateral Step down from 8 inch Step 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 Result processing using Excel sheet Vertical GRF