Analysis of knee joint kinematics during walking in patients with cerebral palsy through human motion capture and gait model-based measurement

2012 ◽  
Author(s):  
Amir Ijaz ◽  
Sheila Gibbs ◽  
Rami Abboud ◽  
Weijie Wang ◽  
Dong Ming ◽  
...  
Keyword(s):  
Cerebral Palsy ◽  
Knee Joint ◽  
Motion Capture ◽  
Human Motion ◽  
Joint Kinematics ◽  
Human Motion Capture ◽  
Model Based ◽  
Knee Joint Kinematics

scholarly journals A Textile Sensor for Long Durations of Human Motion Capture

Sensors ◽  
2019 ◽  
Vol 19 (10) ◽  
pp. 2369 ◽  
Author(s):  
Sufeng Hu ◽  
Miaoding Dai ◽  
Tianyun Dong ◽  
Tao Liu
Keyword(s):  
Knee Joint ◽  
Motion Capture ◽  
Sports Medicine ◽  
Low Cost ◽  
Movement Analysis ◽  
Human Motion ◽  
Joint Movement ◽  
Human Motion Capture ◽  
Knee Joint Motion ◽  
Textile Sensor

Human posture and movement analysis is important in the areas of rehabilitation, sports medicine, and virtual training. However, the development of sensors with good accuracy, low cost, light weight, and suitability for long durations of human motion capture is still an ongoing issue. In this paper, a new flexible textile sensor for knee joint movement measurements was developed by using ordinary fabrics and conductive yarns. An electrogoniometer was adopted as a standard reference to calibrate the proposed sensor and validate its accuracy. The knee movements of different daily activities were performed to evaluate the performance of the sensor. The results show that the proposed sensor could be used to monitor knee joint motion in everyday life with acceptable accuracy.

scholarly journals Closing the Wearable Gap—Part VIII: A Validation Study for a Smart Knee Brace to Capture Knee Joint Kinematics

Biomechanics ◽  
2021 ◽  
Vol 1 (1) ◽  
pp. 152-162
Author(s):  
Alana J. Turner ◽  
Will Carroll ◽  
Sachini N. K. Kodithuwakku Arachchige ◽  
David Saucier ◽  
Reuben F. Burch V ◽  
...  
Keyword(s):  
Knee Joint ◽  
Motion Capture ◽  
Knee Flexion ◽  
Goodness Of Fit ◽  
Weight Bearing ◽  
Critical Role ◽  
Joint Kinematics ◽  
Knee Brace ◽  
Flexion Extension ◽  
Knee Joint Kinematics

Background: Wearable technology is used by clinicians and researchers and play a critical role in biomechanical assessments and rehabilitation. Objective: The purpose of this research is to validate a soft robotic stretch (SRS) sensor embedded in a compression knee brace (smart knee brace) against a motion capture system focusing on knee joint kinematics. Methods: Sixteen participants donned the smart knee brace and completed three separate tasks: non-weight bearing knee flexion/extension, bodyweight air squats, and gait trials. Adjusted R2 for goodness of fit (R2), root mean square error (RMSE), and mean absolute error (MAE) between the SRS sensor and motion capture kinematic data for all three tasks were assessed. Results: For knee flexion/extension: R2 = 0.799, RMSE = 5.470, MAE = 4.560; for bodyweight air squats: R2 = 0.957, RMSE = 8.127, MAE = 6.870; and for gait trials: R2 = 0.565, RMSE = 9.190, MAE = 7.530 were observed. Conclusions: The smart knee brace demonstrated a higher goodness of fit and accuracy during weight-bearing air squats followed by non-weight bearing knee flexion/extension and a lower goodness of fit and accuracy during gait, which can be attributed to the SRS sensor position and orientation, rather than range of motion achieved in each task.

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