Lower limb rehabilitation using multimodal measurement of sit-to-stand and stand-to-sit task
Siddharth Bhardwaj, Abid Ali Khan, Mohammad Muzammil
- 发表年份
- 2019
- 引用次数
- 17
摘要
Purpose Assistive and rehabilitation devices are dependent upon detecting the user intent through physiological and kinematics changes. Rising from a chair and vice-versa have been less investigated for the purpose of rehabilitation-aids. This study investigates the muscle activation along with trunk and knee biomechanics in sagittal plane during sit-to-stand and stand-to-sit transfer. Method Nine healthy participants (age 25.67 ± 3.27 years) were measured for flexion/extension of knee and trunk, and for surface electromyography (EMG) of vastus lateralis (VL) and biceps femoris (BF) of both the legs at a speed of 100 beats per minute while performing sit-to-stand and stand-to-sit task. Results The knee flexion angles at peak EMG-RMS (root mean square envelope of EMG) were significantly different for the two tasks (p = 0.002). Also, for each muscle, EMG-RMS peak was obtained at significantly different knee angle within the same task (p = 0.046). EMG work done (WD) was also found to be significantly different for the intervened muscles (p = 0.002). Conclusions Trunk flexion together with VL showed an earlier onset in sit-to-stand task, which might form an important modality for detecting human intention to perform the activity. However, for stand-to-sit task, some other muscle group in conjunction to BF may be useful for detecting the human intention. The understanding from the study could be used as a first step in devising multimodal control for assistive devices aiding sit-to-stand and stand-to-sit transfers. That would be a novel approach to fuse the data of postural deviation into the EMG signal to achieve lower limb rehabilitation or in prosthetic control.Implications for rehabilitationMulti-modal sensor fusion can be used for realtime monitoring of patient biomechanics.Development of control algorithms for assistive devices aiding sit-stand transfers.Sensor fusion will help in achieving greater robotic compliance rehabilitation.
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