• International Journal of Control, Automation, and Systems
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• v.3 no.2
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• pp.152-158
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• 2005

Commercial lower limb prostheses or orthotics help patients achieve a normal life. However, patients who use such aids need prolonged training to achieve a normal gait, and their fatigability increases. To improve patient comfort, this study proposed a method of predicting gait angle using neural networks and EMG signals. Experimental results using our method show that the absolute average error of the estimated gait angles is $0.25^{\circ}$. This performance data used reference input from a controller for the lower limb orthotic or prosthesis controllers while the patients were walking.

• Korean Journal of Applied Biomechanics
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• v.30 no.1
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• pp.83-91
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• 2020

Objective: The study aimed to develop a functional performance index that evaluates the functional performance of Parkinson's patients, i.e., to integrate biomechanical measurements of walking, balance, muscle strength and tremor, and to use multiple linear regression with stepwise methods to identify the most suitable predictors for the progression of disease. Method: A total of 60 subjects were tested for sub-variables of four factors: walking, balance, isometric strength and hand tremors. Potential independet variables were extracted through correlation analysis of the sub-variables and dependent variables, Hoehn & Yahr scale. And then, a stepwise multiple regression analysis using the potential independent variables was performed to identify predictor of Hoehn & Yahr scale. Results: First, the results of the study showed that physical composition and gait had a relatively more correlated with the progression of the disease, compared to balance and hand tremor. Second, Parkinson's functional performance is characterized by dynamic pattern of walking, such as foot clearance and turning angle (TA) of walking, and a high-explained regression model is completed. Conclusion: The study emphasized the importance of walking variables and body composition in minor pathological features compared to Parkinson's patient's balancing ability and hand tremor. Specifically, it revealed that dynamic walking patterns functionally characterize patients. The results are worth considering when assessing functional performance related to the progression of the disease at the site.