ABSTRACT
The voluntary participation of the paralyzed patients is crucial for the functional electrical stimulation (FES) therapy. In this study, we developed a strategy called "EMG Bridge" (EMGB) for volitional control of multiple movements using FES technique. The surface electromyography (sEMG) signals of the agonist muscles were transformed to stimulation pulses with various pulse width and frequency to stimulate the target paralyzed muscles using MAV/NSS co-modulation (MNDC) algorithm we proposed recently. Motion pattern classification based on linear discriminant analysis (LDA) was included to recognize the motion status and mapping the sEMG detection channel to the corresponding stimulation channel. A prototype EMGB system was built for real-time control of four hand movements. The test results showed that the movements can be reproduced with a successful rate of 92.5±3.5%. The angle trajectory of wrist joint and metacarpal-phalangeal joint can be mimicked with a maximum cross-correlation coefficient > 0.84 and a latency less than 300 ms.
Subject(s)
Electric Stimulation , Electromyography , Hand , Humans , Movement , VolitionABSTRACT
In this paper, a surface multi-pad stimulation electrode with selective characteristics was designed, it was safe to use and easy to mount. Then a wearable and distributed multi-pad functional electrical stimulation (FES) prototype combined with sensing, communication and smart technology was designed, which can achieve a fast, intelligent optimization to determine stimulation electrode sites and comfortable stimulation. In addition, in order to improve the application and convenience of FES in the rehabilitation at clinical and home-setting, an Android application (APP) based on smart phone was designed for running an algorithm of searching optimal stimulation site. The prototype has been validated by performing selective stimulation on one healthy subject, and showed that the FES system can automatically determine the stimulation site.
