Abstract
Nowadays, there are thousands of disabled people around the world who had lost a limb. The majority of them are hand amputees with different level of amputation ranging from elbow disarticulation to upper digits amputation[1]. To bring those people back to normal life, amputees used artificial hand prosthesis controlled by the muscle signal known as Surface Electromyography (sEMG) recorded form the skin surface of residual limb of the amputee. The muscle signal is also commonly named as myoelectric signal. These devices will help amputees to improve their lives and make them self-confident.
It has been reported that EMG activity recorded from the amputee forearm muscles after hand amputation are similar to EMG of healthy subjects [2, 3]. Therefore, there is still an EMG signal when the amputee intends to perform a movement. This fact has inspired researchers to develop EMG signal processing algorithms for the control of a prosthetic hand with the electrical signal of the muscles.
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© 2012 Springer-Verlag Berlin Heidelberg
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Al-Timemy, A., Bugmann, G., Outram, N., Escudero, J., Li, H. (2012). Finger Movements Classification for the Dexterous Control of Upper Limb Prosthesis Using EMG Signals. In: Herrmann, G., et al. Advances in Autonomous Robotics. TAROS 2012. Lecture Notes in Computer Science(), vol 7429. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32527-4_47
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DOI: https://doi.org/10.1007/978-3-642-32527-4_47
Publisher Name: Springer, Berlin, Heidelberg
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