Abstract
This work presents the development of a new algorithm for the control of robotic and prosthetic hands: the proposed architecture is made of an EMG wearable sensor and a personalized Graphical User Interface (GUI). The proposed system inherits and processes eight EMG signals which are locally amplified and rectified within the wearable device: then a signal classifier allows piloting a 2 degree of freedom cursor on the GUI in order to reach a provided target in the Cartesian space. The aim of this study is to finally provide a user-friendly interface for training human subjects on reaching movements with the EMG signals of their forearm muscles. This approach as twofold objectives: (1) to maintain, train and support the muscular tone and (2) to provide an interface for the physiotherapy and preparation of prosthetic use in daily life.
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Acknowledgements
This work was presented in report form in fulfillment of the requirements for the Internship for the student Philippe Cadett under the supervision of Dr. Emanuele Lindo Secco from the Robotics Laboratory, School of Mathematics, Computer Science and Engineering, Liverpool Hope University.
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Secco, E.L., Caddet, P., Nagar, A.K. (2020). Development of an Algorithm for the EMG Control of Prosthetic Hand. In: Nagar, A., Deep, K., Bansal, J., Das, K. (eds) Soft Computing for Problem Solving 2019 . Advances in Intelligent Systems and Computing, vol 1139. Springer, Singapore. https://doi.org/10.1007/978-981-15-3287-0_15
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DOI: https://doi.org/10.1007/978-981-15-3287-0_15
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