Machine Learning and Sensor Technology for Hand Prosthesis Control

Dear Colleagues,

The human hand is a unique and complex prehensile appendage of the human body that allows for a tremendously flexible interaction with the outside world. It offers many degrees of freedom that we learn to control intuitively through various life experiences. The absence or loss of such a tool, through a traumatic event or congenital amputation, leaves a void that is uniquely challenging to fill. For decades, hand prosthetic technologies have seen progress in the functionalities of the prosthetic hand device itself, while the control interface has remained rudimental. For this reason, prosthetic hand devices have encountered important resistance in user acceptance, as they do not properly address people’s needs. The main challenge is, generally, to provide a control method that is both easy to learn and use, and highly functional. These criteria often require compromises, as more functionality typically means more complicated use, while limited functionality means easier use. With the recent advances in machine learning and the possibility of deploying its methods in embedded systems, new paradigms are being unlocked in signal processing and sensor technologies, notably when applied to hand prosthetic control. These novel technological tools allow researchers to reimagine human–machine interfaces and show great potential for overcoming the challenges of traditional hand prosthetic control technologies.

This Special Issue of MDPI Sensors aims to collect original research papers and critical reviews that relate to current hand prosthetic topics such as:

• Wearable sensors and systems for hand prostheses;
• System design for patient acceptability;
• 1D and 2D EMG acquisition, analysis and processing;
• Machine learning in hand prosthetic control;
• Pattern recognition and machine learning for hand gestures;
• Neural networks for embedded control;
• Wireless low-power control;
• Other relevant topics. 

Prof. Dr. Mounir Boukadoum
Prof. Dr. Benoit Gosselin
Guest Editors

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