A Wearable Ultrasound Interface for Prosthetic Hand Control

• Published in: IEEE journal of biomedical and health informatics Vol. 26; no. 11; pp. 1 - 11
• Main Authors: Yin, Zongtian, Chen, Hanwei, Yang, Xingchen, Liu, Yifan, Zhang, Ning, Meng, Jianjun, Liu, Honghai
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.11.2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: A-mode ultrasound; Algorithms; Classification; Control equipment; Decoding; Deformation; gesture recognition; Miniaturized ultrasound system; Modules; Muscles; Performance evaluation; Probes; Prostheses; Prosthetic hand; prosthetic hand control; Sensors; Sockets; Transducers; Ultrasonic imaging; Ultrasound; Wearable technology
• ISSN: 2168-2194; 2168-2208; 2168-2208
• DOI: 10.1109/JBHI.2022.3203084

Ultrasound can non-invasively detect muscle deformations and has great potential applications in prosthetic hand control. Traditional ultrasound equipment was usually too bulky to be applied in wearable scenarios. This research presented a compact ultrasound device that could be integrated into a prosthetic hand socket. The miniaturized ultrasound system included four A-mode ultrasound transducers for sensing musculature deformations, a signal excitation/acquisition module, and a prosthetic hand control module. The size of the ultrasound system was 65*75*25mm, weighing only 85g. For the first time, we integrated the ultrasound system into a prosthetic hand socket to evaluate its performance in practical prosthetic hand control. We designed an experiment requiring twenty subjects to perform six commonly used gestures. The performance of decoding ultrasound signals was analyzed offline using four classification algorithms and then was assessed in online control. The average values of online classification accuracy with and without wearing the physical prosthetic were 91.5<inline-formula><tex-math notation="LaTeX">\pm 6.4\%</tex-math></inline-formula> and 96.5<inline-formula><tex-math notation="LaTeX">\pm 3.0\%</tex-math></inline-formula>, respectively. We found that wearing the prosthetic hand influenced the ultrasound gestures classification accuracy, but remarkable online classification performance could still be maintained. These experimental results demonstrated the efficacy of the designed integrated ultrasound system for practical use, paving the way for an effective HMI system that could be widely used in prosthetic hand control.