A Prototype System for High Frame Rate Ultrasound Imaging based Prosthetic Arm Control
This work addresses the challenge of improving human-machine interfaces for prosthetic arm users, offering a potential alternative to surface electromyography, but it appears incremental as it builds on existing ultrasound imaging methods.
The authors tackled the problem of creating natural control methods for prosthetic arms by proposing a prototype system using high frame rate ultrasound imaging, which achieved over 90% accuracy in classifying four hand gestures in a virtual simulation.
The creation of unique control methods for a hand prosthesis is still a problem that has to be addressed. The best choice of a human-machine interface (HMI) that should be used to enable natural control is still a challenge. Surface electromyography (sEMG), the most popular option, has a variety of difficult-to-fix issues (electrode displacement, sweat, fatigue). The ultrasound imaging-based methodology offers a means of recognising complex muscle activity and configuration with a greater SNR and less hardware requirements as compared to sEMG. In this study, a prototype system for high frame rate ultrasound imaging for prosthetic arm control is proposed. Using the proposed framework, a virtual robotic hand simulation is developed that can mimic a human hand as illustrated in the link [10]. The proposed classification model simulating four hand gestures has a classification accuracy of more than 90%.