Abstract
Technological advances in multi-articulated prosthetic hands have outpaced the development of methods to intuitively control these devices. In fact, prosthetic users often cite "difficulty of use" as a key contributing factor for abandoning their prostheses. To overcome the limitations of the currently pervasive myoelectric control strategies, namely unintuitive proportional control of multiple degrees-of-freedom, we propose a novel approach: proprioceptive sonomyographiccontrol. Unlike myoelectric control strategies which measure electrical activation of muscles and use the extracted signals to determine the velocity of an end-effector; our sonomyography-based strategy measures mechanical muscle deformation directly with ultrasound and uses the extracted signals to proportionally control the position of an end-effector. Therefore, our sonomyography-based control is congruent with a prosthetic user’s innate proprioception of muscle deformation in the residual limb. In this work, we evaluated proprioceptive sonomyographic control with 5 prosthetic users and 5 able-bodied participants in a virtual target achievement and holding task for 5 different hand motions. We observed that with limited training, the performance of prosthetic users was comparable to that of able-bodied participants and thus conclude that proprioceptive sonomyographic control is a robust and intuitive prosthetic control strategy.
Highlights
There are approximately 50,000 individuals living with upper limb loss in the US1
Our training and prediction strategy was first validated with able-bodied participants
It shows that four out of five motions were predicted with 100% accuracy and key grasp was incorrectly predicted as power grasp in just one out of 25 motion instances (5 participants performing 5 motions each)
Summary
There are approximately 50,000 individuals living with upper limb loss in the US1. Even with more sophisticated grasp decoding algorithms using pattern recognition with multiple electrodes[15,16,17,18,19,20,21], the ability to obtain graded proportional control is limited by the fundamental challenges with sEMG amplitude resolution Other invasive strategies, such as implantable myoelectric systems[22,23,24], targeted muscle reinnervation[25] and peripheral implant[26,27] strategies, can produce more robust graded signals. There continues to be a need for a robust noninvasive strategy that can provide intuitive real-time proprioceptive control over multiple degrees-of-freedom to enable prosthetic users to make full use of advanced commercial hands. Previous research has shown that ultrasound techniques could be used for real-time classification of hand movements by predicting forearm muscle deformation patterns in able-bodied individuals[29,31] as well as individuals with transradial amputation[33]
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