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:
There have been significant advances in biosignal extraction techniques to drive external biomechatronic devices or to use as inputs to sophisticated human machine interfaces. The control signals are typically derived from biological signals such as myoelectric measurements made either from the surface of the skin or subcutaneously. Other biosignal sensing modalities are emerging. With improvements in sensing modalities and control algorithms, it is becoming possible to robustly control the target position of an end-effector. It remains largely unknown to what extent these improvements can lead to naturalistic human-like movement. In this paper, we sought to answer this question. We utilized a sensing paradigm called sonomyography based on continuous ultrasound imaging of forearm muscles. Unlike myoelectric control strategies which measure electrical activation and use the extracted signals to determine the velocity of an end-effector; sonomyography measures muscle deformation directly with ultrasound and uses the extracted signals to proportionally control the position of an end-effector. Previously, we showed that users were able to accurately and precisely perform a virtual target acquisition task using sonomyography. In this work, we investigate the time course of the control trajectories derived from sonomyography. We show that the time course of the sonomyography-derived trajectories that users take to reach virtual targets reflect the trajectories shown to be typical for kinematic characteristics observed in biological limbs. Specifically, during a target acquisition task, the velocity profiles followed a minimum jerk trajectory shown for point-to-point arm reaching movements, with similar time to target. In addition, the trajectories based on ultrasound imaging result in a systematic delay and scaling of peak movement velocity as the movement distance increased. We believe this is the first evaluation of similarities in control policies in coordinated movements in jointed limbs, and those based on position control signals extracted at the individual muscle level. These results have strong implications for the future development of control paradigms for assistive technologies.
more » « less- Award ID(s):
- 1922598
- NSF-PAR ID:
- 10441326
- Publisher / Repository:
- Nature Publishing Group
- Date Published:
- Journal Name:
- Scientific Reports
- Volume:
- 13
- Issue:
- 1
- ISSN:
- 2045-2322
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract proprioceptive sonomyographic control . 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 evaluatedproprioceptive 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 thatproprioceptive sonomyographic control is a robust and intuitive prosthetic control strategy. -
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