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Robotic prostheses and powered exoskeletons are novel assistive robotic devices for modern medicine. Muscle activity sensing plays an important role in controlling assistive robotics devices. Most devices measure the surface electromyography (sEMG) signal for myoelectric control. However, sEMG is an integrated signal from muscle activities. It is difficult to sense muscle movements in specific small regions, particularly at different depths. Alternatively, traditional ultrasound imaging has recently been proposed to monitor muscle activity due to its ability to directly visualize superficial and at-depth muscles. Despite their advantages, traditional ultrasound probes lack wearability. In this paper, a wearable ultrasound (US) transducer, based on lead zirconate titanate (PZT) and a polyimide substrate, was developed for a muscle activity sensing demonstration. The fabricated PZT-5A elements were arranged into a 4 × 4 array and then packaged in polydimethylsiloxane (PDMS). In vitro porcine tissue experiments were carried out by generating the muscle activities artificially, and the muscle movements were detected by the proposed wearable US transducer via muscle movement imaging. Experimental results showed that all 16 elements had very similar acoustic behaviors: the averaged central frequency, −6 dB bandwidth, and electrical impedance in water were 10.59 MHz, 37.69%, and 78.41 Ω, respectively. The in vitro study successfully demonstrated the capability of monitoring local muscle activity using the prototyped wearable transducer. The findings indicate that ultrasonic sensing may be an alternative to standardize myoelectric control for assistive robotics applications.
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Using principles of motor control to analyze performance of human machine interfaces
Abstract 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.
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- Award ID(s):
- 1922598
- 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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