First Demonstration of Functional Task Performance Using a Sonomyographic Prosthesis: A Case Study

Engdahl, Susannah M.; King, Erica L.; Bashatah, Ahmed; Sikdar, Siddhartha

doi:10.3389/fbioe.2022.876836

Cited by 17 publications

(15 citation statements)

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“…Our results demonstrate that it is possible to achieve naturalistic control using control signals derived from muscle. Sonomyography is an emerging modality that is being used for controlling upper and lower limb prosthetic devices 94 , but can also be used to control biomechatronic devices such as exoskeletons 95 – 97 and prosthetic hands 18 , 54 , 93 .The results presented in this work have direct relevance to designing control strategies for such devices, that reflect the natural movements of the human body. Surface electromyography has been the predominant method of decoding motor intent in persons with movement disabilities using electrical signals from the surface of the skin 26 .…”

Section: Discussionmentioning

confidence: 87%

Using principles of motor control to analyze performance of human machine interfaces

Patwardhan

Gladhill

Joiner

et al. 2023

Sci Rep

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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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Section: Discussionmentioning

confidence: 87%

Using principles of motor control to analyze performance of human machine interfaces

Patwardhan

Gladhill

Joiner

et al. 2023

Sci Rep

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“…However, robust acquisition of the control in-formation is still achievable if the variability of any transducer movement is accounted for during signal derivation. 35…”

Section: Angle and Orientationmentioning

confidence: 99%

Sonomyography for Control of Upper-Limb Prostheses: Current State and Future Directions

Engdahl,

Acuña,

Kaliki

et al. 2024

J Prosthet Orthot

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Problem Statement Despite the recent advancements in technology, many individuals with upper-limb loss struggle to achieve stable control over multiple degrees of freedom in a prosthesis. There is an ongoing need to develop noninvasive prosthesis control modalities that could improve functional patient outcomes. Proposed Solution Ultrasound-based sensing of muscle deformation, known as sonomyography, is an emerging sensing modality for upper-limb prosthesis control with the potential to significantly improve functionality. Sonomyography enables spatiotemporal characterization of both superficial and deep muscle activity, making it possible to distinguish the contributions of individual muscles during functional movements and derive a large set of independent prosthesis control signals. Using sonomyography to control a prosthesis has shown great promise in the research literature but has not yet been fully adapted for clinical use. This article describes the implementation of sonomyography for upper-limb prosthesis control, ongoing technological development, considerations for deploying this technology in clinical settings, and recommendations for future study. Clinical Relevance Sonomyography may soon become a clinically viable modality for upper-limb prosthesis control that could offer prosthetists an additional solution when selecting optimal treatment plans for their patients.

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“…In addition, there have been similar paradigm improvement studies for other biosignal-driven prosthetic hands that have reference value for myoelectric training paradigms. Susannah et al [ 131 ] explored the effects of different socket loads, arm positions, and motion patterns on training paradigms and verified, for the first time, the feasibility of using sonomyography to control prosthetic hands. Jiarong Wang et al [ 132 ] improved the classic center-out paradigm in the field of EEG signal research, enhancing the training paradigm’s movement prediction performance and generalizability, significantly reducing subjects’ physical exertion.…”

Section: Challenges and Opportunitiesmentioning

confidence: 99%

A Review of Myoelectric Control for Prosthetic Hand Manipulation

et al. 2023

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Myoelectric control for prosthetic hands is an important topic in the field of rehabilitation. Intuitive and intelligent myoelectric control can help amputees to regain upper limb function. However, current research efforts are primarily focused on developing rich myoelectric classifiers and biomimetic control methods, limiting prosthetic hand manipulation to simple grasping and releasing tasks, while rarely exploring complex daily tasks. In this article, we conduct a systematic review of recent achievements in two areas, namely, intention recognition research and control strategy research. Specifically, we focus on advanced methods for motion intention types, discrete motion classification, continuous motion estimation, unidirectional control, feedback control, and shared control. In addition, based on the above review, we analyze the challenges and opportunities for research directions of functionality-augmented prosthetic hands and user burden reduction, which can help overcome the limitations of current myoelectric control research and provide development prospects for future research.

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First Demonstration of Functional Task Performance Using a Sonomyographic Prosthesis: A Case Study

Cited by 17 publications

References 50 publications

Using principles of motor control to analyze performance of human machine interfaces

Using principles of motor control to analyze performance of human machine interfaces

Sonomyography for Control of Upper-Limb Prostheses: Current State and Future Directions

A Review of Myoelectric Control for Prosthetic Hand Manipulation

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