Evaluation of the Role of Proprioception During Proportional Position Control Using Sonomyography: Applications in Prosthetic Control

Patwardhan, Shriniwas; Dhawan, Ananya; Mukherjee, Biswarup; Alzamani, Meena; Joiner, Wilsaan M.; Sikdar, Siddhartha

doi:10.1109/icorr.2019.8779559

Cited by 9 publications

(5 citation statements)

References 26 publications

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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 96 , but can also be used to control biomechatronic devices such as exoskeletons [97][98][99] and prosthetic hands 18,64,95 .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: Applications In Rehabilitation Engineeringmentioning

confidence: 88%

“…In the current work, users had complete access to visual feedback, and we did not perturb the visual representation of the task in real-time during the task. However, we have tested the effect of removing visual feedback of the cursor on task performance (errors,time to target, etc) 95 . In future work, we plan to test the effect of removing visual feedback on the dynamics of the performance reported here.…”

Section: The Minimum Jerk Trajectory During Human Movementmentioning

confidence: 99%

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Using Principles of Motor Control to Analyze Performance of Human Machine Interfaces

Patwardhan

Gladhill

Joiner

et al. 2023

Preprint

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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 a 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: Applications In Rehabilitation Engineeringmentioning

confidence: 88%

Section: The Minimum Jerk Trajectory During Human Movementmentioning

confidence: 99%

Using Principles of Motor Control to Analyze Performance of Human Machine Interfaces

Patwardhan

Gladhill

Joiner

et al. 2023

Preprint

Self Cite

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“…However, we are also interested in understanding the extent to which we can facilitate an intuitive control paradigm that mimics the natural control employed with intact limbs. Our previous work has shown that SMG may eventually enable proportional positional control of prostheses [32] that allows users to rely on their innate proprioceptive sensing [34] to drive their device in a way that is directly congruent with their level of muscle contraction. Therefore, evaluating whether the classifier can accurately detect partially completed grasps is a necessary step towards demonstrating the feasibility of achieving proportional positional control.…”

Section: Methodsmentioning

confidence: 99%

Motion prediction using electromyography and sonomyography for an individual with transhumeral limb loss

Engdahl

Dhawan

Lévay

et al. 2020

Preprint

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Controlling multi-articulated prosthetic hands with surface electromyography can be challenging for users. Sonomyography, or ultrasound-based sensing of muscle deformation, avoids some of the problems of electromyography and enables classification of multiple motion patterns in individuals with upper limb loss. Because sonomyography has been previously studied only in individuals with transradial limb loss, the purpose of this study was to assess the feasibility of an individual with transhumeral limb loss using this modality for motion classification. A secondary aim was to compare motion classification performance between electromyography and sonomyography. A single individual with transhumeral limb loss created two datasets containing 11 motions each (individual flexion of each finger, thumb abduction, power grasp, key grasp, tripod, point, pinch, wrist pronation). Electromyography or sonomyography signals associated with every motion were acquired and cross-validation accuracy was computed for each dataset. While all motions were usually predicted successfully with both electromyography and sonomyography, the cross-validation accuracies were typically higher for sonomyography. Although this was an exploratory study, the results suggest that controlling an upper limb prosthesis using sonomyography may be feasible for individuals with transhumeral limb loss.

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“…Multiple studies [ 17 , 28 , 29 , 30 ] have been undertaken to cover the role of proprioceptive feedback in the control of upper-limb prostheses. They conclude that proprioceptive sensations could significantly improve the ability to accurately perform tasks with a prosthesis with or without visual feedback.…”

Section: Introductionmentioning

confidence: 99%

Control Methods for Transradial Prostheses Based on Remnant Muscle Activity and Its Relationship with Proprioceptive Feedback

Grushko

Spurný

Černý

2020

Sensors

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The loss of a hand can significantly affect one’s work and social life. For many patients, an artificial limb can improve their mobility and ability to manage everyday activities, as well as provide the means to remain independent. This paper provides an extensive review of available biosensing methods to implement the control system for transradial prostheses based on the measured activity in remnant muscles. Covered techniques include electromyography, magnetomyography, electrical impedance tomography, capacitance sensing, near-infrared spectroscopy, sonomyography, optical myography, force myography, phonomyography, myokinetic control, and modern approaches to cineplasty. The paper also covers combinations of these approaches, which, in many cases, achieve better accuracy while mitigating the weaknesses of individual methods. The work is focused on the practical applicability of the approaches, and analyses present challenges associated with each technique along with their relationship with proprioceptive feedback, which is an important factor for intuitive control over the prosthetic device, especially for high dexterity prosthetic hands.

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Evaluation of the Role of Proprioception During Proportional Position Control Using Sonomyography: Applications in Prosthetic Control

Cited by 9 publications

References 26 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

Motion prediction using electromyography and sonomyography for an individual with transhumeral limb loss

Control Methods for Transradial Prostheses Based on Remnant Muscle Activity and Its Relationship with Proprioceptive Feedback

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