Journal article
Haptic shared control improves neural efficiency during myoelectric prosthesis use
Scientific reports, v 13(1), p484
10 Jan 2023
PMID: 36627340
Abstract
Clinical myoelectric prostheses lack the sensory feedback and sufficient dexterity required to complete activities of daily living efficiently and accurately. Providing haptic feedback of relevant environmental cues to the user or imbuing the prosthesis with autonomous control authority have been separately shown to improve prosthesis utility. Few studies, however, have investigated the effect of combining these two approaches in a shared control paradigm, and none have evaluated such an approach from the perspective of neural efficiency (the relationship between task performance and mental effort measured directly from the brain). In this work, we analyzed the neural efficiency of 30 non-amputee participants in a grasp-and-lift task of a brittle object. Here, a myoelectric prosthesis featuring vibrotactile feedback of grip force and autonomous control of grasping was compared with a standard myoelectric prosthesis with and without vibrotactile feedback. As a measure of mental effort, we captured the prefrontal cortex activity changes using functional near infrared spectroscopy during the experiment. It was expected that the prosthesis with haptic shared control would improve both task performance and mental effort compared to the standard prosthesis. Results showed that only the haptic shared control system enabled users to achieve high neural efficiency, and that vibrotactile feedback was important for grasping with the appropriate grip force. These results indicate that the haptic shared control system synergistically combines the benefits of haptic feedback and autonomous controllers, and is well-poised to inform such hybrid advancements in myoelectric prosthesis technology.
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Details
- Title
- Haptic shared control improves neural efficiency during myoelectric prosthesis use
- Creators
- Neha Thomas - Johns Hopkins UniversityAlexandra J Miller - Johns Hopkins UniversityHasan Ayaz - Drexel UniversityJeremy D Brown - Johns Hopkins University
- Publication Details
- Scientific reports, v 13(1), p484
- Publisher
- Springer Nature
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Drexel Solutions Institute; College of Arts and Sciences; School of Biomedical Engineering, Science, and Health Systems
- Web of Science ID
- WOS:001003345000008
- Scopus ID
- 2-s2.0-85146103275
- Other Identifier
- 991019641907404721
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Neurosciences