Perception of static position and kinesthesia of the finger using vibratory stimulation

Luis Vargas, He Helen Huang, Yong Zhu, Xiaogang Hu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Proprioception provides information regarding the state of an individual's limb in terms of static position and kinesthesia (dynamic movement). When such feedback is lost or impaired, the performance of dexterous control of our biological limbs or assistive devices tends to deteriorate. In this study, we determined if external vibratory stimulation patterns could allow for the perception of a finger's static position and kinesthesia. Using four tactors and two stimulus levels, eight vibratory settings corresponded to eight discrete finger positions. The transition patterns between these eight settings corresponded to kinesthesia. Three experimental blocks assessed the perception of a finger's static position, speed, and movement (amplitude and direction). Our results demonstrated that both position and kinesthesia could be recognized with over 93% accuracy. The outcomes suggest that vibratory stimulus can inform subjects of static and dynamic aspects of finger proprioception. This sensory stimulation approach can be implemented to improve outcomes in clinical populations with sensory deficits, and to enhance user experience when users interact with assistive devices.

Original languageEnglish (US)
Title of host publication2021 10th International IEEE/EMBS Conference on Neural Engineering, NER 2021
PublisherIEEE Computer Society
Pages1087-1090
Number of pages4
ISBN (Electronic)9781728143378
DOIs
StatePublished - May 4 2021
Event10th International IEEE/EMBS Conference on Neural Engineering, NER 2021 - Virtual, Online, Italy
Duration: May 4 2021May 6 2021

Publication series

NameInternational IEEE/EMBS Conference on Neural Engineering, NER
Volume2021-May
ISSN (Print)1948-3546
ISSN (Electronic)1948-3554

Conference

Conference10th International IEEE/EMBS Conference on Neural Engineering, NER 2021
Country/TerritoryItaly
CityVirtual, Online
Period5/4/215/6/21

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Mechanical Engineering

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