Static and dynamic proprioceptive recognition through vibrotactile stimulation

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

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

Objective. Proprioceptive information provides individuals with a sense of our limb's static position and dynamic movement. Impaired or a lack of such feedback can diminish our ability to perform dexterous motions with our biological limbs or assistive devices. Here we seek to determine whether both static and dynamic components of proprioception can be recognized using variation of the spatial and temporal components of vibrotactile feedback. Approach. An array of five vibrotactors was placed on the forearm of each subject. Each tactor was encoded to represent one of the five forearm postures. Vibratory stimulus was elicited to convey the static position and movement of the forearm. Four experimental blocks were performed to test each subject's recognition of a forearm's simulated static position, rotational amplitude, rotational amplitude and direction, and rotational speed. Main results. Our results showed that the subjects were able to perform proprioceptive recognition based on the delivered vibrotactile information. Specifically, rotational amplitude recognition resulted in the highest level of accuracy (99.0%), while the recognition accuracy of the static position and the rotational amplitude-direction was the lowest (91.7% and 90.8%, respectively). Nevertheless, all proprioceptive properties were perceived with >90% accuracy, indicating that the implemented vibrotactile encoding scheme could effectively provide proprioceptive information to the users. Significance. The outcomes suggest that information pertaining to static and dynamic aspects of proprioception can be accurately delivered using an array of vibrotactors. This feedback approach could be used to potentially evaluate the sensorimotor integration processes during human-machine interactions, and to improve sensory feedback in clinical populations with somatosensory impairments.

Original languageEnglish (US)
Article number046093
JournalJournal of neural engineering
Volume18
Issue number4
DOIs
StatePublished - Aug 2021

All Science Journal Classification (ASJC) codes

  • Biomedical Engineering
  • Cellular and Molecular Neuroscience

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