Lower limb Movements' Classifications using Hemodynamic Response:fNIRS Study

Maged S. Al-Quraishi, Irraivan Elamvazuthi, Tong Boon Tang, Muhammed Al-Qurishi, S. Parasuraman, Alberto Borboni

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

Abstract

Functional near-infrared spectroscopy (fNIRS) has become a viable approach for brain function investigation and is an interesting modality for brain-machine interfaces (BMIs) due to its portability and resistance to electromagnetic noise. In this work, a hemodynamic response based on fNIRS signals was utilized to classify the right and left ankle joint movements. To achieve this objective, 32 optodes (emitters and detectors) were used to measure the hemodynamic responses in the motor cortex area during the motor execution task of the ankle joint movements. Two-channel sets were formed one including the channels directly related to the movement task, and another including all of the proposed channels. The results of this study reveal that the scheme based only on the selected channels outperformed the scheme that uses all channels. The classification accuracies were 91.38 % and 89.86 % respectively. These results demonstrated that fNIRS signal classification can be enhanced by eliminating the redundant channels.

Original languageEnglish
Title of host publicationProceedings - 2020 IEEE EMBS Conference on Biomedical Engineering and Sciences, IECBES 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages76-81
Number of pages6
ISBN (Electronic)9781728142456
DOIs
StatePublished - 1 Mar 2021
Externally publishedYes

Publication series

NameProceedings - 2020 IEEE EMBS Conference on Biomedical Engineering and Sciences, IECBES 2020

Bibliographical note

Publisher Copyright:
© 2021 IEEE.

Keywords

  • BMI
  • classification
  • fNIRS
  • hemodynamic response
  • movements

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Instrumentation

Fingerprint

Dive into the research topics of 'Lower limb Movements' Classifications using Hemodynamic Response:fNIRS Study'. Together they form a unique fingerprint.

Cite this