Comparing different methods of gait speed estimation using wearable sensors in individuals with varying levels of mobility impairments

Erick H. Nunez, Sanjit Parhar, Isao Iwata, Soko Setoguchi, Haoqian Chen, Jean Francois Daneault

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

Abstract

Wearable sensors, such as inertial measurement units (IMU), provide the ability to quantify gait parameters outside of traditional gait laboratory settings. Walking speed has been shown to be associated with morbidity and mortality. Therefore, the ability of a clinician to easily and inexpensively measure gait speed within their clinic or patients' home setting can improve patient management and care. This study highlights multiple methods used to estimate patient walking speeds based only on IMU data and minimal anthropometric data, and identifies the algorithm appearing to be the most robust; one relying on identifying swing phases of gait first.Clinical relevance - Providing a clinician with a simple, inexpensive and reliable protocol for measuring patients' gait speed and other parameters could offer prevention and individualized care.

Original languageEnglish (US)
Title of host publication42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society
Subtitle of host publicationEnabling Innovative Technologies for Global Healthcare, EMBC 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3792-3798
Number of pages7
ISBN (Electronic)9781728119908
DOIs
StatePublished - Jul 2020
Externally publishedYes
Event42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society, EMBC 2020 - Montreal, Canada
Duration: Jul 20 2020Jul 24 2020

Publication series

NameProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Volume2020-July
ISSN (Print)1557-170X

Conference

Conference42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society, EMBC 2020
CountryCanada
CityMontreal
Period7/20/207/24/20

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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