Measuring fatigue through heart rate variability and activity recognition: A scoping literature review of machine learning techniques

Karla Gonzalez, Farzan Sasangohar, Ranjana K. Mehta, Mark Lawley, Madhav Erraguntla

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

17 Scopus citations

Abstract

A scoping literature review was conducted to summarize the current research trends in fatigue identification with applications to human activity recognition through the use of diverse commercially available accelerometers. This paper also provides a brief overview of heart rate variability and its effect on fatigue. The linkage between recognizing an individual's unique physical activities, and its possible feedback to manage fatigue levels were explored. Overall, triangulation of heart rate variability and accelerometer data show promise in identify chronic cognitive and physical fatigue levels.

Original languageEnglish (US)
Title of host publicationProceedings of the Human Factors and Ergonomics Society 2017 International Annual Meeting, HFES 2017
PublisherHuman Factors an Ergonomics Society Inc.
Pages1748-1752
Number of pages5
ISBN (Electronic)9780945289531
DOIs
StatePublished - 2017
EventHuman Factors and Ergonomics Society 2017 International Annual Meeting, HFES 2017 - Austin, United States
Duration: Oct 9 2017Oct 13 2017

Publication series

NameProceedings of the Human Factors and Ergonomics Society
Volume2017-October
ISSN (Print)1071-1813

Other

OtherHuman Factors and Ergonomics Society 2017 International Annual Meeting, HFES 2017
Country/TerritoryUnited States
CityAustin
Period10/9/1710/13/17

ASJC Scopus subject areas

  • Human Factors and Ergonomics

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