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Monitoring worker fatigue using wearable devices: A case study to detect changes in gait parameters

  • SUNY Buffalo
  • Miami University
  • Saint Louis University

Research output: Contribution to journalArticlepeer-review

51 Scopus citations

Abstract

The goal of this case study is to answer four research questions related to fatigue through features derived from wearable sensors to measure patterns in steps: (1) How do important gait parameters change over time? (2) How do these sensor-based changes relate to the participant's subjective fatigue ratings over time? (3) Are there consistent patterns in performance across different individuals over time? and (4) Do these patterns vary systematically based on specific demographic characteristics? To answer these questions, we have combined multivariate changepoint methods with hierarchical time-series clustering and exploratory data analysis. The results improve our understanding of fatigue development.

Original languageEnglish
Pages (from-to)47-71
Number of pages25
JournalJournal of Quality Technology
Volume53
Issue number1
DOIs
StatePublished - 2021

Keywords

  • clustering
  • internet of people
  • median filter
  • nonparametric multivariate inference
  • signal processing

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