Machine learning approach for foot-side classification using a single wearable sensor

Jungyeon Choi, Jong Hoon Youn, Christian Haas

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

Abstract

Gait analysis is a common technique used to identify problems related to movement and posture in people with injuries, and foot-side detection is one of its important challenges. As many commercial sensors only provide limited information and traditional lab-based gait analysis is expensive, the aim of this study is to discriminate between left and right foot steps based on acceleration data from a single chest-worn accelerometer. To achieve this goal, an experimental study was conducted with 25 participants wearing an accelerometer on their chest and walking in a static environment. Several machine learning (ML) classifiers were trained to detect a foot-side from collected acceleration data. All machine learning classifiers achieved high classification accuracy, with Random Forest providing the best results. This result shows that ML-based foot-side classification using a single sensor is achievable and can contribute to develop an efficient health monitoring system to track lower limb's problems.

Original languageEnglish (US)
Title of host publication40th International Conference on Information Systems, ICIS 2019
PublisherAssociation for Information Systems
ISBN (Electronic)9780996683197
StatePublished - 2020
Event40th International Conference on Information Systems, ICIS 2019 - Munich, Germany
Duration: Dec 15 2019Dec 18 2019

Publication series

Name40th International Conference on Information Systems, ICIS 2019

Conference

Conference40th International Conference on Information Systems, ICIS 2019
CountryGermany
CityMunich
Period12/15/1912/18/19

Keywords

  • Foot-side classification
  • Gait analysis
  • Machine learning
  • Wearable sensor

ASJC Scopus subject areas

  • Computer Science Applications
  • Information Systems

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  • Cite this

    Choi, J., Youn, J. H., & Haas, C. (2020). Machine learning approach for foot-side classification using a single wearable sensor. In 40th International Conference on Information Systems, ICIS 2019 (40th International Conference on Information Systems, ICIS 2019). Association for Information Systems.