Gait analyzer based on a cell phone with a single three-axis accelerometer

Toshiki Iso, Kenichi Yamazaki

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

86 Citations (Scopus)

Abstract

We propose a fuss-free gait analyzer based on a single three-axis accelerometer mounted on a cell phone for health care and presence services. It is not necessary for users not to wear sensors on any part of their bodies; all they need to do is to carry the cell phone. Our algorithm has two main functions; one is to extract feature vectors by analyzing sensor data in detail using wavelet packet decomposition. The other is to flexibly cluster personal gaits by combining a self-organizing algorithm with Bayesian theory. Not only does the three-axis accelerometer realize low cost personal devices, but we can track aging or situation changes through on-line learning. A prototype that implements the algorithm is constructed. Experiments on the prototype show that the algorithm can identify gaits such as walking, running, going up/down stairs, and walking fast with an accuracy of about 80[%].

Original languageEnglish
Title of host publicationMobileHCI 2006 - 8th International Conference on Human-Computer Interaction with Mobile Devices and Services
Pages141-144
Number of pages4
DOIs
Publication statusPublished - 2006
Externally publishedYes
Event8th International Conference on Human-Computer Interaction with Mobile Devices and Services, MobileHCI 2006 - Espoo, Finland
Duration: 2006 Sept 122006 Sept 15

Publication series

NameACM International Conference Proceeding Series
Volume159

Conference

Conference8th International Conference on Human-Computer Interaction with Mobile Devices and Services, MobileHCI 2006
Country/TerritoryFinland
CityEspoo
Period06/9/1206/9/15

Keywords

  • Accelerometer
  • Cell phone
  • Context
  • Gait analysis
  • Self-organizing map
  • Sensor
  • Ubiquitous service
  • Wavelet packet

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications

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