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Development of Wearable Device and Clustering Based Method for Detecting Falls in the Elderly

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

Abstract

This work presents a wearable inertial sensor-based system for detecting falls in the elderly. The system is fixed on the elderly's head to obtain stable human body acceleration. To detect a variety of falls, a K-means model based on abundant daily activity data is constructed, and then the fall samples are detected by comparing the similarity with the other non-fall samples. The system requires no fall samples for training, and achieves an accuracy of 96.8%.

Original languageEnglish
Title of host publication2021 IEEE 10th Global Conference on Consumer Electronics, GCCE 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages231-232
Number of pages2
ISBN (Electronic)9781665436762
DOIs
Publication statusPublished - 2021
Event10th IEEE Global Conference on Consumer Electronics, GCCE 2021 - Kyoto, Japan
Duration: 2021 Oct 122021 Oct 15

Publication series

Name2021 IEEE 10th Global Conference on Consumer Electronics, GCCE 2021

Conference

Conference10th IEEE Global Conference on Consumer Electronics, GCCE 2021
Country/TerritoryJapan
CityKyoto
Period21-10-1221-10-15

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Signal Processing
  • Biomedical Engineering
  • Electrical and Electronic Engineering
  • Media Technology
  • Instrumentation

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