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

Po Ting Lee, Wen Ching Chiu, Yuan Hao Ho, You Cheng Tai, Chou Ching K. Lin, Chih Lung Lin

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

5 Citations (Scopus)

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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