Patient-centric on-body sensor localization in smart health systems

Ramyar Saeedi, Navid Amini, Hassan Ghasemzadeh

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

16 Scopus citations

Abstract

A major obstacle in widespread adoption of current wearable monitoring systems is that sensors must be worn on predefined locations on the body. In order to continuously detect sensor locations, we propose a localization algorithm that allows patients to wear the sensors on different body locations without having to adhere to a specific installation protocol. Our approach achieves localization accuracy of 90.8% even when the sensor nodes are mis-oriented. Integration of the resulting location information as a feature in an activity recognition classifier significantly increased the recognition accuracy from 23.5% to 99.5%.

Original languageEnglish (US)
Title of host publicationConference Record of the 48th Asilomar Conference on Signals, Systems and Computers
EditorsMichael B. Matthews
PublisherIEEE Computer Society
Pages2081-2085
Number of pages5
ISBN (Electronic)9781479982974
DOIs
StatePublished - Apr 24 2015
Externally publishedYes
Event48th Asilomar Conference on Signals, Systems and Computers, ACSSC 2015 - Pacific Grove, United States
Duration: Nov 2 2014Nov 5 2014

Publication series

NameConference Record - Asilomar Conference on Signals, Systems and Computers
Volume2015-April
ISSN (Print)1058-6393

Other

Other48th Asilomar Conference on Signals, Systems and Computers, ACSSC 2015
Country/TerritoryUnited States
CityPacific Grove
Period11/2/1411/5/14

ASJC Scopus subject areas

  • Signal Processing
  • Computer Networks and Communications

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