Motion Scale: A Body Motion Monitoring System Using Bed-Mounted Wireless Load Cells

Musaab Alaziz, Zhenhua Jia, Jian Liu, Richard Howard, Yingying Chen, Yanyong Zhang

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

24 Scopus citations

Abstract

In-bed motion detection is an important techniquethat can enable an array of applications, among which aresleep monitoring and abnormal movement detection. In thispaper, we present a low-cost, low-overhead, and highly robustsystem for in-bed movement detection and classification thatuses low-end load cells. By observing the forces sensed by theload cells, placed under each bed leg, we can detect manydifferent types of movements, and further classify them as bigor small depending on magnitude of the force changes on theload cells. We have designed three different features, whichwe refer to as Log-Peak, Energy-Peak, ZeroX-Valley, that caneffectively extract body movement signals from load cell datathat are collected through wireless links in an energy-efficientmanner. After establishing the feature values, we employ a simplethreshold-based algorithm to detect and classify movements. Wehave conducted thorough evaluation, that involves collecting datafrom 30 subjects who perform 27 pre-defined movements in anexperiment. By comparing our detection and classification resultsagainst the ground truth captured by a video camera, we showthe Log-Peak strategy can detect these 27 types of movementsat an error rate of 6.3% while classifying them to big or smallmovements at an error rate of 4.2%.

Original languageEnglish (US)
Title of host publicationProceedings - 2016 IEEE 1st International Conference on Connected Health
Subtitle of host publicationApplications, Systems and Engineering Technologies, CHASE 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages183-192
Number of pages10
ISBN (Electronic)9781509009435
DOIs
StatePublished - Aug 16 2016
Event1st IEEE International Conference on Connected Health: Applications, Systems and Engineering Technologies, CHASE 2016 - Washington, United States
Duration: Jun 27 2016Jun 29 2016

Publication series

NameProceedings - 2016 IEEE 1st International Conference on Connected Health: Applications, Systems and Engineering Technologies, CHASE 2016

Other

Other1st IEEE International Conference on Connected Health: Applications, Systems and Engineering Technologies, CHASE 2016
Country/TerritoryUnited States
CityWashington
Period6/27/166/29/16

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Information Systems and Management
  • Biomedical Engineering
  • Computer Networks and Communications
  • Hardware and Architecture

Keywords

  • Bed-Mounted Sensor
  • Signal Processing
  • Sleep Monitoring

Fingerprint

Dive into the research topics of 'Motion Scale: A Body Motion Monitoring System Using Bed-Mounted Wireless Load Cells'. Together they form a unique fingerprint.

Cite this