Pressure sensor array and camera-based activity level monitoring at home: A feasibility study

Anil Kumar Appukuttan Nair Syamala Amma, Longfei Chen, Robert B. Fisher, Srinjoy Mitra

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

Abstract / Description of output

Detecting ‘lack of movement’ is an important capability for supporting ageing adults who are trying to live independently. This paper introduces a novel system for monitoring inactivity at home by combining a pressure sensor array embedded in a cushion along with an RGBD camera. This approach aims to improve the reliability of the detection of human activity, addressing limitations that arise when solely relying on camera-based monitoring. The practicality of the system was evaluated through a series of experiments where participants engaged in various activities, including movements and prolonged stillness. The feasibility study results indicate that the pressure sensor array can accurately detect small movements that may go unnoticed by the camera alone. This integrated setup offers a reliable solution for comprehensive activity monitoring in home environments.
Original languageEnglish
Title of host publicationProceedings of the 17th International Conference on Sensing Technology
PublisherInstitute of Electrical and Electronics Engineers
Pages1-6
Number of pages6
Publication statusAccepted/In press - 12 Aug 2024
EventThe 17th International Conference on Sensing Technology - Macquarie University, Sydney, Australia
Duration: 9 Dec 202411 Dec 2024
Conference number: 17
https://icst.in/icst2024/

Publication series

NameProceedings of the International Conference on Sensing Technology
PublisherInstitute of Electrical and Electronics Engineers
ISSN (Print)2156-8065
ISSN (Electronic)2156-8073

Conference

ConferenceThe 17th International Conference on Sensing Technology
Abbreviated titleICST 2024
Country/TerritoryAustralia
CitySydney
Period9/12/2411/12/24
Internet address

Keywords / Materials (for Non-textual outputs)

  • inactivity monitoring
  • older adults
  • computer vision
  • pressure sensor

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