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Nonintrusive Fine-Grained Home Care Monitoring: Characterizing Quality of In-Home Postural Changes Using Bone-Based

Sinan Chen1, Sachio Saiki1, Masahide Nakamura1,2

  • 1Graduate School of System Informatics, Kobe University, 1-1 Rokkodai-cho, Nada, Kobe 657-8501, Japan.

Sensors (Basel, Switzerland)
|October 21, 2020
PubMed
Summary
This summary is machine-generated.

This study introduces a noninvasive home monitoring system using cameras and bone-based sensing to track postural changes in individuals needing special care. The system offers sustainable, fine-grained insights into daily living habits and care timings for improved health management.

Keywords:
body movementhome care monitoringhuman sensingphysical activitypose conversionpose estimationpositional changespostural changes

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Area of Science:

  • Biomedical Engineering
  • Gerontology
  • Computer Science

Background:

  • Individuals requiring long-term care exhibit low-intensity physical activities and postural changes.
  • Existing wearable devices for monitoring physical activity increase the burden on patients.

Purpose of the Study:

  • To develop a noninvasive, sustainable, fine-grained home care monitoring system for individuals needing special care.
  • To characterize the quality of in-home postural changes using novel sensing technologies.

Main Methods:

  • Integration of inexpensive camera devices and bone-based human sensing.
  • Local processing of feature data acquisition (once per second) on Raspberry Pi.
  • Utilizing pose estimation models to analyze bounding box changes for pose conversion, body movement, and positional changes.
  • Distributed processing across multiple servers for web-based home monitoring.

Main Results:

  • The system successfully characterized in-home postural changes.
  • Experimental results provided insights into daily living habits and care timing irregularities.
  • The proposed method offers a sustainable alternative to burdensome wearable devices.

Conclusions:

  • The developed system provides a noninvasive and sustainable solution for monitoring individuals requiring special care.
  • Fine-grained analysis of postural changes can inform improvements in daily living habits and care routines.
  • This approach enables effective remote home monitoring as a web service.