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Methodology for Establishing a Community-Wide Life Laboratory for Capturing Unobtrusive and Continuous Remote Activity and Health Data
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Development of an IoT-Based Monitoring System for Healthcare: A Preliminary Study.

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  • 1NEWCAT Research Institute, Department of Electrical and Electronic Engineering, College of Engineering, Koriyama, Japan.

Advances in Experimental Medicine and Biology
|January 2, 2020
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Summary

This study introduces an IoT healthcare system for long-term monitoring of vital signs and brain activity. Results show individuals can self-monitor physiological data, including prefrontal cortex activity, in non-medical settings like gyms.

Keywords:
Big dataHealth careIoTNear infrared spectroscopyPrevention medicine

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Area of Science:

  • Biomedical Engineering
  • Health Informatics
  • Neuroscience

Background:

  • Continuous monitoring of physiological parameters is crucial for proactive healthcare.
  • Existing systems often require clinical settings, limiting accessibility.
  • Assessing brain function, such as prefrontal cortex (PFC) activity, can indicate mental stress levels.

Purpose of the Study:

  • To develop and evaluate an Internet of Things (IoT)-based system for long-term, self-administered monitoring of key physiological indicators.
  • To assess the feasibility of using such a system in a non-medical environment, specifically a fitness gym.
  • To investigate the relationship between physiological data and prefrontal cortex (PFC) activity, including its asymmetry, as a measure of mental stress.

Main Methods:

  • An IoT system was implemented for simultaneous measurement of blood pressure (BP), heart rate (HR), body weight (BW), and near-infrared spectroscopy (NIRS) data.
  • A preliminary study involved 39 gym members who were trained to operate the system for self-measurement.
  • Data on BP, HR, BW, and PFC activity (using laterality index at rest - LIR) were collected over six months.

Main Results:

  • Participants successfully self-measured their physiological data after initial instruction.
  • The system demonstrated applicability for continuous monitoring of physiological functions, including brain activity, in a gym setting.
  • Analysis of NIRS data provided insights into left-right asymmetry of PFC activity, correlating with mental stress.

Conclusions:

  • An IoT-based healthcare monitoring system is viable for long-term, self-managed data collection outside clinical environments.
  • This technology empowers individuals to continuously track vital signs and brain function, promoting health awareness.
  • The findings support the integration of accessible health monitoring technologies in everyday community spaces like fitness centers.