Ballistocardiogram (BCG)-Based Senior Life Log Monitoring System

Overview

As society rapidly ages, the demand for senior care services is growing. Traditional approaches to elderly health management systems primarily focus on physical health, offering limited support for emotional and psychological well-being. In addition, wearable health devices are often uncomfortable, leading to low user adherence among seniors.

To address these challenges, Clomental was developed — a non-contact biosignal monitoring system that continuously tracks seniors’ physiological status and enables immediate emergency response when abnormalities are detected.

Project description

The system collects and analyzes seniors’ biosignal data in real time, offering personalized health management and emergency response functions.

• Non-contact Ballistocardiogram (BCG) Sensor-based Vital Sign Monitoring
  • Clomental monitors seniors’ health status by capturing ballistocardiogram data without physical contact. It analyzes indicators such as heart rate variability (HRV) and respiratory patterns to detect potential health issues and provides personalized care recommendations.
• AI-Based Biosignal Analysis and Health Prediction
  • By applying AI algorithms to the collected data, the system identifies health risk factors, supporting early detection of abnormalities and enabling prompt response.
• Emergency Detection and Automatic Notification
  • Upon detecting abnormal signals, the system automatically alerts caregivers and welfare agencies. If necessary, it connects to emergency services, ensuring the safety of elderly individuals living alone or in high-risk conditions.
• Integration with Public Data and Welfare Systems
  • Through collaboration with the Gyeongsangnam-do Public Agency for Social Service, the system integrates health and welfare data to provide personalized welfare services.

Key technological features

• Non-contact Heartbeat detection based on Ballistocardiogram (BCG): Analyzes health conditions by non-contact measurement of biochemical gradient.
• AI-Based Biosignal Analysis Algorithm: Predicts health risks by analyzing heart rate variability (HRV) and breathing patterns.
• Emergency Detection and Automatic Notification System: Enables immediate connection to emergency services through real-time health monitoring
• Integration with Public Data and Welfare Service: Operates in conjunction with regional health and welfare data for comprehensive senior care.

Before (as-is)
A single caregiver struggles to monitor multiple seniors indoors, respond to emergencies in real time, and provide emotional care simultaneously.

After (to-be)
Enables highly accurate real-time response even from outside facilities; offers better practicality and responsiveness compared to AI speakers or other passive devices.

Expected outcomes

The project enhances the overall level of elderly health management and emergency response capacity.

Additionally, by leveraging public data to deliver personalized care services, the project improves welfare service efficiency and contributes to the creation of a safe, data-driven senior care ecosystem.

Launch year: 2024

Attribution

Case study courtesy of the National Information Society Agency, Republic of Korea, Apolitical's Content Partner. Sourced from Use Cases of Public AI Service, Vol.1,  https://eng.nia.or.kr/site/nia_eng/ex/bbs/View.do?cbIdx=31975&bcIdx=28997&parentSeq=29000