Virtual Module Platform System Development Plan

Subproject Four: Virtual Module Platform System Development Plan

With the rapid advancement of digital healthcare, virtual health platforms are becoming essential tools for improving health management. This project focuses on developing a virtual platform system centered on personal-generated health data (PGHD). By integrating wearable devices and risk prediction models, it aims to provide real-time and precise health management services. The key achievements and applications are as follows:

1. PGHD Transmission Workflow

We have completed initial tests for the PGHD transmission workflow, successfully verifying the technical feasibility of data collection and management. The system imports data from Google Fit and Apple Health, temporarily stores it on AWS, and then integrates it into a backend management system for analysis. Current data sources include wearable devices and smartphones, primarily collecting heart rate, step count, and sleep duration. Due to the limitations of some devices in measuring electrocardiograms (ECG) and blood pressure, these are secondary data collection targets. This workflow establishes a solid foundation for the future expansion of health platforms by ensuring the seamless integration and flow of multi-device, multi-platform data.

2. Health Data Collection Platform

To further enhance data collection efficiency, we have developed a platform capable of automatically processing data from wearable devices. Users can synchronize their data to the platform through Google Fit or Apple Health authorization. Key data collected includes:

• Heart Rate: Real-time monitoring of cardiac health.
• Step Count: Reflecting daily activity levels.
• Sleep Duration: Assessing individual rest quality.

Future developments will expand the collection to additional physiological indicators, such as blood pressure and ECG, to provide more comprehensive health data.

3. Chronic Disease Risk Prediction Model Platform

Building on previously developed chronic disease risk models, we have established a risk prediction platform. Users can input their personal health data to predict their risk of developing diseases within the next five years. The platform currently supports risk assessments for diabetes and chronic obstructive pulmonary disease (COPD):

• Diabetes Risk Platform: Users can understand their likelihood of developing diabetes and receive professional advice, such as dietary adjustments or exercise plans.
• COPD Risk Platform: This feature provides predictions about lung function status, enabling early treatment or health interventions.

These functionalities not only enhance the convenience of individual health management but also support healthcare institutions in delivering more precise disease prevention.

Applications and Future Prospects

The virtual module platform integrates PGHD technologies and risk prediction models, effectively facilitating the integration of health data while offering personalized health management solutions. In the future, we plan to further expand the platform’s features by introducing additional disease models and advanced data analysis technologies. By improving data collection and prediction accuracy, we aim to ensure that every user can enjoy efficient and accessible health services.