Personalized USB Biosensor Module for Effective ECG Monitoring

Area of Science:

• Biomedical Engineering
• Health Informatics
• Wearable Technology

Background:

• Chronic diseases pose significant financial and disability burdens on healthcare systems.
• There is a growing need for cost-effective, personalized home health solutions for early diagnosis and prevention.
• Existing monitoring systems can be complex and require specialized user knowledge.

Purpose of the Study:

• To develop an easy-to-use, personalized Electrocardiogram (ECG) monitoring system for home health applications.
• To create a cost-effective solution for continuous monitoring of chronic diseases, physical activity, and rehabilitation.
• To simplify the process of data acquisition and analysis for patients and healthcare providers.

Main Methods:

• A biosensor dongle with sensing probes and a micro USB interface was developed for unobtrusive data collection.
• A smartphone application was designed for real-time data reading, system power supply, and user interaction.
• Plug-and-play functionality was implemented to eliminate the need for driver installations, simplifying system usage.
• Configurable sensor combinations allow for tailored monitoring based on individual patient needs.

Main Results:

• The system provides reliable and unobtrusive sensing, preprocessing, and storage of ECG data.
• The smartphone integration offers an intuitive user interface for real-time data visualization.
• Simplified plug-and-play functionality ensures ease of use for a broad patient population.
• The system's adaptability through sensor combinations supports diverse monitoring requirements.

Conclusions:

• The developed ECG monitoring system offers a user-friendly and cost-effective approach to personalized home healthcare.
• It effectively addresses the need for continuous monitoring in chronic disease management, physical activity tracking, and rehabilitation.
• This technology has the potential to improve patient outcomes and reduce healthcare system costs through early detection and prevention.