A wearable smartphone-based platform for real-time cardiovascular disease detection via electrocardiogram processing

Area of Science:

• Biomedical Engineering
• Cardiology
• Digital Health

Background:

• Cardiovascular disease (CVD) remains the leading global cause of mortality.
• Cardiac arrhythmia is a common CVD type, increasing stroke and sudden cardiac death risk.
• Standard resting ECGs and portable Holter monitors have limitations in real-time arrhythmia detection and analysis.

Purpose of the Study:

• To develop smartphone-based wearable platforms for real-time ECG acquisition and analysis.
• To combine the portability of Holter monitors with the real-time processing of resting ECG machines.
• To provide an assistive diagnosis solution for cardiovascular arrhythmias using smartphones.

Main Methods:

• Development of two smartphone-based wearable platforms for ECG acquisition.
• Implementation of real-time feature extraction and beat classification algorithms.
• Integration of statistical summaries comparable to resting ECG machines.

Main Results:

• Successful development of functional smartphone-based wearable CVD-detection platforms.
• Demonstrated capability for real-time ECG acquisition, display, and analysis.
• Provided statistical summaries for arrhythmia risk assessment.

Conclusions:

• Smartphone-based wearable platforms offer a promising solution for real-time arrhythmia detection.
• These devices can enhance CVD diagnosis by providing continuous monitoring and immediate feedback.
• The technology integrates portability and advanced real-time processing for improved cardiac care.