Wearable Flexible Sensors for Cardiovascular Disease Monitoring

Area of Science:

• Bioelectronics and Biomedical Engineering
• Materials Science and Engineering
• Cardiovascular Medicine

Background:

• Wearable flexible sensors are crucial for next-generation bioelectronics.
• They enable continuous, high-fidelity monitoring of cardiovascular diseases (CVDs).
• Current platforms require advancements in performance and clinical translation.

Purpose of the Study:

• To review structure-function relationships in wearable cardiovascular sensors.
• To correlate physiological signals with sensing mechanisms.
• To propose a unified design paradigm for intelligent CVD monitoring.

Main Methods:

• Systematic review of material innovation, structure engineering, and device architectures.
• Correlation of cardiovascular signals (electrical, mechanical, hemodynamic, biochemical) with transduction mechanisms (piezoresistive, capacitive, triboelectric, electrochemical, optical).
• Discussion of machine learning integration for diagnostics and prediction.

Main Results:

• Structure-function relationships dictate sensor performance (sensitivity, robustness, biocompatibility).
• Diverse sensing mechanisms effectively capture various physiological signals.
• Machine learning enhances personalized diagnostics and risk prediction.

Conclusions:

• A unified design paradigm integrating materials, multimodal sensing, and AI is proposed.
• Addressing challenges in stability, manufacturing, and validation is critical.
• Development of interpretable and clinically translatable wearable platforms is essential for precision CVD monitoring.