Breath, Pulse, and Speech: A Multi-Parameter Wearable System using Airflow-Thermoelectric Fusion Technology

Area of Science:

• Wearable technology
• Biomedical engineering
• Materials science

Background:

• Conventional single-parameter monitoring is insufficient for medical emergencies.
• Current technologies lack intelligent emergency-state recognition, delaying treatment.
• Need for advanced wearable systems for real-time patient assessment.

Purpose of the Study:

• Develop a flexible thermoelectric textile-based wearable system for emergency monitoring.
• Integrate optical cardiac sensing for comprehensive physiological data.
• Establish intelligent emergency-state recognition using multi-source data fusion.

Main Methods:

• Fabrication of a high-performance flexible thermoelectric textile.
• Integration of a Kirigami spacer for optimal sensor performance.
• Development of a thermoelectric-optical system for wireless monitoring.
• Investigation of dynamic airflow-thermoelectric response theory.
• Creation of a multi-source fusion recognition model.

Main Results:

• Achieved 139.7 mV open-circuit voltage at ΔT = 30 K.
• Speech recognition through airflow variations with 98% accuracy.
• Emergency state identification with 98% accuracy using fused data.
• Demonstrated flexibility, breathability, and reliable sensor readings.

Conclusions:

• The developed system offers intelligent emergency-state recognition.
• Advances theoretical understanding of thermoelectric responses to physiological activities.
• Shows significant potential for clinical applications in emergency medicine.