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

Abstract

In medical emergency scenarios, conventional single-parameter monitoring cannot fully assess patient conditions, and current technologies lack intelligent emergency-state recognition, which delays timely treatment. To overcome these challenges, this study develops a high-performance flexible thermoelectric textile-based wearable system that generates a 139.7 mV open-circuit voltage at ΔT = 30 K. To prevent skin-thermoelectric contact from distorting sensor readings, a Kirigami spacer is integrated to ensure proper air gaps while maintaining flexibility and breathability. By integrating optical cardiac sensing, the system establishes a thermoelectric-optical system for wireless real-time cooperative monitoring of both respiration and cardiac activity. The research systematically investigates the effects of airflow velocity on thermoelectric output, leading to the development of an innovative dynamic airflow-thermoelectric response theory. This theory enables speech recognition through airflow variations with 98% accuracy. Additionally, the study creates a multi-source fusion recognition model that combines respiratory patterns, speech-airflow, and cardiac signals to identify emergency states with 98% accuracy. These advances supplement the theoretical understanding of thermoelectric responses to physiological activities while providing decision support for emergency conditions, demonstrating considerable potential for clinical application.