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.