A Fast-Response Breathing Monitoring System for Human Respiration Disease Detection
Xiaoyi Wang, Zongqin Ke, Guanglan Liao, Xiaofang Pan, Yatao Yang, Wei Xu
Abstract
This paper presents a sensing system for the real-time monitoring of human respiration. The system is equipped with a fast response thermoresistive micro calorimetric flow (TMCF) sensor and a dedicated data processing algorithm. The TMCF sensor is designed with a proposed nonlinear sensor model and fabricated in a CMOS compatible process, which obtains a high sensitivity of 114 mV/SLM and a fast response time of less than 6 ms. By using this high-performance micro flow sensor and its proprietary data processing algorithm, critical human respiration information including respiratory rate (RR) and minute ventilation (MV) can be easily obtained. The proposed sensing system achieves a very small mean absolute error (MAE) of less than 2.7 mHz for RR, and the extracted MV is also in good agreement with the commonly reported value of 4 - 6 L/min. In addition, benefiting from the very short time constant of the developed TMCF sensor, the proposed sensing system can successfully distinguish different respiratory diseases, such as apnea, hypopnea, polypnea, etc. Therefore, this proposed human respiration monitoring system will be a promising sensing technology for respiration diagnosis in medical applications.