TY - JOUR
T1 - Design of a Multi-Parameter Fusion Sensor and System for Respiratory Monitoring of Mechanically Ventilated Patients in the ICU
AU - Ren, Shuai
AU - Wang, Xiaohan
AU - Cai, Maolin
AU - Shi, Yan
AU - Wang, Tao
AU - Luo, Zujin
N1 - Publisher Copyright:
© 2013 IEEE.
PY - 2024
Y1 - 2024
N2 - In order to achieve precise respiratory therapy for mechanically ventilated patients, real-time monitoring of the state parameters of inhaled and exhaled gases is required. These parameters are primarily measured by ventilators, with limitations such as insufficient monitoring parameters, circuit leaks, and constraints imposed by distance and obstacles. This paper designs a low-power wireless sensor for multi-parameter monitoring near the patient, which can be used continuously for approximately 60 days. Based on this sensor, an intelligent respiratory monitoring system with a distributed architecture is proposed to achieve intelligent patient-ventilator asynchrony (PVA) perception. Experimental results show that the system can stably and accurately collect and transmit data, with measurement errors for pressure, flow, temperature, humidity, and CO2 concentration being pm1.3%, pm2.1%, pm 0.6° C, pm1% RH, pm0.3 mmHg respectively. The proposed sensor and system have the potential to enhance the efficiency and intelligence of medical care significantly.
AB - In order to achieve precise respiratory therapy for mechanically ventilated patients, real-time monitoring of the state parameters of inhaled and exhaled gases is required. These parameters are primarily measured by ventilators, with limitations such as insufficient monitoring parameters, circuit leaks, and constraints imposed by distance and obstacles. This paper designs a low-power wireless sensor for multi-parameter monitoring near the patient, which can be used continuously for approximately 60 days. Based on this sensor, an intelligent respiratory monitoring system with a distributed architecture is proposed to achieve intelligent patient-ventilator asynchrony (PVA) perception. Experimental results show that the system can stably and accurately collect and transmit data, with measurement errors for pressure, flow, temperature, humidity, and CO2 concentration being pm1.3%, pm2.1%, pm 0.6° C, pm1% RH, pm0.3 mmHg respectively. The proposed sensor and system have the potential to enhance the efficiency and intelligence of medical care significantly.
KW - Mechanical Ventilation
KW - Multi-Parameter
KW - Remote Monitoring
KW - Respiratory Monitoring
KW - Wireless
UR - http://www.scopus.com/inward/record.url?scp=85205690061&partnerID=8YFLogxK
U2 - 10.1109/JBHI.2024.3471822
DO - 10.1109/JBHI.2024.3471822
M3 - Article
C2 - 39352825
AN - SCOPUS:85205690061
SN - 2168-2194
JO - IEEE Journal of Biomedical and Health Informatics
JF - IEEE Journal of Biomedical and Health Informatics
ER -