Fusion of Induced Variations Using Quality Metrics to Estimate Respiratory Rate from Photoplethysmography Signal

摘要

Among the vital signs of acutely ill hospital patients, Respiratory Rate (RR) is a highly accurate predictor of health deterioration. The most common method for measuring RR in hospitals is transthoracic Impedance Pneumography (IP). The drawback of IP which measures impedance at the electrocardiogram electrodes is the injection of high-frequency alternating current into the tissue through drive electrodes. Thus, IP becomes an active electronic device. The usage of IP may also cause natural breathing disturbance in patients and eventually contributes to discomfort. This study aims to evaluate the RR from passive and noninvasive acquisition module, Photoplethysmogram (PPG) signals. Algorithms comprise signal quality indices. The RR estimation method for extracting three respiratory signal-induced variations of PPG was described. The three respiration rates were combined through a weighted average using quality metrics for each signal. The weights were determined using good quality MIMIC II benchmark datasets. PPG signal and reference breathing signal using nasal air flow sensor of 20 healthy subjects have also been recorded and the RR has been combined. The Mean Square Error (MSE) was 0.86 breath/min compared with the reference RR. The proposed methodology could replace the manual counting method of RR, uncomfortable nasal airflow sensor, chest band and IP which are often used in hospitals. Given its simple setup, the future system can increase the efficiency of the RR monitoring frequency for patients with critical illnesses.