PQR signal quality indexes: A method for real-time photoplethysmogram signal quality estimation based on noise interferences. (January 2019)

• Record Type: Journal Article
• Authors: Song, Jiajia; Li, Dan; Ma, Xiaoyuan; Teng, Guowei; Wei, Jianming
• Is Part Of: Biomedical signal processing and control. Volume 47(2019)
• Page Start: 88
• Page End: 95
• Publication Date: 2019-01
• Subjects: Photoplethysmograph -- Signal quality estimation -- High-frequency noises -- Baseline wandering -- Motion artifacts; Signal processing -- Periodicals; Biomedical engineering -- Periodicals; Signal Processing, Computer-Assisted -- Periodicals; Image Processing, Computer-Assisted -- Periodicals; Biomedical Engineering -- Periodicals; 610.28
• DOI: 10.1016/j.bspc.2018.05.020
• Languages: English
• ISSNs: 1746-8094

Abstract

Abstract: The photoplethysmograph (PPG) acquired from pulse oximeters has been extensively used to estimate the heart rate and blood oxygen saturation. However, how to improve the accuracy of these parameters is always a challenging work as PPG is susceptible to be contaminated by noises especially motion artifacts (MAs). This study presents an algorithm called PQR to calculate three indexes (P/Q/R) for estimation the signal quality based on noise interferences and rSQI index for comparison of any two signals. P/Q/R indicates the influencing degree of high-frequency noise, baseline wandering and motion artifacts on PPG respectively. And a relative signal quality estimation index rSQI is designed to compare the quality of any two signals. When the value of rSQI is greater than zero, it illustrates that the quality of the former signal is better than the latter, and vice versa. Lower P/Q/R scores could be obtained from the algorithm if PPG is contaminated by strong artifacts or with an irregular signal morphology. The algorithm put a complete successive signal into consideration instead of signal segmentation beat by beat. Experiment results using MIMIC (Multi-parameter Intelligent Monitoring for Intensive care) database indicates the availability of PQR algorithm. And the real-time PPG signal quality estimation system could be realized to help estimating heart rate online by applying PQR algorithm to the dataset of IEEE Signal Processing Society. Moreover, the experiments using our lab hardware platform show the corresponding preliminary results of application on the comparison of different signal processing methods. The novel PQR algorithm generates significantly lower rSQI values with the comparison of reference signal when PPG signals are contaminated by strong noise. The chosen threshold could be established once an application has been defined derived from the collected data. The PQR algorithm maybe could help to guide the choice of PPG signal in real-time for the physical information extraction such as heart rate.