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Blood pressure assessment with in-ear photoplethysmography

Xiaoman Xing, Zhimin Ma, Shengkai Xu, Mingyou Zhang, Wei Zhao, Mingxuan Song, Wen‐Fei Dong

2021Physiological Measurement16 citationsDOI

Abstract

Abstract Objective . In this study, we aimed to estimate blood pressure (BP) from in-ear photoplethysmography (PPG). This novel implementation provided an unobtrusive and steady way of recording PPG, whereas previous PPG measurements were mostly performed at the wrist, finger, or earlobe. Methods . The time between forward and reflected PPG waves was very short at the ear site. To minimize errors introduced by feature extraction, a multi-Gaussian decomposition of in-ear PPG was performed. Both hand-crafted and whole-based features were extracted and the best combination of features was selected using a backward-search wrapper method and evaluated by the Akaike information criteria. Hemodynamic parameters such as compliance and inertance were estimated from a four-element Windkessel (WK4) model, which was used to pre-classify PPG signals and generate different BP estimation algorithms. Calibration was done by using previous measurements from the same class. To validate this novel approach, 53 subjects were recruited for a one-month follow-up study, and 17 subjects were recruited for a two-month follow-up study. Calibrated systolic BP estimation accuracy was significantly improved with inertance-based pre-classification, while diastolic BP showed less improvement. Results . With proper feature selection, pre-classification and calibration, we have achieved a mean absolute error of 5.35 mmHg for SBP estimation, compared to 6.16 mmHg if no pre-classification was carried out. The performance did not deteriorate in two months, showing a decent BP trend-tracking ability. Conclusion . The study demonstrated the feasibility of in-ear PPG to reliably measure BP, which represents an important technological advancement in terms of unobtrusiveness and steadiness.

Topics & Concepts

PhotoplethysmogramEarlobePhonocardiogramInertanceAuscultationPattern recognition (psychology)CalibrationBlood pressureComputer scienceSpeech recognitionArtificial intelligenceMedicineMathematicsCardiologySurgeryInternal medicineComputer visionStatisticsEngineeringTube (container)Mechanical engineeringFilter (signal processing)Non-Invasive Vital Sign MonitoringHeart Rate Variability and Autonomic ControlHemodynamic Monitoring and Therapy
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