Sensors · 2020 · 27 citations · 63 references
NursingHealth SciencesHealth AssessmentHealth Data AnalyticsMobile Health InformaticsCardiovascular MonitoringElectrocardiographyHeart Rate VariabilityMobile Health ApplicationsVital SignsVital Signs RecordingBland-altman PlotHealth MonitoringHeart Rate MonitoringPhotoplethysmogram Signal ProcessingPhotoplethysmographyPhysiological Signal ProcessingSignal Quality AssessmentSmartphone-based Diagnostics
Heart rate variability (HRV) provides essential health information such as the risks of heart attacks and mental disorders. However, inconvenience related to the accurate detection of HRV limits its potential applications. The ubiquitous use of smartphones makes them an excellent choice for regular and portable health monitoring. Following this trend, smartphone photoplethysmography (PPG) has recently garnered prominence; however, the lack of robustness has prevented both researchers and practitioners from embracing this technology. This study aimed to bridge the gap in the literature by developing a novel smartphone PPG quality index (SPQI) that can filter corrupted data. A total of 226 participants joined the study, and results from 1343 samples were used to validate the proposed sinusoidal function-based model. In both the correlation coefficient and Bland-Altman analyses, the agreement between HRV measurements generated by both the smartphone PPG and the reference electrocardiogram improved when data were filtered through the SPQI. Our results support not only the proposed approach but also the general value of using smartphone PPG in HRV analysis.
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Cuiyan Wang, Xiaoyang Wan, Yilin Tan et al. · International Journal of Environmental Research and Public Health · 2020 · 10.3K citations · Full text
Julian F. Thayer, Anita L. Hansen, Evelyn Saus-Rose et al. · Annals of Behavioral Medicine · 2009 · 1.8K citations · Full text