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- W4247557897 abstract "<sec> <title>BACKGROUND</title> Wearable and connected health devices along with the recent advances in mobile and cloud computing provide a continuous, convenient-to-patient and scalable way to collect personal health data remotely. The Wavelet Health Platform and the Wavelet Wristband have been developed to capture multiple physiological signals and to derive biometrics from these signals including resting heart rate, heart rate variability, and respiration rate. </sec> <sec> <title>OBJECTIVE</title> This study aims to evaluate the accuracy of the biometrics estimates and signal quality of the wristband. </sec> <sec> <title>METHODS</title> Measurements collected from 35 subjects using the Wavelet Wristband were compared with simultaneously recorded electrocardiogram and spirometry measurements. </sec> <sec> <title>RESULTS</title> The heart rate, heart rate variability (SDNN) and respiration rate estimates matched within 0.6 ± 0.9 bpm, 7 ± 10 ms and 1 ± 1 brpm mean absolute deviation of the reference measurements, respectively. The quality of the raw plethysmography signal collected by the wristband, as determined by the harmonic-to-noise ratio, was comparable to that obtained from measurements from a finger-clip plethysmography device. </sec> <sec> <title>CONCLUSIONS</title> The accuracy of the biometrics estimates and high signal quality indicate that the Wristband PPG device is suitable for performing pulse wave analysis and measuring vital signs. </sec>" @default.
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- W4247557897 date "2018-05-14" @default.
- W4247557897 modified "2023-10-16" @default.
- W4247557897 title "Design rationale and performance evaluation of Wavelet Health Wristband: bench-top validation of a wrist-worn physiological signal recorder (Preprint)" @default.
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- W4247557897 doi "https://doi.org/10.2196/preprints.11040" @default.
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