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• W3214448957 abstract "Physical activity can severely influence the quality of photoplethysmographic (PPG) signals due to motion artefacts (MA). This study aims to extract heart rate (HR) and respiration rate (RR) values from raw PPG signals captured from a multi-wavelength illumination optoelectronic patch sensor (mOEPS) during physical activity of different intensities, and to do this in an effective manner. The proposed method, combined with a 3-axis accelerometer as a motion reference, was developed for the extraction of the desired PPG signals. The adaptive notch-filtration architecture (ANFA) comprises three parts: 1) the adaptive moving average filter, 2) the adaptive notch filter, and 3) extraction for physiological parameters. 24 healthy subjects completed four stages of exercise of increasing intensity. The recovered PPG signals for the calculation of HR and RR were comparable to the measurements from commercial devices, with an average absolute error for HR of < 1.0 beats/min for the IEEE-SPC dataset, and 1.3 beats/min for HR, and 2.8 breaths/min for RR, from the in–house dataset. The ANFA has been proofed to have a good robustness and low complexity to be suitable for application in real-time physiological monitoring." @default.
• W3214448957 created "2021-11-22" @default.
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• W3214448957 date "2022-02-01" @default.
• W3214448957 modified "2023-10-16" @default.
• W3214448957 title "Adaptive notch-filtration to effectively recover photoplethysmographic signals during physical activity" @default.
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• W3214448957 doi "https://doi.org/10.1016/j.bspc.2021.103303" @default.
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