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- W2509704932 abstract "Measuring bio signals such as the heart rate in non medical applications is gaining an increasing importance. With camera based photoplethysmography (PPG) it is possible to measure the heart rate remotely with built in webcams of every tablet and laptop. Recent research with machine learning based methods showed great success compared to signal processing based methods. In this paper, we use k-nearest neighbor (kNN) and multilayer perceptron (MLP) with an alternative representation of the input vector. Estimating the quality of peaks with a Gaussian distribution could further improve the detection. Overall we could improve the root mean square error (RMSE) from 23.97 to 8.62." @default.
- W2509704932 created "2016-09-16" @default.
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- W2509704932 date "2016-01-01" @default.
- W2509704932 modified "2023-10-14" @default.
- W2509704932 title "Machine Learning Driven Heart Rate Detection with Camera Photoplethysmography in Time Domain" @default.
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- W2509704932 doi "https://doi.org/10.1007/978-3-319-46182-3_27" @default.
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