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Deep PPG: Large-Scale Heart Rate Estimation with Convolutional Neural Networks
2019
Sensors
Photoplethysmography (PPG)-based continuous heart rate monitoring is essential in a number of domains, e.g., for healthcare or fitness applications. Recently, methods based on time-frequency spectra emerged to address the challenges of motion artefact compensation. However, existing approaches are highly parametrised and optimised for specific scenarios of small, public datasets. We address this fragmentation by contributing research into the robustness and generalisation capabilities of
doi:10.3390/s19143079
pmid:31336894
pmcid:PMC6679242
fatcat:7yxsn6hiznfrjpuzksh2y7iabm