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The Electrocardiogram (ECG) collected in real-life scenarios is often noisy and contaminated with motion artefacts. This study proposes a new framework to analyse the heart rate variability (HRV) in mobile scenarios by introducing novel R-peak detection and HRV detrending algorithms. The R-peak detection combines matched filtering and Hilbert transform, while detrending the HRV is performed using empirical mode decomposition with novel physically meaningful stopping criteria. Next, fourdoi:10.1109/icassp.2016.7471788 dblp:conf/icassp/ChanwimalueangA16 fatcat:ng4l62zdpzczpoiissid3grxg4