A Novel Algorithm for Heart Rate Estimation Based on Synchrosqueezing Transform

Nils Laurent (1) , Sylvain Meignen (1) , Julie Fontecave-Jallon (2) , Bertrand Rivet (3)

1 DAO - Données, Apprentissage et Optimisation
2 TIMC-PRETA - Physiologie cardio-Respiratoire Expérimentale Théorique et Appliquée
3 GIPSA-VIBS - GIPSA - Vision and Brain Signal Processing

To estimate the heart rate (HR) from electrocardiogram (ECG), time-frequency representations such as the short-time Fourier transform (STFT) is often used. As the STFT is constrained by the choice of a specific analysis window used for its definition, we alternatively propose to estimate HR from a synchrosqueezed STFT. More precisely, we build a novel algorithm inspired by non-negative matrix factorization to estimate HR by determining the minimal Wasserstein distance between a synchrosqueezed STFT and columns of a specific dictionary matrix. Throughout numerical simulations carried out on both synthetic and real ECGs, we show in what way to use a synchrosqueezed STFT rather than STFT improves HR estimation.

Mots clés: HR estimation; non-negative matrix factorization; Wasserstein distance; synchrosqueezing transform

Domaines: Traitement du signal et de l'image [eess.SP]

Nils Laurent, Sylvain Meignen, Julie Fontecave-Jallon, Bertrand Rivet. A Novel Algorithm for Heart Rate Estimation Based on Synchrosqueezing Transform. EUSIPCO 2021 - 29th European Signal Processing Conference (EUSIPCO), Aug 2021, Dublin, Ireland. pp.1286-1290, ⟨10.23919/EUSIPCO54536.2021.9616306⟩. ⟨hal-03544794⟩