A cascaded approach of group sparse mode decomposition and deep neural network for heart rate estimation using reference signal-less PPG signal

•The proposed GSMD-based method effectively removes MA from a PPG and doesn’t require a reference signal.•Proposed a CNN-Bi-LSTM-Attention model for robust HR estimation from PPG signals.•Applied Bayesian optimization for enhanced accuracy and computational efficiency.•Achieved MAE of 2.42 BPM, vali...

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Bibliographic Details
Published in:	Measurement : journal of the International Measurement Confederation Vol. 246; p. 116546
Main Authors:	Pankaj, Maan, Pratibha, Kumar, Manjeet, Kumar, Ashish, Komaragiri, Rama
Format:	Journal Article
Language:	English
Published:	Elsevier Ltd 31.03.2025
Subjects:	Bayesian optimization Bi-LSTM CNN Deep learning Group sparse mode decomposition Heart rate estimation K-fold cross-validation PPG signal Deep learning Bi-LSTM CNN PPG signal Bayesian optimization K-fold cross-validation Group sparse mode decomposition Heart rate estimation
ISSN:	0263-2241
Online Access:	Get full text
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