Improving the Accuracy in Classification of Blood Pressure from Photoplethysmography Using Continuous Wavelet Transform and Deep Learning.

"the supplementary materials have been uploaded on https://github com/hao203/journal-file/tree/main/ppg-bp . the supplementary materials have been uploaded on https://github com/hao203/journal-file/tree/main/ppg-bp .; supplementary materials supplementary materials s_file 1: python code for scalograms transformed from ppg by continuous wavelet transform."

"Disclosure The funding source had no role in the study design; the collection, analysis, and interpretation of data; the writing of the manuscript; and the decision to submit the manuscript for publication. Conflicts of Interest Jiaze Wu, Hao Liang, Xindi Huang, Jianghua Huang, and Qinghua Peng declare that they have no conflicts of interest."

"The authors are thankful to Mohamed Elgendi and his team, for guiding them to their important publications and for the stimulating questions on wavelet transform and deep learning in hypertension diagnosis. Their articles were vital in inspiring the authors to think out the more effective work. This work was supported by the grants from China Postdoctoral Science Foundation (no. 2020M682578), Hunan Province Outstanding Postdoctoral Innovative Talent Project (no. 2020RC2061), and Hunan Provincial Department of Education (nos. 18C0380 and 18K070). Disclosure: The funding source had no role in the study design; the collection, analysis, and interpretation of data; the writing of the manuscript; and the decision to submit the manuscript for publication."