SiamQuality: a ConvNet-based foundation model for photoplethysmography signals
Cheng Ding,
Zhicheng Guo,
Zhaoliang Chen
et al.
Abstract:Objective: Physiological data are often low quality and thereby compromises the effectiveness of related health monitoring. The primary goal of this study is to develop a robust foundation model that can effectively handle low-quality issue in physiological data.
Approach: We introduce SiamQuality, a self-supervised learning approach using convolutional neural networks (CNNs) as the backbone. SiamQuality learns to generate similar representations for both high and low quality photoplethysmography (PPG)… Show more
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