ArticleScientific reports2023
Deep-learning-based blood pressure estimation using multi channel photoplethysmogram and finger pressure with attention mechanism.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Towards trustworthy AI-driven cuffless blood pressure monitoring.NPJ digital medicine · 2026Article
- Current perspectives and challenges of digital hypertension: artificial intelligence in the management of hypertension.Clinical hypertension · 2026Review
- Oscillometric blood pressure estimation using machine learning-based mapping of waveform features.Biomedical engineering letters · 2025Article
- Accurate and 30-plus days reliable cuffless blood pressure measurements with 9-minutes personal photoplethysmograph data and mixed deduction learning.Scientific reports · 2024Article
- Transforming the cardiometabolic disease landscape: Multimodal AI-powered approaches in prevention and management.Cell metabolism · 2024Review
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Authors and funding
7 authors.
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Abstract
Recently, several studies have proposed methods for measuring cuffless blood pressure (BP) using finger photoplethysmogram (PPG) signals. This study presents a new BP estimation system that measures PPG signals under progressive finger pressure, making the system relatively robust to errors caused by finger position when using the cuffless oscillometric method. To reduce errors caused by finger position, we developed a sensor that can simultaneously measure multi-channel PPG and force signals in a wide field of view (FOV). We propose a deep-learning-based algorithm that can learn to focus on the optimal PPG channel from multi channel PPG using an attention mechanism. The errors (ME ± STD) of the proposed multi channel system were 0.43±9.35 mmHg and 0.21 ± 7.72 mmHg for SBP and DBP, respectively. Through extensive experiments, we found a significant performance difference depending on the location of the PPG measurement in the BP estimation system using finger pressure.
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