PreprintArticleVersion 1Preserved in Portico This version is not peer-reviewed
Improving Estimation of Heart Rate and Heart Variability with Real-Time Palm Images Based on Independent Component Analysis and Particle Swarm Optimization
Version 1
: Received: 22 January 2024 / Approved: 23 January 2024 / Online: 23 January 2024 (09:30:41 CET)
How to cite:
Su, T.-J.; Cheng, J.-C.; Lin, W.-H.; Yang, W.-R.; Hung, Y.-C.; Wang, S.-M.; Tseng, L.-C. Improving Estimation of Heart Rate and Heart Variability with Real-Time Palm Images Based on Independent Component Analysis and Particle Swarm Optimization. Preprints2024, 2024011618. https://doi.org/10.20944/preprints202401.1618.v1
Su, T.-J.; Cheng, J.-C.; Lin, W.-H.; Yang, W.-R.; Hung, Y.-C.; Wang, S.-M.; Tseng, L.-C. Improving Estimation of Heart Rate and Heart Variability with Real-Time Palm Images Based on Independent Component Analysis and Particle Swarm Optimization. Preprints 2024, 2024011618. https://doi.org/10.20944/preprints202401.1618.v1
Su, T.-J.; Cheng, J.-C.; Lin, W.-H.; Yang, W.-R.; Hung, Y.-C.; Wang, S.-M.; Tseng, L.-C. Improving Estimation of Heart Rate and Heart Variability with Real-Time Palm Images Based on Independent Component Analysis and Particle Swarm Optimization. Preprints2024, 2024011618. https://doi.org/10.20944/preprints202401.1618.v1
APA Style
Su, T. J., Cheng, J. C., Lin, W. H., Yang, W. R., Hung, Y. C., Wang, S. M., & Tseng, L. C. (2024). Improving Estimation of Heart Rate and Heart Variability with Real-Time Palm Images Based on Independent Component Analysis and Particle Swarm Optimization. Preprints. https://doi.org/10.20944/preprints202401.1618.v1
Chicago/Turabian Style
Su, T., Shih-Ming Wang and Li-chin Tseng. 2024 "Improving Estimation of Heart Rate and Heart Variability with Real-Time Palm Images Based on Independent Component Analysis and Particle Swarm Optimization" Preprints. https://doi.org/10.20944/preprints202401.1618.v1
Abstract
Since the outbreak of the COVID-19 pandemic, patients infected with COVID-19 may experience abnormal heart rates, posing potential health risks. This study proposes a non-contact method for measuring heart rate (HR) and heart rate variability (HRV) to effectively reduce the risk of infection and assist healthcare professionals in more accurate diagnosis and treatment. In this study, except for the different image acquisition method, other research processes and methods are similar to the research methods in [15]. The image acquisition method is changed from forehead image to palm image. The new non-contact measurement performance of the proposed method can effectively not only avoid infection concerns but also obtain heart rate and HRV quickly and conveniently, providing higher accuracy for physiological parameters, root mean square error (RMSE), and mean absolute percentage error (MAPE) compared to those in recently published papers.
Computer Science and Mathematics, Artificial Intelligence and Machine Learning
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.