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Proceedings (MDPI)
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July 5, 2022
Measuring Vascular Recovery Rate After Exercise <sup>†</sup>
Halil Dijab, Jordi Alastruey, Peter H Charlton
Machine Learning. Health
|
September 17, 2025
Generalizable deep learning for photoplethysmography-based blood pressure estimation-A benchmarking study
Mohammad Moulaeifard, Peter H Charlton, Nils Strodthoff
Proceedings (MDPI)
|
July 5, 2022
Using Smart Wearables to Monitor Cardiac Ejection <sup>†</sup>
Aristide Mathieu, Peter H Charlton, Jordi Alastruey
Frontiers in Physiology
|
March 12, 2024
Photoplethysmogram beat detection using Symmetric Projection Attractor Reconstruction
Callum Pettit, Peter H Charlton, Philip J Aston
Proceedings (MDPI)
|
July 7, 2022
Alzheimer's Disease: A Step Towards Prognosis Using Smart Wearables <sup>†</sup>
Antonella D Pontoriero, Peter H Charlton, Jordi Alastruey
Physiological Measurement
|
May 4, 2022
Establishing best practices in photoplethysmography signal acquisition and processing
Peter H Charlton, Kristjan Pilt, Panicos A Kyriacou
Physiological Measurement
|
June 6, 2018
Comment on 'Numerical assessment and comparison of pulse wave velocity methods aiming at measuring aortic stiffness'
Peter H Charlton, Marie Willemet, Phil Chowienczyk, et al.
Physiological Measurement
|
March 13, 2024
pyPPG: a Python toolbox for comprehensive photoplethysmography signal analysis
Márton Á Goda, Peter H Charlton, Joachim A Behar
Arxiv
|
July 28, 2023
Robust peak detection for photoplethysmography signal analysis
Márton Á Goda, Peter H Charlton, Joachim A Behar
Engineering Proceedings
|
March 29, 2021
Acquiring Wearable Photoplethysmography Data in Daily Life: The PPG Diary Pilot Study <sup>†</sup>
Peter H Charlton, Panicos Kyriacou, Jonathan Mant, et al.
Page
of 6
Search research articles
Search
Showing results (1-10 of 53) with videos related to
Sort By:
Page
of 6
Proceedings (MDPI)
|
July 5, 2022
Measuring Vascular Recovery Rate After Exercise <sup>†</sup>
Halil Dijab, Jordi Alastruey, Peter H Charlton
Machine Learning. Health
|
September 17, 2025
Generalizable deep learning for photoplethysmography-based blood pressure estimation-A benchmarking study
Mohammad Moulaeifard, Peter H Charlton, Nils Strodthoff
Proceedings (MDPI)
|
July 5, 2022
Using Smart Wearables to Monitor Cardiac Ejection <sup>†</sup>
Aristide Mathieu, Peter H Charlton, Jordi Alastruey
Frontiers in Physiology
|
March 12, 2024
Photoplethysmogram beat detection using Symmetric Projection Attractor Reconstruction
Callum Pettit, Peter H Charlton, Philip J Aston
Proceedings (MDPI)
|
July 7, 2022
Alzheimer's Disease: A Step Towards Prognosis Using Smart Wearables <sup>†</sup>
Antonella D Pontoriero, Peter H Charlton, Jordi Alastruey
Physiological Measurement
|
May 4, 2022
Establishing best practices in photoplethysmography signal acquisition and processing
Peter H Charlton, Kristjan Pilt, Panicos A Kyriacou
Physiological Measurement
|
June 6, 2018
Comment on 'Numerical assessment and comparison of pulse wave velocity methods aiming at measuring aortic stiffness'
Peter H Charlton, Marie Willemet, Phil Chowienczyk, et al.
Physiological Measurement
|
March 13, 2024
pyPPG: a Python toolbox for comprehensive photoplethysmography signal analysis
Márton Á Goda, Peter H Charlton, Joachim A Behar
Arxiv
|
July 28, 2023
Robust peak detection for photoplethysmography signal analysis
Márton Á Goda, Peter H Charlton, Joachim A Behar
Engineering Proceedings
|
March 29, 2021
Acquiring Wearable Photoplethysmography Data in Daily Life: The PPG Diary Pilot Study <sup>†</sup>
Peter H Charlton, Panicos Kyriacou, Jonathan Mant, et al.
Page
of 6