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Machine-learning for photoplethysmography analysis: Benchmarking feature, image, and signal-based approaches
27 February 2025
Mohammad Moulaeifard
Loic Coquelin
Mantas Rinkevičius
Andrius Sološenko
Oskar Pfeffer
Ciaran Bench
Nando Hegemann
Sara Vardanega
Manasi Nandi
Jordi Alastruey
Christian Heiss
Vaidotas Marozas
Andrew Thompson
Philip Aston
Peter H. Charlton
Nils Strodthoff
OOD
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Papers citing
"Machine-learning for photoplethysmography analysis: Benchmarking feature, image, and signal-based approaches"
4 / 4 papers shown
A systematic evaluation of uncertainty quantification techniques in deep learning: a case study in photoplethysmography signal analysis
Ciaran Bench
Oskar Pfeffer
Vivek Desai
Mohammad Moulaeifard
Loic Coquelin
Peter H. Charlton
Nils Strodthoff
Nando Hegemann
Philip Aston
Andrew Thompson
211
0
0
31 Oct 2025
Generalizable deep learning for photoplethysmography-based blood pressure estimation -- A Benchmarking Study
Mohammad Moulaeifard
Peter H. Charlton
Nils Strodthoff
OOD
600
7
0
26 Feb 2025
PaPaGei: Open Foundation Models for Optical Physiological Signals
International Conference on Learning Representations (ICLR), 2024
Arvind Pillai
Dimitris Spathis
F. Kawsar
Mohammad Malekzadeh
VLM
431
61
0
27 Oct 2024
A Review of Deep Learning Methods for Photoplethysmography Data
Guangkun Nie
Jiabao Zhu
Gongzheng Tang
Deyun Zhang
Shijia Geng
Qinghao Zhao
Shenda Hong
332
27
0
23 Jan 2024
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