Pedro Fonseca
Pedro Fonseca
Senior Scientist, Philips Sleep and Respiratory Care
Verified email at
Cited by
Cited by
Sleep stage classification with ECG and respiratory effort
P Fonseca, X Long, M Radha, R Haakma, RM Aarts, J Rolink
Physiological measurement 36 (10), 2027, 2015
Sleep stage classification from heart-rate variability using long short-term memory neural networks
M Radha, P Fonseca, A Moreau, M Ross, A Cerny, P Anderer, X Long, ...
Scientific reports 9 (1), 14149, 2019
Validation of photoplethysmography-based sleep staging compared with polysomnography in healthy middle-aged adults
P Fonseca, T Weysen, MS Goelema, EIS Møst, M Radha, ...
Sleep 40 (7), zsx097, 2017
Sleep and wake classification with actigraphy and respiratory effort using dynamic warping
X Long, P Fonseca, J Foussier, R Haakma, RM Aarts
IEEE journal of biomedical and health informatics 18 (4), 1272-1284, 2013
Analyzing respiratory effort amplitude for automated sleep stage classification
X Long, J Foussier, P Fonseca, R Haakma, RM Aarts
Biomedical Signal Processing and Control 14, 197-205, 2014
Cardiorespiratory sleep stage detection using conditional random fields
P Fonseca, N Den Teuling, X Long, RM Aarts
IEEE journal of biomedical and health informatics 21 (4), 956-966, 2016
Estimating blood pressure trends and the nocturnal dip from photoplethysmography
M Radha, K De Groot, N Rajani, CCP Wong, N Kobold, V Vos, P Fonseca, ...
Physiological measurement 40 (2), 025006, 2019
A deep transfer learning approach for wearable sleep stage classification with photoplethysmography
M Radha, P Fonseca, A Moreau, M Ross, A Cerny, P Anderer, X Long, ...
NPJ digital medicine 4 (1), 135, 2021
Wearable monitoring of sleep-disordered breathing: Estimation of the apnea–hypopnea index using wrist-worn reflective photoplethysmography
GB Papini, P Fonseca, MM van Gilst, JWM Bergmans, R Vullings, ...
Scientific reports 10 (1), 13512, 2020
Automatic sleep staging using heart rate variability, body movements, and recurrent neural networks in a sleep disordered population
P Fonseca, MM van Gilst, M Radha, M Ross, A Moreau, A Cerny, ...
Sleep 43 (9), zsaa048, 2020
Measuring dissimilarity between respiratory effort signals based on uniform scaling for sleep staging
X Long, J Yang, T Weysen, R Haakma, J Foussier, P Fonseca, RM Aarts
Physiological measurement 35 (12), 2529, 2014
A comparison of probabilistic classifiers for sleep stage classification
P Fonseca, N Den Teuling, X Long, RM Aarts
Physiological measurement 39 (5), 055001, 2018
Spectral boundary adaptation on heart rate variability for sleep and wake classification
X Long, P Fonseca, R Haakma, RM Aarts, J Foussier
International Journal on Artificial Intelligence Tools 23 (03), 1460002, 2014
Automatic video summarization based on MPEG-7 descriptions
PM Fonseca, F Pereira
Signal Processing: Image Communication 19 (8), 685-699, 2004
Photoplethysmography beat detection and pulse morphology quality assessment for signal reliability estimation
GB Papini, P Fonseca, XL Aubert, S Overeem, JWM Bergmans, R Vullings
2017 39th annual international conference of the IEEE engineering in …, 2017
Measures of cardiovascular autonomic activity in insomnia disorder: A systematic review
MM Nano, P Fonseca, R Vullings, RM Aarts
PloS one 12 (10), e0186716, 2017
A novel low-complexity post-processing algorithm for precise QRS localization
P Fonseca, R Aarts, X Long, P, Foussier
SpringerPlus 3, 376, 2004
Protocol of the SOMNIA project: an observational study to create a neurophysiological database for advanced clinical sleep monitoring
MM van Gilst, JP van Dijk, R Krijn, B Hoondert, P Fonseca, RJG van Sloun, ...
BMJ open 9 (11), e030996, 2019
method and apparatus for selecting a representative image
MA Peters, P Fonseca
US Patent App. 13/377,841, 2012
Image processing
MA Peters, T Tsoneva, P Fonseca
US Patent App. 12/999,381, 2011
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