Multiparameter Respiratory Rate Estimation from the Photoplethysmogram W Karlen, S Raman, JM Ansermino, GA Dumont IEEE Transactions on Biomedical Engineering 60 (7), 1946 - 1953, 2013 | 492 | 2013 |
Cxplain: Causal explanations for model interpretation under uncertainty P Schwab, W Karlen Advances in neural information processing systems 32, 2019 | 220 | 2019 |
Sleep and wake classification with ECG and respiratory effort signals W Karlen, C Mattiussi, D Floreano Biomedical Circuits and Systems, IEEE Transactions on 3 (2), 71-78, 2009 | 168 | 2009 |
Capillary refill time: is it still a useful clinical sign? A Pickard, W Karlen, JM Ansermino Anesthesia & Analgesia 113 (1), 120-123, 2011 | 156 | 2011 |
CapnoBase: Signal database and tools to collect, share and annotate respiratory signals W Karlen, M Turner, E Cooke, GA Dumont, JM Ansermino Annual Meeting of the Society for Technology in Anesthesia (STA) 48, 25, 2010 | 143 | 2010 |
Photoplethysmogram signal quality estimation using repeated Gaussian filters and cross-correlation W Karlen, K Kobayashi, JM Ansermino, GA Dumont Physiological measurement 33 (10), 1617, 2012 | 139 | 2012 |
Learning counterfactual representations for estimating individual dose-response curves P Schwab, L Linhardt, S Bauer, JM Buhmann, W Karlen Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 5612-5619, 2020 | 132 | 2020 |
Development of a screening tool for sleep disordered breathing in children using the phone Oximeter™ A Garde, P Dehkordi, W Karlen, D Wensley, JM Ansermino, GA Dumont PloS one 9 (11), e112959, 2014 | 131 | 2014 |
Estimating respiratory and heart rates from the correntropy spectral density of the photoplethysmogram A Garde, W Karlen, JM Ansermino, GA Dumont PloS one 9 (1), e86427, 2014 | 126 | 2014 |
Perfect match: A simple method for learning representations for counterfactual inference with neural networks P Schwab, L Linhardt, W Karlen arXiv preprint arXiv:1810.00656, 2018 | 113 | 2018 |
Beat by beat: Classifying cardiac arrhythmias with recurrent neural networks P Schwab, GC Scebba, J Zhang, M Delai, W Karlen 2017 Computing in Cardiology (CinC), 1-4, 2017 | 98 | 2017 |
Adaptive pulse segmentation and artifact detection in photoplethysmography for mobile applications W Karlen, JM Ansermino, G Dumont 2012 Annual International Conference of the IEEE Engineering in Medicine and …, 2012 | 95 | 2012 |
Improving the accuracy and efficiency of respiratory rate measurements in children using mobile devices W Karlen, H Gan, M Chiu, D Dunsmuir, G Zhou, GA Dumont, ... PloS one 9 (6), e99266, 2014 | 85 | 2014 |
Empirical mode decomposition for respiratory and heart rate estimation from the photoplethysmogram A Garde, W Karlen, P Dehkordi, JM Ansermino, GA Dumont Computing in cardiology 2013, 799-802, 2013 | 83 | 2013 |
Remote health diagnosis and monitoring in the time of COVID-19 JA Behar, C Liu, K Kotzen, K Tsutsui, VDA Corino, J Singh, MAF Pimentel, ... Physiological measurement 41 (10), 10TR01, 2020 | 73 | 2020 |
Multispectral video fusion for non-contact monitoring of respiratory rate and apnea G Scebba, G Da Poian, W Karlen IEEE Transactions on Biomedical Engineering 68 (1), 350-359, 2020 | 73 | 2020 |
Ethics review of big data research: What should stay and what should be reformed? A Ferretti, M Ienca, M Sheehan, A Blasimme, ES Dove, B Farsides, ... BMC medical ethics 22 (1), 51, 2021 | 67 | 2021 |
Pulse rate variability compared with heart rate variability in children with and without sleep disordered breathing P Dehkordi, A Garde, W Karlen, D Wensley, JM Ansermino, GA Dumont 2013 35th Annual International Conference of the IEEE Engineering in …, 2013 | 64 | 2013 |
Malaria and the ‘last’parasite: how can technology help? NM Pham, W Karlen, HP Beck, E Delamarche Malaria Journal 17, 1-16, 2018 | 61 | 2018 |
Usability testing of a prototype Phone Oximeter with healthcare providers in high‐and low‐medical resource environments J Hudson, SM Nguku, J Sleiman, W Karlen, GA Dumont, CL Petersen, ... Anaesthesia 67 (9), 957-967, 2012 | 60 | 2012 |