Transfer learning from ECG to PPG for improved sleep staging from wrist-worn wearables Q Li, Q Li, AS Cakmak, G Da Poian, DL Bliwise, V Vaccarino, AJ Shah, ... Physiological measurement 42 (4), 044004, 2021 | 34 | 2021 |
Classification and prediction of post-trauma outcomes related to PTSD using circadian rhythm changes measured via wrist-worn research watch in a large longitudinal cohort AS Cakmak, EAP Alday, G Da Poian, AB Rad, TJ Metzler, TC Neylan, ... IEEE journal of biomedical and health informatics 25 (8), 2866-2876, 2021 | 21 | 2021 |
Addressing class imbalance in classification problems of noisy signals by using fourier transform surrogates JTC Schwabedal, JC Snyder, A Cakmak, S Nemati, GD Clifford arXiv preprint arXiv:1806.08675, 2018 | 20 | 2018 |
An unbiased, efficient sleep–wake detection algorithm for a population with sleep disorders: change point decoder AS Cakmak, G Da Poian, A Willats, A Haffar, R Abdulbaki, YA Ko, ... Sleep 43 (8), zsaa011, 2020 | 13 | 2020 |
Utility of wrist-wearable data for assessing pain, sleep, and anxiety outcomes after traumatic stress exposure LD Straus, X An, Y Ji, SA McLean, TC Neylan, AS Cakmak, A Richards, ... JAMA psychiatry 80 (3), 220-229, 2023 | 12 | 2023 |
Use of a wearable device to assess sleep and motor function in Duchenne muscular dystrophy BI Siegel, A Cakmak, E Reinertsen, M Benoit, J Figueroa, GD Clifford, ... Muscle & nerve 61 (2), 198-204, 2020 | 11 | 2020 |
Personalized heart failure severity estimates using passive smartphone data AS Cakmak, E Reinertsen, HA Taylor, AJ Shah, GD Clifford 2018 IEEE International Conference on Big Data (Big Data), 1569-1574, 2018 | 10 | 2018 |
Using convolutional variational autoencoders to predict post-trauma health outcomes from actigraphy data AS Cakmak, N Thigpen, G Honke, EP Alday, AB Rad, R Adaimi, ... arXiv preprint arXiv:2011.07406, 2020 | 4 | 2020 |
Passive smartphone actigraphy data predicts heart failure decompensation AS Cakmak, HJ Lanier, E Reinertsen, A Harzand, AM Zafari, ... Circulation 140 (Suppl_1), A15444-A15444, 2019 | 3 | 2019 |
Obstructive Sleep Apnea Classification in a Mixed-Disorder Elderly Male Population Using a Low-Cost Off-Body Movement Sensor PB Suresha, AS Cakmak, G Da Poian, AJ Shah, V Vaccarino, D Bliwise, ... 2019 IEEE EMBS International Conference on Biomedical & Health Informatics …, 2019 | 3 | 2019 |
Passive data collection and use of machine-learning models for event prediction G Clifford, A Cakmak, A Shah, E Reinertsen US Patent App. 17/295,248, 2021 | 1 | 2021 |
Late fusion of machine learning models using passively captured interpersonal social interactions and motion from smartphones predicts decompensation in heart failure AS Cakmak, S Densen, G Najarro, P Rout, CJ Rozell, OT Inan, AJ Shah, ... arXiv preprint arXiv:2104.01511, 2021 | 1 | 2021 |
Benchmarking changepoint detection algorithms on cardiac time series A Cakmak, E Reinertsen, S Nemati, GD Clifford arXiv preprint arXiv:2404.12408, 2024 | | 2024 |
Estimating Heart Rate Recovery After Maximum or High-Exertion Activity Based on Sensor Observations of Daily Activities WRPIII Britni A Crocker, Adeeti V Ullal, Ayse S Cakmak, Johahn Y Leung ... US Patent App. 17/952,147, 2023 | | 2023 |
Systems and Methods for Detecting Sleep Activity G Clifford, A Cakmak, C Rozell, A Willats US Patent App. 17/640,405, 2022 | | 2022 |
Passively Captured Interpersonal Social Interactions and Motion From Smartphones for Predicting Decompensation in Heart Failure: Observational Cohort Study AS Cakmak, EAP Alday, S Densen, G Najarro, P Rout, CJ Rozell, OT Inan, ... JMIR Formative Research 6 (8), e36972, 2022 | | 2022 |
Twenty-four hour activity patterns, pain, and mental health trajectories after a traumatic event. L Straus, X An, A Cakmak, G Clifford, T Neylan, S McLean | | 2022 |
System and methods for tracking behavior and detecting abnormalities G Clifford, J Zelko, N Shu, P Suresha, A Cakmak US Patent App. 17/430,414, 2022 | | 2022 |