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Fitbeat: COVID-19 Estimation based on Wristband Heart Rate [article]

Shuo Liu, Jing Han, Estela Laporta Puyal, Spyridon Kontaxis, Shaoxiong Sun, Patrick Locatelli, Judith Dineley, Florian B. Pokorny, Gloria Dalla Costa, Letizia Leocan, Ana Isabel Guerrero, Carlos Nos (+17 others)
2021 arXiv   pre-print
Aspart of the project protocol, heart-rate data was collected from participants using a Fitbit wristband.  ...  This study investigates the potential of deep learning methods to identify individuals with suspected COVID-19 infection using remotely collected heart-rate data.  ...  Overall, we are optimistic that an applicable decision can be made as to COVID-19 presence based on the symptoms defined herein based on machine learning analysis of consumer-type heart rate measurement  ... 
arXiv:2104.09263v1 fatcat:ik52jtdtzndptdil3jz6dx4mg4

Fitbeat: COVID-19 Estimation Based on Wristband Heart Rate Using a Contrastive Convolutional Auto-Encoder

Shuo Liu, Jing Han, Estela Laporta Puyal, Spyridon Kontaxis, Shaoxiong Sun, Patrick Locatelli, Judith Dineley, Florian B. Pokorny, Gloria Dalla Costa, Letizia Leocani, Ana Isabel Guerrero, Carlos Nos (+18 others)
2021 Pattern Recognition  
Heart-rate data was remotely collected using a Fitbit wristband.  ...  On a test set of 19 participants with MS with reported symptoms of COVID-19, each one paired with a participant with MS with no COVID-19 symptoms, the contrastive CAE achieves an unweighted average recall  ...  The models were pre-trained based on the heart rate data of 49 participants with MS who reported having COVID-19-like symptoms.  ... 
doi:10.1016/j.patcog.2021.108403 pmid:34720200 pmcid:PMC8547790 fatcat:bs6ninnakfda3lw5t7wwqujzua