CovidRhythm: A Deep Learning Model for Passive Prediction of Covid-19 Using Biobehavioral Rhythms Derived From Wearable Physiological Data

CovidRhythm: A Deep Learning Model for Passive Prediction of Covid-19 Using Biobehavioral Rhythms Derived From Wearable Physiological Data

<italic>Goal:</italic> To investigate whether a deep learning model can detect Covid-19 from disruptions in the human body&#x0027;s physiological (heart rate) and rest-activity rhythms (rhythmic dysregulation) caused by the SARS-CoV-2 virus. <italic>Methods:</italic> We p...

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Bibliographic Details
Main Authors: Atifa Sarwar, Emmanuel O. Agu, Abdulsalam Almadani
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Open Journal of Engineering in Medicine and Biology
Subjects:
Biobehavioral rhythms
Covid-19
deep learning
passive assessment
multi-head self attention
physiological signs
Online Access:https://ieeexplore.ieee.org/document/10079194/

Internet

https://ieeexplore.ieee.org/document/10079194/

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