Fitbeat: COVID-19 estimation based on wristband heart rate using a contrastive convolutional auto-encoder

•Heart rate based identification of individuals with suspected COVID-19 infection.•Semi-supervised framework using combination of auto-encoder and contrastive loss.•Contrastive convolutional auto-encoder is capable of finding proper latent attributes.•COVID-19 estimation performance declines with da...

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Veröffentlicht in:	Pattern recognition 2022-03, Vol.123, p.108403-108403, Article 108403
Hauptverfasser:	Liu, Shuo, Han, Jing, Puyal, Estela Laporta, Kontaxis, Spyridon, Sun, Shaoxiong, Locatelli, Patrick, Dineley, Judith, Pokorny, Florian B., Costa, Gloria Dalla, Leocani, Letizia, Guerrero, Ana Isabel, Nos, Carlos, Zabalza, Ana, Sørensen, Per Soelberg, Buron, Mathias, Magyari, Melinda, Ranjan, Yatharth, Rashid, Zulqarnain, Conde, Pauline, Stewart, Callum, Folarin, Amos A, Dobson, Richard JB, Bailón, Raquel, Vairavan, Srinivasan, Cummins, Nicholas, Narayan, Vaibhav A, Hotopf, Matthew, Comi, Giancarlo, Schuller, Björn, Consortium, RADAR-CNS
Format:	Artikel
Sprache:	eng
Schlagworte:	Anomaly detection Contrastive learning Convolutional auto-encoder COVID-19 Respiratory tract infection
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