Compressed Deep Learning to Classify Arrhythmia in an Embedded Wearable Device

The importance of an embedded wearable device with automatic detection and alarming cannot be overstated, given that 15–30% of patients with atrial fibrillation are reported to be asymptomatic. These asymptomatic patients do not seek medical care, hence traditional diagnostic tools including Holter...

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Detalles Bibliográficos
Autores principales: Lee, Kwang-Sig, Park, Hyun-Joon, Kim, Ji Eon, Kim, Hee Jung, Chon, Sangil, Kim, Sangkyu, Jang, Jaesung, Kim, Jin-Kook, Jang, Seongbin, Gil, Yeongjoon, Son, Ho Sung
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8914813/
https://www.ncbi.nlm.nih.gov/pubmed/35270923
http://dx.doi.org/10.3390/s22051776

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8914813/
https://www.ncbi.nlm.nih.gov/pubmed/35270923
http://dx.doi.org/10.3390/s22051776

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