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End-to-End Deep Learning Architecture for Continuous Blood Pressure Estimation Using Attention Mechanism.
Eom, Heesang; Lee, Dongseok; Han, Seungwoo; Hariyani, Yuli Sun; Lim, Yonggyu; Sohn, Illsoo; Park, Kwangsuk; Park, Cheolsoo.
Affiliation
  • Eom H; Department of Computer Engineering, Kwangwoon University, Seoul 01897, Korea.
  • Lee D; Interdisciplinary Program in Bioengineering, Seoul National University, Seoul 03080, Korea.
  • Han S; Department of Intelligent Information System and Embedded Software Engineering, Kwangwoon University, Seoul 01897, Korea.
  • Hariyani YS; Department of Computer Engineering, Kwangwoon University, Seoul 01897, Korea.
  • Lim Y; School of Applied Science, Telkom University, Bandung 40257, Indonesia.
  • Sohn I; Department of Oriental Biomedical Engineering, Sangji University, Wonju 26339, Korea.
  • Park K; Department of Computer Science and Engineering, Seoul National University of Science and Technology, Seoul 01811, Korea.
  • Park C; Department of Biomedical Engineering, College of Medicine, Seoul National University, Seoul 03080, Korea.
Sensors (Basel) ; 20(8)2020 Apr 20.
Article in En | MEDLINE | ID: mdl-32325970
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Blood Pressure / Deep Learning Limits: Humans Language: En Journal: Sensors (Basel) Year: 2020 Document type: Article Country of publication: Switzerland
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Blood Pressure / Deep Learning Limits: Humans Language: En Journal: Sensors (Basel) Year: 2020 Document type: Article Country of publication: Switzerland