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Position recognition algorithm using a two-stage pattern classification set applied in sleep tracking

  • The overall goal of this work is to detect and analyze a person's movement, breathing and heart rate during sleep in a common bed overnight without any additional physical contact. The measurement is performed with the help of sensors placed between the mattress and the frame. A two-stage pattern classification algorithm based has been implemented that applies statistics analysis to recognize the position of patients. The system is implemented in a sensors-network, hosting several nodes and communication end-points to support quick and efficient classification. The overall tests show convincing results for the position recognition and a reasonable overlap in matching.

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Author:Eva Rodríguez de Trujillo, Ralf SeepoldORCiDGND, Maksym GaidukORCiD
Parent Title (English):Procedia Computer Science
Document Type:Article
Year of Publication:2018
Release Date:2019/01/16
Tag:Movement detection; Pattern recognition; Sleep positions; Sleep study
First Page:1819
Last Page:1827
Institutes:Fakultät Informatik
Open Access?:Ja
Relevance:Peer reviewed Publikation entsprechend Liste der AG4
Licence (English):License LogoLizenzbedingungen Elsevier
Licence (German):License LogoCreative Commons - CC BY-NC-ND - Namensnennung - Nicht kommerziell - Keine Bearbeitungen 4.0 International