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

Eva Rodríguez de Trujillo | Zendy; Ralf Seepold | Zendy; Maksym Gaiduk | Zendy

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

Author(s) -

Eva Rodríguez de Trujillo,

Ralf Seepold,

Maksym Gaiduk

Publication year - 2018

Publication title -

procedia computer science

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.334

H-Index - 76

ISSN - 1877-0509

DOI - 10.1016/j.procs.2018.08.095

Subject(s) - computer science , position (finance) , frame (networking) , set (abstract data type) , sleep (system call) , algorithm , matching (statistics) , tracking (education) , artificial intelligence , pattern recognition (psychology) , statistics , telecommunications , psychology , pedagogy , mathematics , finance , economics , programming language , operating system

STUDENT PAPER 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 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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