Algorithms for sleep-wake identification using actigraphy: A comparative study and new results

Joëlle Tilmanne, Jérôme Urbain, Mayuresh V. Kothare, Alain Vande Wouwer, Sanjeev V. Kothare

Research output: Contribution to journalArticlepeer-review

Abstract

The aim of this study was to investigate two new scoring algorithms employing artificial neural networks and decision trees for distinguishing sleep and wake states in infants using actigraphy and to validate and compare the performance of the proposed algorithms with known actigraphy scoring algorithms. The study employed previously recorded longitudinal physiological infant data set from the Collaborative Home Infant Monitoring Evaluation (CHIME) study conducted between 1994 and 1998 [b4http://dccwww.bumc.bu.edu/ChimeNisp/Main- Chime.asp; Sleep26 (1997) 553] at five clinical sites around the USA. The original CHIME data set contains recordings of 1079 infants

Original languageEnglish (US)
Pages (from-to)85-98
Number of pages14
JournalJournal of Sleep Research
Volume18
Issue number1
DOIs
StatePublished - Mar 2009
Externally publishedYes

Keywords

  • Actigraphy
  • Artificial neural networks
  • Decision trees
  • Sleep diagnosis
  • Sleep-wake scoring

ASJC Scopus subject areas

  • Behavioral Neuroscience
  • Cognitive Neuroscience
  • Medicine(all)

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