title: Automatic sleep spindles detection--overview and development of a standard proposal assessment method.
abstract: Since the 1970s, various automatic sleep spindles procedures have been implemented and presented in the literature. Unfortunately, their results are not easily comparable because the databases, the assessment methods and the terminologies employed are often radically different. In this study, we propose a systematic assessment method for any automatic sleep spindles detection algorithm. We apply this assessment method to our own automatic detection process in order to illustrate and legitimate its use. We obtain a global sensitivity of 70.20%, for a false positive proportion (relative to the total number of visually scored sleep spindles) of only 26.44% (False positive rate = 1.38% and specificity = 98.62%).
authors.affiliation: TCTS Lab, Université de Mons -UMONS, B-7000 Mons, Belgium. stephanie.devuyst@umons.ac.be
authors.forename: S
authors.initials: S
authors.lastname: Devuyst
authors.forename: T
authors.initials: T
authors.lastname: Dutoit
authors.forename: P
authors.initials: P
authors.lastname: Stenuit
authors.forename: M
authors.initials: M
authors.lastname: Kerkhofs
mesh_terms: D000328:Adult; D000465:Algorithms; D001921:Brain / Q000503:physiopathology*; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D004569:Electroencephalography / Q000379:methods*; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D010363:Pattern Recognition, Automated / Q000379:methods*; D017286:Polysomnography / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012890:Sleep; D012893:Sleep Wake Disorders / Q000175:diagnosis* / Q000503:physiopathology*