title: Application of audio fingerprinting to neonatal EEG.
abstract: A clinical neurophysiologist must recognize patterns in EEG signals to evaluate the health of a patient's brain activity. Rare or unusual patterns may take time to correctly identify. The ability to automatically assist this recall would be beneficial in ensuring that appropriate measures could be taken in a timely fashion. Audio fingerprinting is a method used to identify songs using only a snippet of the song. Fingerprints are extracted from a sub-section of the song and matched against a database of previously computed fingerprints. In this paper, a fingerprint quantization technique is implemented on neonatal EEG data to attempt to identify sections of EEG data when only seeing a sub-section of the data. The impact of signal distortions is investigated and results from a database of one hour recordings from 40 newborns are presented.
authors.forename: B M
authors.initials: BM
authors.lastname: Murphy
authors.forename: C
authors.initials: C
authors.lastname: O'Driscoll
authors.forename: I
authors.initials: I
authors.lastname: Korotchikova
authors.forename: G B
authors.initials: GB
authors.lastname: Boylan
authors.forename: G
authors.initials: G
authors.lastname: Lightbody
authors.forename: W P
authors.initials: WP
authors.lastname: Marnane
mesh_terms: D000162:Acoustics; D000465:Algorithms; D016208:Databases, Factual; D004569:Electroencephalography / Q000379:methods*; D006801:Humans; D007223:Infant; D007231:Infant, Newborn; D012815:Signal Processing, Computer-Assisted; D059629:Signal-To-Noise Ratio