Automatic detection and classification of artifacts in single-channel EEG

Thomas Olund, Jonas Duun-Henriksen, Troels W. Kjaer, Helge B.D. Sorensen

Publikation: Bidrag til bog/antologi/rapportKonferencebidragForskningpeer review

Abstrakt

Ambulatory EEG monitoring can provide medical doctors important diagnostic information, without hospitalizing the patient. These recordings are however more exposed to noise and artifacts compared to clinically recorded EEG. An automatic artifact detection and classification algorithm for singlechannel EEG is proposed to help identifying these artifacts. Features are extracted from the EEG signal and wavelet subbands. Subsequently a selection algorithm is applied in order to identify the best discriminating features. A non-linear support vector machine is used to discriminate among different artifact classes using the selected features. Single-channel (Fp1-F7) EEG recordings are obtained from experiments with 12 healthy subjects performing artifact inducing movements. The dataset was used to construct and validate the model. Both subject-specific and generic implementation, are investigated. The detection algorithm yield an average sensitivity and specificity above 95% for both the subject-specific and generic models. The classification algorithm show a mean accuracy of 78 and 64% for the subject-specific and generic model, respectively. The classification model was additionally validated on a reference dataset with similar results.

OriginalsprogEngelsk
Titel2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014
ForlagInstitute of Electrical and Electronics Engineers Inc.
Sider922-925
Antal sider4
ISBN (Elektronisk)9781424479290
DOI
StatusUdgivet - 2 nov. 2014
Begivenhed2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014 - Chicago, USA
Varighed: 26 aug. 201430 aug. 2014

Publikationsserier

Navn2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014

Konference

Konference2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014
Land/OmrådeUSA
ByChicago
Periode26/08/1430/08/14

Fingeraftryk

Udforsk hvilke forskningsemner 'Automatic detection and classification of artifacts in single-channel EEG' indeholder.

Citationsformater