--- abstract: | Multichannel recordings of the electromagnetic fields emerging from neural currents in the brain generate large amounts of data. Suitable feature extraction methods are, therefore, useful to facilitate the representation and interpretation of the data. Recently developed independent component analysis (ICA) has been shown to be an efficient tool for artifact identification and extraction from electroencephalographic (EEG) and magnetoen- cephalographic (MEG) recordings. In addition, ICA has been ap- plied to the analysis of brain signals evoked by sensory stimuli. This paper reviews our recent results in this field. altloc: - http://www.cis.hut.fi/jaakkos/TBME2000.pdf chapter: ~ commentary: ~ commref: ~ confdates: ~ conference: ~ confloc: ~ contact_email: ~ creators_id: - '' - 4715 - '' - '' - '' creators_name: - family: Vigário given: Ricardo honourific: Dr lineage: '' - family: Särelä given: Jaakko honourific: Mr lineage: '' - family: Jousmäki given: Veikko honourific: Dr lineage: '' - family: Hämäläinen given: Matti honourific: Dr lineage: '' - family: Oja given: Erkki honourific: prof. lineage: '' date: 2000 date_type: published datestamp: 2004-05-24 department: ~ dir: disk0/00/00/36/39 edit_lock_since: ~ edit_lock_until: ~ edit_lock_user: ~ editors_id: [] editors_name: [] eprint_status: archive eprintid: 3639 fileinfo: /style/images/fileicons/application_pdf.png;/3639/1/TBME2000.pdf full_text_status: public importid: ~ institution: ~ isbn: ~ ispublished: pub issn: ~ item_issues_comment: [] item_issues_count: 0 item_issues_description: [] item_issues_id: [] item_issues_reported_by: [] item_issues_resolved_by: [] item_issues_status: [] item_issues_timestamp: [] item_issues_type: [] keywords: "independent component analysis (ICA), blind source separation (BSS), unsupervised learning, electroencephalography (EEG), magnetoencephalography(MEG), artifact removal, auditory evoked field (AEF), somatosensory evoked field (SEF)\n" lastmod: 2011-03-11 08:55:36 latitude: ~ longitude: ~ metadata_visibility: show note: ~ number: 5 pagerange: 589-593 pubdom: FALSE publication: IEEE transactions on biomedical engineering publisher: ~ refereed: TRUE referencetext: ~ relation_type: [] relation_uri: [] reportno: ~ rev_number: 12 series: ~ source: ~ status_changed: 2007-09-12 16:52:32 subjects: - brain-img - comp-sci-stat-model - comp-sci-mach-learn succeeds: ~ suggestions: ~ sword_depositor: ~ sword_slug: ~ thesistype: ~ title: Independent component approach to the analysis of EEG and MEG recordings type: journalp userid: 4715 volume: 47