A new combination: scale-space filtering of projected brain activities.
In the present study, well known scale-space filtering (SSF) algorithm is used in combination with a linear mapping approach (LMA) to obtain clear auditory evoked potential (EP) waveform. The proposed combination involves two sequential steps: At first, the EEG noise level is reduced from -5 to 0 dB...
| Publicado en: | Medical & Biological Engineering & Computing Vol. 47; no. 4; pp. 435 - 441 |
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| Autores principales: | , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
Apr2009
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=105472859&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 105472859 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01400118 PO0 jtl: Medical & Biological Engineering & Computing issn: 01400118 maglogo: N pubinfo: dt: Apr2009 vid: 47 iid: 4 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 105472859 NLM19205770 2010218364 10.1007/s11517-009-0450-3 NLM19205770 105472859 ppf: 435 ppct: 6 formats: fmt: @attributes: type: P tig: atl: A new combination: scale-space filtering of projected brain activities. aug: au: Aydin S Aydin, Serap affil: Electrical and Electronics Engineering Department, Engineering Faculty, Ondokuz Mayis University, Kurupelit, Samsun, Turkey sug: subj: Electroencephalography Methods Signal Processing, Computer Assisted Adult Algorithms Electricity Evoked Potentials, Auditory Female Male Adult: 19-44 years Female Male ab: In the present study, well known scale-space filtering (SSF) algorithm is used in combination with a linear mapping approach (LMA) to obtain clear auditory evoked potential (EP) waveform. The proposed combination involves two sequential steps: At first, the EEG noise level is reduced from -5 to 0 dB owing to the LMA based on the singular-value-decomposition. In the secondary process, the EEG noise remaining on the projected data is removed by using the SSF. A small number of sweeps are composed as a raw matrix to project the data without using the ensemble averaging at the beginning of the proposed method. Then, single sweeps are individually filtered in wavelet domain by using the SSF in the secondary step. The experimental results show that the SSF can extract the clear single-sweep auditory EP waveform where the LMA is used as a primary filtering. As well, the results indicate that the EP signal and background EEG noise create different wavelet coefficients due to their different characteristics. However, this characteristic difference can be considered to distinguish the EP signal and the EEG noise when the Signal-to-Noise-Ratio is higher than 0 dB. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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