Literature DB >> 19622432

Time-frequency phase analysis of ictal EEG recordings with the S-transform.

C Robert Pinnegar1, Houman Khosravani, Paolo Federico.   

Abstract

The calculation and visualization of temporal and phase information in the brain, such as during cognitive processes and epileptiform activity, is an important tool in EEG-based studies of physiological brain activation. To this end, we present a technique that estimates the phase and time offsets between different channels in EEG recordings of seizure activity. The offset information is visually combined with amplitude information to emphasize the most significant signal features. The estimates of phase and time offset are derived from the S-transform, a time-frequency representation that is similar to a windowed Fourier transform, but with a wavelet-like, scalable window. The phase offsets are obtained from the differences between phase spectra of S-transforms of different traces, and the time offsets are then obtained from the frequency-domain gradients of the phase offsets. This is analogous to the link between frequency "phase ramping" and time translation in ordinary Fourier analysis. In this paper, we present a synthetic example to help describe the method, and then show ictal EEG recordings from two human subjects. The differences between the recording times of spike-wave discharges at different electrodes exhibit behavior that is strongly dependent on time and frequency.

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Year:  2009        PMID: 19622432     DOI: 10.1109/TBME.2009.2026735

Source DB:  PubMed          Journal:  IEEE Trans Biomed Eng        ISSN: 0018-9294            Impact factor:   4.538


  3 in total

1.  Classification of Two Class Motor Imagery Tasks Using Hybrid GA-PSO Based K-Means Clustering.

Authors:  Purnendu Tiwari; Subhojit Ghosh; Rakesh Kumar Sinha
Journal:  Comput Intell Neurosci       Date:  2015-04-20

2.  Early ictal recruitment of midline thalamus in mesial temporal lobe epilepsy.

Authors:  Andrew Romeo; Alexandra T Issa Roach; Emilia Toth; Ganne Chaitanya; Adeel Ilyas; Kristen O Riley; Sandipan Pati
Journal:  Ann Clin Transl Neurol       Date:  2019-07-05       Impact factor: 4.511

3.  SEMG Feature Extraction Based on StockwellTransform Improves Hand MovementRecognition Accuracy.

Authors:  Haotian She; Jinying Zhu; Ye Tian; Yanchao Wang; Hiroshi Yokoi; Qiang Huang
Journal:  Sensors (Basel)       Date:  2019-10-14       Impact factor: 3.576

  3 in total

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