Informed Cooperative Adaptive Line Enhancer for Detection of Spindles from Sleep EEG

Sanei, Saeid; Lee, K. M. Tracey

doi:10.1109/icdsp.2018.8631833

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Cooperative Adaptive Line Enhancer1

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2020

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“…Nevertheless, the main hypothesis in this work is that, during the above different brain states/activities, the connectivity patterns between various brain zones vary considerably. Hence, the brain connectivity parameters can be good estimates of the combination weights for a cooperative ALE (CoALE) introduced in [13] to best estimate the desired waveform and classify the above waveforms. For a CoALE the target signal in equation 2is replaced with the shifted input signal, i.e.,…”

Section: Cooperative Adaptive Line Enhancermentioning

confidence: 99%

Eeg Connectivity - Informed Cooperative Adaptive Line Enhancer for Recognition of Brain State

Sanei

Took

Jarchi

et al. 2020

ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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Bursts of sleep spindles and paroxysmal fast brain activity waveforms have frequency overlap whilst generally, paroxysmal waveforms have shorter duration than spindles. Both resemble bursts of normal alpha activity during short rests while awake with closed eyes. In this paper, it is shown that for a proposed cooperative adaptive line enhancer, which can both detect and separate such periodic bursts, the combination weights are consistently different from each other. The outcome suggests that for accurate modelling of the brain neuro-generators, the brain connectivity has to be precisely estimated and plugged into the adaptation process.

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Section: Cooperative Adaptive Line Enhancermentioning

confidence: 99%