Multi-Scale Representation of Sleep Electroencephalogram Events for Healthy Adult Using Wavelet Transformation

Feng, Qiansheng; Zhang, Meiyun; Zhang, Ying; Jiang, Nan; Zhang, Jingling

doi:10.1166/jmihi.2017.2117

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Recognition Of Obbb Using Time-frequency Analysis1

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2021

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“…Today, one of the generally accepted nonlinear methods for processing and detecting of oscillatory activity in biomedical signals is continuous wavelet transformation (CWT) [39][40][41]. CWT is sufficiently resistant to abrupt changes in the frequency composition of the analyzed experimental signals, which makes it possible to adequately analyze rather short time intervals of highly nonstationary signals.…”

Section: Recognition Of Obbb Using Time-frequency Analysismentioning

confidence: 99%

Non-invasive analysis of blood-brain barrier permeability based on wavelet and machine learning approaches

Semenova,

Segreev,

Slepnev

et al. 2021

Preprint

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The blood-brain barrier plays a decisive role in protecting the brain from toxins and pathogens. The ability to analyze the BBB opening (OBBB) is crucial for the treatment of many brain diseases, but it is very difficult to noninvasively monitor OBBB. In this paper we analyse the EEG series of healthy rats in free behaviour and after music-induced OBBB. The research is performed using two completely different methods based on wavelet analysis and machine learning approach. Both methods enable us to recognize OBBB and are in a good agreement with each other. The comparative analysis was carried out using F-measures and ROC-curves.

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Section: Recognition Of Obbb Using Time-frequency Analysismentioning

confidence: 99%