EEG signalsShort-time Fourier TransformSpectrogramsFeature ExtractionSeizure ClassificationIdentification of EEG signals is currently an open problem where performance analysis in terms of accuracy is relevant in several fields, such as biomedicine and brain computer interfaces. Nevertheless, performance depends...
how to extract eeg features using matlab 댓글 수: 1 Yuen2024년 6월 6일 Hi, How is everything going on with your masters? I'm doing my master project and requires feature extraction of eeg signals as well. I was hoping if you could share...
Shanshan ChenSpringer, Berlin, HeidelbergThe feature extraction method of EEG signals based on degree distribution of complex networks from nonlinear time series. Fenglin Wang,Qingfang Meng,Weidong Zhou. Lecture Notes in Computer Science . 2013
feature extraction 摘要 The method of common spatial patterns (CSP) is an effective feature extractor for representing electroencephalogram (EEG) signals with the purpose of classification in brain computer interfaces (BCIs). However, it has two apparent demerits mainly about the estimation of covariance...
Sleep stages classification one of the essential factors concerning sleep disorder diagnoses, which can contribute to many functional disease treatments or prevent the primary cognitive risks in daily activities. In this study, A novel method of mapping EEG signals to music is proposed to classify sle...
The extraction methodology of the significant features from the signals is one of the most important pre-requisite steps for EEG signal classification. Common spatial pattern (CSP) is a widely used feature extraction method for EEG signal but with a lacking of failing to maintain discriminative feat...
Finally, long short-term memory(LSTM) deep neural networks are used to classify EEG data. The alpha and beta waves are considered in this paper. For pre-processing and feature extractions of EEG fundamental approaches are considered to prove the utility of LSTM DNN. The results are obtained ...
In response to the current issues of one-sided effective feature extraction and low classification accuracy in multi-class motor imagery recognition, this study proposes an Electroencephalogram (EEG) signal recognition method based on multi-domain featur
In this respect, in the present study for epileptic seizure detection in patients with absence seizures (petit mal), the WT was used for feature extraction from the EEG signals belonging to the normal and the patient with absence seizure. Wavelet is an effective time–frequency analysis tool ...
Electroencephalography (EEG) signals collected from human brains have generally been used to diagnose diseases. Moreover, EEG signals can be used in severa