Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Sudip Modak"'
Publikováno v:
2022 IEEE 6th International Conference on Condition Assessment Techniques in Electrical Systems (CATCON).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::35b9865e880819c86fb4d0fab845ee90
https://doi.org/10.1109/catcon56237.2022.10077641
https://doi.org/10.1109/catcon56237.2022.10077641
Publikováno v:
IEEE Sensors Journal. 21:23335-23343
Accurate detection of focal seizure area through EEG screening is important to remove the affected regions of human brain, prior to surgery. Considering the aforesaid fact, in this paper, we propose a novel approach for automated detection and classi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ca75c69ac8f084aac163e12bf6e5038b
https://doi.org/10.1109/jsen.2021.3111102
https://doi.org/10.1109/jsen.2021.3111102
Publikováno v:
IEEE Sensors Letters. 4:1-4
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4a7abe0431778847f87a5e8538fcf298
https://doi.org/10.1109/lsens.2020.3002991
https://doi.org/10.1109/lsens.2020.3002991
Publikováno v:
IEEE Sensors Letters. 4:1-4
In this letter, a novel neuromuscular disease detection framework employing cross-wavelet spectrum (XWS) based deep feature extraction is proposed. In joint time–frequency analysis, cross-wavelet transform (XWT) is an important tool which provides
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bb2e38d52206051c3fb0c0ca1a1909c6
https://doi.org/10.1109/lsens.2020.2992452
https://doi.org/10.1109/lsens.2020.2992452
In this chapter, we propose a novel technique for the detection of epileptic electroencephalogram (EEG) signals using sequential visibility graph (VG) motifs. VG is a technique, which converts any time-domain signal to an undirected and binary graph
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f37a73ecfed2da0749bd52a78380cafe
https://doi.org/10.1201/9781003121152-3
https://doi.org/10.1201/9781003121152-3
Publikováno v:
IEEE journal of biomedical and health informatics. 25(3)
In this contribution, we propose a novel neuromuscular disease detection framework employing weighted visibility graph (WVG) aided analysis of electromyography signals. WVG converts a time series into an undirected graph, while preserving the signal
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ceb4268161afbb5170a0c30e53e981aa
https://pubmed.ncbi.nlm.nih.gov/32750934
https://pubmed.ncbi.nlm.nih.gov/32750934
Publikováno v:
EMBC
In this paper, a deep learning framework for detection and classification of EMG signals for diagnosis of neuromuscular disorders is proposed employing cross wavelet transform. Cross wavelet transform which is a modification of continuous wavelet tra
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fc747edc4174488e769028e24c364f48
https://doi.org/10.1109/embc44109.2020.9176464
https://doi.org/10.1109/embc44109.2020.9176464
Autor:
Kaniska Samanta, Sayantan Dey, Ronjoy Bhowmik, Sayanjit Singha Roy, Sudip Modak, Soumya Chatterjee, Rohit Bose
Publikováno v:
2020 International Conference on Computer, Electrical & Communication Engineering (ICCECE).
Focal epilepsy is a neurological disease, stem from a specific region of human brain, which is known as epileptogenic focus. Diagnosis of focal seizures is usually done using EEG analysis. In this paper, a novel technique to discriminate EEG signals
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::231cc3c1d4c3c984158a301358c3a440
https://doi.org/10.1109/iccece48148.2020.9223096
https://doi.org/10.1109/iccece48148.2020.9223096