dc.contributor.author | Çalışkan, Abdullah | |
dc.contributor.author | Badem, Hasan | |
dc.contributor.author | Çil, Zeynel Abidin | |
dc.date.accessioned | 2020-05-24T14:24:18Z | |
dc.date.available | 2020-05-24T14:24:18Z | |
dc.date.issued | 2019 | |
dc.identifier.citation | Çalışkan, A., Badem, H., Çil, Z.A. (2019).Determination of window size and sliding interval for EMG signals by using genetic algorithm [Article@EMG sinyalleri için pencere genişliǧinin ve kaydirma miktarinin genetik algoritmayla
belirlenmesi] TIPTEKNO 2019 - Tip Teknolojileri Kongresi, art. no. 8895122.https://doi.org/10.1109/TIPTEKNO.2019.8895122 | en_US |
dc.identifier.isbn | 9781728124209 | |
dc.identifier.uri | https://doi.org/10.1109/TIPTEKNO.2019.8895122 | |
dc.identifier.uri | https://hdl.handle.net/20.500.12508/1062 | |
dc.description | 2019 Medical Technologies Congress, TIPTEKNO 2019 -- 3 October 2019 through 5 October 2019 -- -- 154293 | en_US |
dc.description.abstract | The selection of window size and sliding interval are one of the important problems encountered in Electromyography (EMG) signal processing. However, there exist a few methods to determine the window size and sliding interval for EMG signal classification problems. In this paper, a new method is proposed to optimize the window size and sliding interval for EMG signals by using Genetic Algorithm. Experimental results on a EMG data set show that the proposed method improve the performance of a traditional classifier in terms of classification accuracy. © 2019 IEEE. | en_US |
dc.language.iso | eng | en_US |
dc.publisher | Institute of Electrical and Electronics Engineers Inc. | en_US |
dc.relation.isversionof | 10.1109/TIPTEKNO.2019.8895122 | en_US |
dc.rights | info:eu-repo/semantics/closedAccess | en_US |
dc.subject | Electromyography | en_US |
dc.subject | Genetic algorithm | en_US |
dc.subject | Sliding interval | en_US |
dc.subject | Window size | en_US |
dc.subject.classification | Electromyography | Artificial Limb | Hand Gesture Recognition | en_US |
dc.subject.classification | Engineering, Biomedical | en_US |
dc.subject.other | Biomedical engineering | en_US |
dc.subject.other | Classification (of information) | en_US |
dc.subject.other | Electromyography | en_US |
dc.subject.other | Genetic algorithms | en_US |
dc.subject.other | Classification accuracy | en_US |
dc.subject.other | Data set | en_US |
dc.subject.other | EMG signal | en_US |
dc.subject.other | Emg signal classifications | en_US |
dc.subject.other | Sliding interval | en_US |
dc.subject.other | Window Size | en_US |
dc.subject.other | Biomedical signal processing | en_US |
dc.subject.other | Classification | en_US |
dc.title | Determination of window size and sliding interval for EMG signals by using genetic algorithm | en_US |
dc.title.alternative | EMG sinyalleri için pencere genişli?inin ve kaydirma miktarinin genetik algoritmayla belirlenmesi | en_US |
dc.type | conferenceObject | en_US |
dc.relation.journal | TIPTEKNO 2019 - Tip Teknolojileri Kongresi | en_US |
dc.contributor.department | İskenderun Teknik Üniversitesi | en_US |
dc.contributor.department | Mühendislik ve Doğa Bilimleri Fakültesi -- Biyomedikal Mühendisliği Bölümü | en_US |
dc.relation.publicationcategory | Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı | en_US |
dc.contributor.isteauthor | Çalışkan, Abdullah | en_US |
dc.relation.index | Web of Science Core Collection - Conference Proceedings Citation Index- Science | en_US |
dc.relation.index | Web of Science - Scopus | en_US |