M. Suchocki, A. Dobrowolski, E. Majda-Zdancewicz, K. Tomczykiewicz
{"title":"基于小波分解和SVM网络的听觉电位触发分类","authors":"M. Suchocki, A. Dobrowolski, E. Majda-Zdancewicz, K. Tomczykiewicz","doi":"10.5604/12345865.1186236","DOIUrl":null,"url":null,"abstract":"For electrophysiological hearing assessment and diagnosis of brain stem lesions, the most often used are auditory brainstem evoked potentials of short latency. They are characterized by successively arranged maxima as a function of time, called waves. Morphology of the course, in particular, the timing and amplitude of each wave, allow a neurologist to make diagnose, what is not an easy task. a neurologist should be experienced, concentrated, and should have very good perception. in order to support his diagnostic process, the authors have developed an algorithm implementing the automated classification of auditory evoked potentials to the group of pathological and physiological cases, the sensitivity and specificity determined for an independent test group (of 50 cases) of respectively 84% and 88%.","PeriodicalId":9068,"journal":{"name":"Biuletyn Wojskowej Akademii Technicznej","volume":"64 1","pages":"117-129"},"PeriodicalIF":0.0000,"publicationDate":"2015-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Klasyfikacja słuchowych potencjałów wywołanych w oparciu o dekompozycję falkową i sieć SVM\",\"authors\":\"M. Suchocki, A. Dobrowolski, E. Majda-Zdancewicz, K. Tomczykiewicz\",\"doi\":\"10.5604/12345865.1186236\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"For electrophysiological hearing assessment and diagnosis of brain stem lesions, the most often used are auditory brainstem evoked potentials of short latency. They are characterized by successively arranged maxima as a function of time, called waves. Morphology of the course, in particular, the timing and amplitude of each wave, allow a neurologist to make diagnose, what is not an easy task. a neurologist should be experienced, concentrated, and should have very good perception. in order to support his diagnostic process, the authors have developed an algorithm implementing the automated classification of auditory evoked potentials to the group of pathological and physiological cases, the sensitivity and specificity determined for an independent test group (of 50 cases) of respectively 84% and 88%.\",\"PeriodicalId\":9068,\"journal\":{\"name\":\"Biuletyn Wojskowej Akademii Technicznej\",\"volume\":\"64 1\",\"pages\":\"117-129\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-12-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Biuletyn Wojskowej Akademii Technicznej\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5604/12345865.1186236\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Biuletyn Wojskowej Akademii Technicznej","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5604/12345865.1186236","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Klasyfikacja słuchowych potencjałów wywołanych w oparciu o dekompozycję falkową i sieć SVM
For electrophysiological hearing assessment and diagnosis of brain stem lesions, the most often used are auditory brainstem evoked potentials of short latency. They are characterized by successively arranged maxima as a function of time, called waves. Morphology of the course, in particular, the timing and amplitude of each wave, allow a neurologist to make diagnose, what is not an easy task. a neurologist should be experienced, concentrated, and should have very good perception. in order to support his diagnostic process, the authors have developed an algorithm implementing the automated classification of auditory evoked potentials to the group of pathological and physiological cases, the sensitivity and specificity determined for an independent test group (of 50 cases) of respectively 84% and 88%.