{"title":"用保相量化方法早期检测脑电图信号的癫痫活动","authors":"Sylmarie Dávila-Montero, E. Ashoori, A. Mason","doi":"10.1109/BIOCAS.2018.8584766","DOIUrl":null,"url":null,"abstract":"This paper demonstrates the use of a data decimation method, called phase-preserving quantization (PPQ), for early seizure prediction. PPQ consists of a) amplifying and filtering the neural signals around the frequency band of interest, and b) compressing the filtered signal using a 1-bit quantizer with a 0-V single-threshold decision. The ability of PPQ to retain phase information and predict seizure events while compressing the signal resolution to a single bit is demonstrated using electroencephalography (EEG) recordings from the Children's Hospital Boston-MIT (CHB-MIT) EEG database. Results show 97% accuracy when calculating synchrony values using PPQ, which is an improvement of 7% when compared to previously published results. The presented improved method enables the early detection of seizure events, resulting in a decrease in phase synchrony computation time while allowing an increase in the number of recording channels that can be screened when using EEG.","PeriodicalId":259162,"journal":{"name":"2018 IEEE Biomedical Circuits and Systems Conference (BioCAS)","volume":"68 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Early Detection of Epileptic Activity on EEG Signals using Phase-Preserving Quantization Method\",\"authors\":\"Sylmarie Dávila-Montero, E. Ashoori, A. Mason\",\"doi\":\"10.1109/BIOCAS.2018.8584766\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper demonstrates the use of a data decimation method, called phase-preserving quantization (PPQ), for early seizure prediction. PPQ consists of a) amplifying and filtering the neural signals around the frequency band of interest, and b) compressing the filtered signal using a 1-bit quantizer with a 0-V single-threshold decision. The ability of PPQ to retain phase information and predict seizure events while compressing the signal resolution to a single bit is demonstrated using electroencephalography (EEG) recordings from the Children's Hospital Boston-MIT (CHB-MIT) EEG database. Results show 97% accuracy when calculating synchrony values using PPQ, which is an improvement of 7% when compared to previously published results. The presented improved method enables the early detection of seizure events, resulting in a decrease in phase synchrony computation time while allowing an increase in the number of recording channels that can be screened when using EEG.\",\"PeriodicalId\":259162,\"journal\":{\"name\":\"2018 IEEE Biomedical Circuits and Systems Conference (BioCAS)\",\"volume\":\"68 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE Biomedical Circuits and Systems Conference (BioCAS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/BIOCAS.2018.8584766\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE Biomedical Circuits and Systems Conference (BioCAS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BIOCAS.2018.8584766","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Early Detection of Epileptic Activity on EEG Signals using Phase-Preserving Quantization Method
This paper demonstrates the use of a data decimation method, called phase-preserving quantization (PPQ), for early seizure prediction. PPQ consists of a) amplifying and filtering the neural signals around the frequency band of interest, and b) compressing the filtered signal using a 1-bit quantizer with a 0-V single-threshold decision. The ability of PPQ to retain phase information and predict seizure events while compressing the signal resolution to a single bit is demonstrated using electroencephalography (EEG) recordings from the Children's Hospital Boston-MIT (CHB-MIT) EEG database. Results show 97% accuracy when calculating synchrony values using PPQ, which is an improvement of 7% when compared to previously published results. The presented improved method enables the early detection of seizure events, resulting in a decrease in phase synchrony computation time while allowing an increase in the number of recording channels that can be screened when using EEG.