G. Q. Mamani, F. Fraga, Guilherme Tavares, E. Johns, N. Phillips
{"title":"基于脑电图的工作记忆任务生物标志物对阿尔茨海默病和轻度认知障碍的早期诊断","authors":"G. Q. Mamani, F. Fraga, Guilherme Tavares, E. Johns, N. Phillips","doi":"10.1109/HIC.2017.8227628","DOIUrl":null,"url":null,"abstract":"Alzheimer's Disease (AD) is a neurodegenerative syndrome affecting millions of people worldwide. Also, individuals with mild cognitive impairment (MCI) are in a group of risk that should be followed and treated since there is a high probability of evolution to AD. In this study we carried out an Event-Related Potential (ERP) analysis on patient and control groups from 32-channel EEG recorded during N-back working memory (WM) tasks with the aim of finding an ERP-based biomarker for early diagnosis of both AD and MCI. Participants were 15 AD patients, 20 individuals diagnosed with MCI and 26 age-matched healthy elderly (HE) controls. Subjects underwent a three-level visual N-back task with ascending memory load difficulty. Nonparametric Kruskal-Wallis tests with cluster correction and 5% significance level were used for statistical analysis. A considerable amount of significant differences between patient and control groups were found in the ERP during execution of the WM tasks, predominantly in fronto-centro-parietal electrodes. Such results are promising in the direction of achieving an early EEG-based diagnosis of MCI and AD.","PeriodicalId":120815,"journal":{"name":"2017 IEEE Healthcare Innovations and Point of Care Technologies (HI-POCT)","volume":"274 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":"{\"title\":\"EEG-based biomarkers on working memory tasks for early diagnosis of Alzheimer's disease and mild cognitive impairment\",\"authors\":\"G. Q. Mamani, F. Fraga, Guilherme Tavares, E. Johns, N. Phillips\",\"doi\":\"10.1109/HIC.2017.8227628\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Alzheimer's Disease (AD) is a neurodegenerative syndrome affecting millions of people worldwide. Also, individuals with mild cognitive impairment (MCI) are in a group of risk that should be followed and treated since there is a high probability of evolution to AD. In this study we carried out an Event-Related Potential (ERP) analysis on patient and control groups from 32-channel EEG recorded during N-back working memory (WM) tasks with the aim of finding an ERP-based biomarker for early diagnosis of both AD and MCI. Participants were 15 AD patients, 20 individuals diagnosed with MCI and 26 age-matched healthy elderly (HE) controls. Subjects underwent a three-level visual N-back task with ascending memory load difficulty. Nonparametric Kruskal-Wallis tests with cluster correction and 5% significance level were used for statistical analysis. A considerable amount of significant differences between patient and control groups were found in the ERP during execution of the WM tasks, predominantly in fronto-centro-parietal electrodes. Such results are promising in the direction of achieving an early EEG-based diagnosis of MCI and AD.\",\"PeriodicalId\":120815,\"journal\":{\"name\":\"2017 IEEE Healthcare Innovations and Point of Care Technologies (HI-POCT)\",\"volume\":\"274 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"12\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 IEEE Healthcare Innovations and Point of Care Technologies (HI-POCT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/HIC.2017.8227628\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE Healthcare Innovations and Point of Care Technologies (HI-POCT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HIC.2017.8227628","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
EEG-based biomarkers on working memory tasks for early diagnosis of Alzheimer's disease and mild cognitive impairment
Alzheimer's Disease (AD) is a neurodegenerative syndrome affecting millions of people worldwide. Also, individuals with mild cognitive impairment (MCI) are in a group of risk that should be followed and treated since there is a high probability of evolution to AD. In this study we carried out an Event-Related Potential (ERP) analysis on patient and control groups from 32-channel EEG recorded during N-back working memory (WM) tasks with the aim of finding an ERP-based biomarker for early diagnosis of both AD and MCI. Participants were 15 AD patients, 20 individuals diagnosed with MCI and 26 age-matched healthy elderly (HE) controls. Subjects underwent a three-level visual N-back task with ascending memory load difficulty. Nonparametric Kruskal-Wallis tests with cluster correction and 5% significance level were used for statistical analysis. A considerable amount of significant differences between patient and control groups were found in the ERP during execution of the WM tasks, predominantly in fronto-centro-parietal electrodes. Such results are promising in the direction of achieving an early EEG-based diagnosis of MCI and AD.