T. R. Shivaraja, K. Chellappan, N. Kamal, R. Remli
{"title":"面向远程监测的移动脑电图个性化设计","authors":"T. R. Shivaraja, K. Chellappan, N. Kamal, R. Remli","doi":"10.1109/IECBES54088.2022.10079507","DOIUrl":null,"url":null,"abstract":"Personalized remote monitoring healthcare devices have begun emerging in the industry over the years, slowly setting a new standard for long term monitoring services. In this study, the researchers are addressing epilepsy. This neurological disorder hinders mobility freedom and may affect humans of any age, often starting in childhood or people over 60 years old. Diagnosing epileptic patients still stands as a challenge due to similar symptoms shown by other medical conditions such as migraines, fainting and panic attacks, often unable to be ruled as epilepsy without detecting seizure. Electroencephalogram (EEG) has proven to be the most helpful procedure for diagnosis of epilepsy. Interictal epileptiform discharges (IED), detected in EEG aids in differentiating epileptic and other nonepileptic episodes. Currently, available EEG devices are often bulky and restricted to be in use of clinical environments, limiting treatment process among epilepsy patients. The aim of this research is to present a personalized mobile EEG device for epilepsy monitoring and management. A customizable dry electrode EEG headset with 16-channel was assembled and configured. A server and an Android based mobile application were also developed to aid in remote monitoring regardless of location and available network. The device was tested and validated for signal reliability by a neurologist at the Neurology Lab of Canselor Tuanku Muhriz Hospital. The proposed device has potential to be solution for numerous limitations in current epilepsy treatment decision and may even be vital in addressing the drawback of recent pandemic. The outcome of the study is expected to boost and improve neurological research and clinical diagnosis in patient monitoring.","PeriodicalId":146681,"journal":{"name":"2022 IEEE-EMBS Conference on Biomedical Engineering and Sciences (IECBES)","volume":"64 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Personalization of a Mobile EEG for Remote Monitoring\",\"authors\":\"T. R. Shivaraja, K. Chellappan, N. Kamal, R. Remli\",\"doi\":\"10.1109/IECBES54088.2022.10079507\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Personalized remote monitoring healthcare devices have begun emerging in the industry over the years, slowly setting a new standard for long term monitoring services. In this study, the researchers are addressing epilepsy. This neurological disorder hinders mobility freedom and may affect humans of any age, often starting in childhood or people over 60 years old. Diagnosing epileptic patients still stands as a challenge due to similar symptoms shown by other medical conditions such as migraines, fainting and panic attacks, often unable to be ruled as epilepsy without detecting seizure. Electroencephalogram (EEG) has proven to be the most helpful procedure for diagnosis of epilepsy. Interictal epileptiform discharges (IED), detected in EEG aids in differentiating epileptic and other nonepileptic episodes. Currently, available EEG devices are often bulky and restricted to be in use of clinical environments, limiting treatment process among epilepsy patients. The aim of this research is to present a personalized mobile EEG device for epilepsy monitoring and management. A customizable dry electrode EEG headset with 16-channel was assembled and configured. A server and an Android based mobile application were also developed to aid in remote monitoring regardless of location and available network. The device was tested and validated for signal reliability by a neurologist at the Neurology Lab of Canselor Tuanku Muhriz Hospital. The proposed device has potential to be solution for numerous limitations in current epilepsy treatment decision and may even be vital in addressing the drawback of recent pandemic. The outcome of the study is expected to boost and improve neurological research and clinical diagnosis in patient monitoring.\",\"PeriodicalId\":146681,\"journal\":{\"name\":\"2022 IEEE-EMBS Conference on Biomedical Engineering and Sciences (IECBES)\",\"volume\":\"64 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-12-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 IEEE-EMBS Conference on Biomedical Engineering and Sciences (IECBES)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IECBES54088.2022.10079507\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE-EMBS Conference on Biomedical Engineering and Sciences (IECBES)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IECBES54088.2022.10079507","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Personalization of a Mobile EEG for Remote Monitoring
Personalized remote monitoring healthcare devices have begun emerging in the industry over the years, slowly setting a new standard for long term monitoring services. In this study, the researchers are addressing epilepsy. This neurological disorder hinders mobility freedom and may affect humans of any age, often starting in childhood or people over 60 years old. Diagnosing epileptic patients still stands as a challenge due to similar symptoms shown by other medical conditions such as migraines, fainting and panic attacks, often unable to be ruled as epilepsy without detecting seizure. Electroencephalogram (EEG) has proven to be the most helpful procedure for diagnosis of epilepsy. Interictal epileptiform discharges (IED), detected in EEG aids in differentiating epileptic and other nonepileptic episodes. Currently, available EEG devices are often bulky and restricted to be in use of clinical environments, limiting treatment process among epilepsy patients. The aim of this research is to present a personalized mobile EEG device for epilepsy monitoring and management. A customizable dry electrode EEG headset with 16-channel was assembled and configured. A server and an Android based mobile application were also developed to aid in remote monitoring regardless of location and available network. The device was tested and validated for signal reliability by a neurologist at the Neurology Lab of Canselor Tuanku Muhriz Hospital. The proposed device has potential to be solution for numerous limitations in current epilepsy treatment decision and may even be vital in addressing the drawback of recent pandemic. The outcome of the study is expected to boost and improve neurological research and clinical diagnosis in patient monitoring.