{"title":"利用脑电图生物信号变化检测重症监护病房中的谵妄症","authors":"Taixian Jin, Huiying Jin, Sun-Mi Lee","doi":"10.1097/JNN.0000000000000639","DOIUrl":null,"url":null,"abstract":"<p><strong>Abstract: </strong>BACKGROUND: Biosignal data acquired during quantitative electroencephalography (QEEG) research may ultimately be used to develop algorithms for more accurate detection of delirium. This study investigates the biosignal changes during delirium states by using the QEEG data of patients in a medical intensive care unit. METHODS: This observational study was conducted between September 2018 and December 2019 at a tertiary hospital in South Korea. Delirium was measured using the Korean version of Confusion Assessment Method for the Intensive Care Unit in intensive care unit patients. Quantitative EEG measurements were recorded for 20 minutes in a natural state without external treatment or stimuli, and QEEG data measured in the centroparietal and parietal regions with eyes open were selected for analysis. Power spectrum analysis with a 5-minute epoch was conducted on the selected 65 cases. RESULTS: QEEG changes in the presence of delirium indicated that alpha, beta, gamma, and spectral edge frequency 50% waves showed significantly lower absolute power spectra than the corresponding findings in the absence of delirium. Brain-mapping results showed that these brain waves were inactivated in delirious states. CONCLUSION: QEEG assessments can potentially detect the changes in the centroparietal and parietal regions of delirium patients. QEEG changes, including lower power spectra of alpha, beta, and gamma waves, and spectral edge frequency 50%, can be successfully used to distinguish delirium from the absence of delirium.</p>","PeriodicalId":50113,"journal":{"name":"Journal of Neuroscience Nursing","volume":"54 2","pages":"96-101"},"PeriodicalIF":1.5000,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Using Electroencephalogram Biosignal Changes for Delirium Detection in Intensive Care Units.\",\"authors\":\"Taixian Jin, Huiying Jin, Sun-Mi Lee\",\"doi\":\"10.1097/JNN.0000000000000639\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Abstract: </strong>BACKGROUND: Biosignal data acquired during quantitative electroencephalography (QEEG) research may ultimately be used to develop algorithms for more accurate detection of delirium. This study investigates the biosignal changes during delirium states by using the QEEG data of patients in a medical intensive care unit. METHODS: This observational study was conducted between September 2018 and December 2019 at a tertiary hospital in South Korea. Delirium was measured using the Korean version of Confusion Assessment Method for the Intensive Care Unit in intensive care unit patients. Quantitative EEG measurements were recorded for 20 minutes in a natural state without external treatment or stimuli, and QEEG data measured in the centroparietal and parietal regions with eyes open were selected for analysis. Power spectrum analysis with a 5-minute epoch was conducted on the selected 65 cases. RESULTS: QEEG changes in the presence of delirium indicated that alpha, beta, gamma, and spectral edge frequency 50% waves showed significantly lower absolute power spectra than the corresponding findings in the absence of delirium. Brain-mapping results showed that these brain waves were inactivated in delirious states. CONCLUSION: QEEG assessments can potentially detect the changes in the centroparietal and parietal regions of delirium patients. QEEG changes, including lower power spectra of alpha, beta, and gamma waves, and spectral edge frequency 50%, can be successfully used to distinguish delirium from the absence of delirium.</p>\",\"PeriodicalId\":50113,\"journal\":{\"name\":\"Journal of Neuroscience Nursing\",\"volume\":\"54 2\",\"pages\":\"96-101\"},\"PeriodicalIF\":1.5000,\"publicationDate\":\"2022-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Neuroscience Nursing\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1097/JNN.0000000000000639\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"CLINICAL NEUROLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Neuroscience Nursing","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1097/JNN.0000000000000639","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"CLINICAL NEUROLOGY","Score":null,"Total":0}
Using Electroencephalogram Biosignal Changes for Delirium Detection in Intensive Care Units.
Abstract: BACKGROUND: Biosignal data acquired during quantitative electroencephalography (QEEG) research may ultimately be used to develop algorithms for more accurate detection of delirium. This study investigates the biosignal changes during delirium states by using the QEEG data of patients in a medical intensive care unit. METHODS: This observational study was conducted between September 2018 and December 2019 at a tertiary hospital in South Korea. Delirium was measured using the Korean version of Confusion Assessment Method for the Intensive Care Unit in intensive care unit patients. Quantitative EEG measurements were recorded for 20 minutes in a natural state without external treatment or stimuli, and QEEG data measured in the centroparietal and parietal regions with eyes open were selected for analysis. Power spectrum analysis with a 5-minute epoch was conducted on the selected 65 cases. RESULTS: QEEG changes in the presence of delirium indicated that alpha, beta, gamma, and spectral edge frequency 50% waves showed significantly lower absolute power spectra than the corresponding findings in the absence of delirium. Brain-mapping results showed that these brain waves were inactivated in delirious states. CONCLUSION: QEEG assessments can potentially detect the changes in the centroparietal and parietal regions of delirium patients. QEEG changes, including lower power spectra of alpha, beta, and gamma waves, and spectral edge frequency 50%, can be successfully used to distinguish delirium from the absence of delirium.
期刊介绍:
The Journal of Neuroscience Nursing (JNN), the official journal of the American Association of Neuroscience Nurses, contains original articles on advances in neurosurgical and neurological techniques as they affect nursing care, theory and research, as well as commentary on the roles of the neuroscience nurse in the health care team.
The journal provides information to nurses and health care professionals working in diverse areas of neuroscience patient care such as multi-specialty and neuroscience intensive care units, general neuroscience units, combination units (neuro/ortho, neuromuscular/rehabilitation, neuropsychiatry, neurogerontology), rehabilitation units, medical-surgical units, pediatric units, emergency and trauma departments, and surgery. The information is applicable to professionals working in clinical, research, administrative, and educational settings.