{"title":"The design of the patient's room facilities controller using an eye blink","authors":"I. Zaeni, A. Wibawa, M. Ashar","doi":"10.1109/ICEEIE.2017.8328768","DOIUrl":null,"url":null,"abstract":"This study proposed a design to control patient room facilities using eye blink. The room facilities consisted of moving the bed backrest upward, moving the bed backrest downward, switch the fan on/off and switch the light on/off. Four icons representing four commands appear on the screen sequentially. The subject electroencephalograph (EEG) signals were acquired from the prefrontal region. Attention and eye blink used as input for the decision system. The attention level was acquired from the EEG headset, while the eye blink was detected from the filtered raw EEG signal. The low pass filter and peak amplitude were used to detect the eye blink from EEG signal. The decision is made if eye blink and attention level are higher than the threshold. The command that chosen is the icon that appears when the decision is made. Based on the experiment, the average accuracy of the system is 89.79% which verify that the system can be used to help people with ALS to control their room facilities.","PeriodicalId":304532,"journal":{"name":"2017 5th International Conference on Electrical, Electronics and Information Engineering (ICEEIE)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 5th International Conference on Electrical, Electronics and Information Engineering (ICEEIE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICEEIE.2017.8328768","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
This study proposed a design to control patient room facilities using eye blink. The room facilities consisted of moving the bed backrest upward, moving the bed backrest downward, switch the fan on/off and switch the light on/off. Four icons representing four commands appear on the screen sequentially. The subject electroencephalograph (EEG) signals were acquired from the prefrontal region. Attention and eye blink used as input for the decision system. The attention level was acquired from the EEG headset, while the eye blink was detected from the filtered raw EEG signal. The low pass filter and peak amplitude were used to detect the eye blink from EEG signal. The decision is made if eye blink and attention level are higher than the threshold. The command that chosen is the icon that appears when the decision is made. Based on the experiment, the average accuracy of the system is 89.79% which verify that the system can be used to help people with ALS to control their room facilities.