{"title":"Protocol for Controlling Fan Speed in Real Time via Brain Waves","authors":"M. A. Mazlan, W. Mansor, A. Z. Ahmad Zainuddin","doi":"10.1109/ISCAIE.2019.8743948","DOIUrl":null,"url":null,"abstract":"Assistive technology that does not require the use of hands is very useful for disabled people and senior citizens. This paper describes the protocol for controlling the fan speed in real time using EEG. Eye blinks detected from EEG signal were used to represent the intention to control the fan speed. The acquisition of the EEG signal in real time was carried out using two frames and buffer. The fan speed was controlled by detecting the eye blink event in the EEG signal and transferring the control signal to the microcontroller. The algorithm has managed to control the fan speed according to the numbers of eye blink detected.","PeriodicalId":369098,"journal":{"name":"2019 IEEE 9th Symposium on Computer Applications & Industrial Electronics (ISCAIE)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE 9th Symposium on Computer Applications & Industrial Electronics (ISCAIE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISCAIE.2019.8743948","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Assistive technology that does not require the use of hands is very useful for disabled people and senior citizens. This paper describes the protocol for controlling the fan speed in real time using EEG. Eye blinks detected from EEG signal were used to represent the intention to control the fan speed. The acquisition of the EEG signal in real time was carried out using two frames and buffer. The fan speed was controlled by detecting the eye blink event in the EEG signal and transferring the control signal to the microcontroller. The algorithm has managed to control the fan speed according to the numbers of eye blink detected.