{"title":"WalkingWizard - 适合日常使用的真正可佩戴脑电图耳机","authors":"Teck Lun Goh, L. Peh","doi":"10.1145/3648106","DOIUrl":null,"url":null,"abstract":"\n Electroencephalography (EEG) provides an opportunity to gain insights to electrocortical activity without the need for invasive technology. While increasingly used in various application areas, EEG headsets tend to be suited only to a laboratory environment due to the long preparation time to don the headset and the need for users to remain stationary. We present our design of a dry, dual-electrodes flexible PCB assembly that realizes accurate sensing in face of practical motion artifacts. Using it, we present WalkingWizard, our prototype dry-electrode EEG baseball cap that can be used under motion in everyday scenarios. We first evaluated its hardware performance by comparing its electrode-scalp impedance and ability to capture alpha rhythm against both wet EEG, and commercially available dry EEG headsets. We then tested WalkingWizard using SSVEP experiments, achieving high classification accuracy of 87% for walking speeds up to 5.0km/hr, beating state-of-the-art. Expanding on WalkingWizard, we integrated all necessary electronic components into a flexible PCB assembly - realizing\n WalkingWizard Integrated\n , in a truly wearable form-factor. Utilizing WalkingWizard Integrated, we demonstrated several applications as proof-of-concept: Classification of SSVEP in VR environment while walking, Real-time acquisition of emotional state of users while moving around the neighbourhood, and Understanding the effect of guided meditation for relaxation.\n","PeriodicalId":72043,"journal":{"name":"ACM transactions on computing for healthcare","volume":"61 ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"WalkingWizard - A truly wearable EEG headset for everyday use\",\"authors\":\"Teck Lun Goh, L. Peh\",\"doi\":\"10.1145/3648106\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\n Electroencephalography (EEG) provides an opportunity to gain insights to electrocortical activity without the need for invasive technology. While increasingly used in various application areas, EEG headsets tend to be suited only to a laboratory environment due to the long preparation time to don the headset and the need for users to remain stationary. We present our design of a dry, dual-electrodes flexible PCB assembly that realizes accurate sensing in face of practical motion artifacts. Using it, we present WalkingWizard, our prototype dry-electrode EEG baseball cap that can be used under motion in everyday scenarios. We first evaluated its hardware performance by comparing its electrode-scalp impedance and ability to capture alpha rhythm against both wet EEG, and commercially available dry EEG headsets. We then tested WalkingWizard using SSVEP experiments, achieving high classification accuracy of 87% for walking speeds up to 5.0km/hr, beating state-of-the-art. Expanding on WalkingWizard, we integrated all necessary electronic components into a flexible PCB assembly - realizing\\n WalkingWizard Integrated\\n , in a truly wearable form-factor. Utilizing WalkingWizard Integrated, we demonstrated several applications as proof-of-concept: Classification of SSVEP in VR environment while walking, Real-time acquisition of emotional state of users while moving around the neighbourhood, and Understanding the effect of guided meditation for relaxation.\\n\",\"PeriodicalId\":72043,\"journal\":{\"name\":\"ACM transactions on computing for healthcare\",\"volume\":\"61 \",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-02-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACM transactions on computing for healthcare\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3648106\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACM transactions on computing for healthcare","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3648106","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
WalkingWizard - A truly wearable EEG headset for everyday use
Electroencephalography (EEG) provides an opportunity to gain insights to electrocortical activity without the need for invasive technology. While increasingly used in various application areas, EEG headsets tend to be suited only to a laboratory environment due to the long preparation time to don the headset and the need for users to remain stationary. We present our design of a dry, dual-electrodes flexible PCB assembly that realizes accurate sensing in face of practical motion artifacts. Using it, we present WalkingWizard, our prototype dry-electrode EEG baseball cap that can be used under motion in everyday scenarios. We first evaluated its hardware performance by comparing its electrode-scalp impedance and ability to capture alpha rhythm against both wet EEG, and commercially available dry EEG headsets. We then tested WalkingWizard using SSVEP experiments, achieving high classification accuracy of 87% for walking speeds up to 5.0km/hr, beating state-of-the-art. Expanding on WalkingWizard, we integrated all necessary electronic components into a flexible PCB assembly - realizing
WalkingWizard Integrated
, in a truly wearable form-factor. Utilizing WalkingWizard Integrated, we demonstrated several applications as proof-of-concept: Classification of SSVEP in VR environment while walking, Real-time acquisition of emotional state of users while moving around the neighbourhood, and Understanding the effect of guided meditation for relaxation.