{"title":"The Feasibility and Effectiveness of P300 Responses using Low Fidelity Equipment in Three Distinctive Environments","authors":"Patrick Schembri, R. Anthony, Mariusz Pelc","doi":"10.5220/0006895000770086","DOIUrl":null,"url":null,"abstract":"In this paper we investigate the viability, practicability and efficacy of eliciting P300 responses based on the P300 speller BCI paradigm (oddball) and the xDAWN algorithm, with five healthy subjects; while using a non-invasive Brain Computer Interface (BCI) based on low fidelity electroencephalographic (EEG) equipment. The experiments were performed in three distinctive environments: lab conditions, mild and controlled user distractions, and real world environment (realistic sound and visual distractions present). Our main contribution is the assessment of the ways and extents to which different degrees of user distraction affect the detection success achievable using low fidelity equipment. Our results demonstrate the applicability of using off-the-shelf equipment as a means to successfully and effectively detect P300 responses, with different degrees of success across the three distinctive types of environment.","PeriodicalId":326453,"journal":{"name":"International Conference on Physiological Computing Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Physiological Computing Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5220/0006895000770086","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
In this paper we investigate the viability, practicability and efficacy of eliciting P300 responses based on the P300 speller BCI paradigm (oddball) and the xDAWN algorithm, with five healthy subjects; while using a non-invasive Brain Computer Interface (BCI) based on low fidelity electroencephalographic (EEG) equipment. The experiments were performed in three distinctive environments: lab conditions, mild and controlled user distractions, and real world environment (realistic sound and visual distractions present). Our main contribution is the assessment of the ways and extents to which different degrees of user distraction affect the detection success achievable using low fidelity equipment. Our results demonstrate the applicability of using off-the-shelf equipment as a means to successfully and effectively detect P300 responses, with different degrees of success across the three distinctive types of environment.