Title
Assessing NeuroSky's Usability to Detect Attention Levels in an Assessment Exercise
Abstract
This paper presents the results of a usability evaluation of the NeuroSky's MindSet (MS). Until recently most Brain Computer Interfaces (BCI) have been designed for clinical and research purposes partly due to their size and complexity. However, a new generation of consumer-oriented BCI has appeared for the video game industry. The MS, a headset with a single electrode, is based on electro-encephalogram readings (EEG) capturing faint electrical signals generated by neural activity. The electrical signal across the electrode is measured to determine levels of attention (based on Alpha waveforms) and then translated into binary data. This paper presents the results of an evaluation to assess the usability of the MS by defining a model of attention to fuse attention signals with user-generated data in a Second Life assessment exercise. The results of this evaluation suggest that the MS provides accurate readings regarding attention, since there is a positive correlation between measured and self-reported attention levels. The results also suggest there are some usability and technical problems with its operation. Future research is presented consisting of the definition a standardized reading methodology and an algorithm to level out the natural fluctuation of users' attention levels if they are to be used as inputs.
Year
DOI
Venue
2009
10.1007/978-3-642-02574-7_17
HCI (1)
Keywords
Field
DocType
detect attention levels,consumer-oriented bci,research purpose,fuse attention signal,electrical signal,attention level,self-reported attention level,binary data,faint electrical signal,assessing neurosky,assessment exercise,usability evaluation,brain computer interface
Headset,Mindset,Heuristic evaluation,Computer science,Usability,Brain–computer interface,Human–computer interaction,Cognitive walkthrough,Binary data,Multimedia,Electroencephalography
Conference
Volume
ISSN
Citations 
5610
0302-9743
44
PageRank 
References 
Authors
3.49
5
7