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Moving an on-screen cursor with the Emotiv Insight EEG headset: An evaluation through case studies
Blekinge Institute of Technology, Faculty of Computing, Department of Software Engineering.
Blekinge Institute of Technology, Faculty of Computing, Department of Software Engineering.
2018 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

Today smartphones are everywhere and they ease the lives of millions of people every day. However there are people who, because of various reasons, are unable to receive the benefits of these devices because they are not able to interact with a smartphone in the intended way; using their hands.

In this thesis we investigate an alternative method for interacting with a smartphone; using a commercially available electroencephalography (EEG) headset. EEG is a technique for measuring and recording brain activity, often through the use of sensors placed along the scalp of the user.

We developed a prototype of a brain-computer interface (BCI) for use with android and the Emotiv Insight commercial EEG headset. The prototype allows the user to control an on-screen cursor in one dimension within an android application using the Emotiv Insight.

We performed three case studies with one participant in each. The participants had no prior experience with EEG headsets or BCIs. We had them train to use the Emotiv Insight with our BCI prototype. After the training was completed they performed a series of tests in order to measure their ability to control an on-screen cursor in one dimension. Finally the participants filled out a questionnaire regarding their subjective experiences of using the Emotiv Insight.

These case studies showed the inadequacies of the Emotiv Insight. All three participants had issues with training and using the headset. These issues are reflected in our tests, where 44 out of 45 attempts at moving the cursor to a specific area resulted in a failure. All participants also reported fatigue and headaches during the case studies. We also concluded that the Emotiv Insight provides a poor user experience because of fatigue in longer sessions and the amount of work needed to train the headset.

Place, publisher, year, edition, pages
2018. , p. 39
Keywords [en]
EEG, Emotiv Insight, BCI
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:bth-16307OAI: oai:DiVA.org:bth-16307DiVA, id: diva2:1213634
Subject / course
PA1445 Kandidatkurs i Programvaruteknik
Educational program
PAGPT Software Engineering
Presentation
2018-06-01, 09:15 (English)
Supervisors
Examiners
Available from: 2018-06-07 Created: 2018-06-05 Last updated: 2018-06-07Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
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Output format
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