What's on your mind? Mental task awareness using single electrode brain computer interfaces

Alireza Sahami Shirazi, Mariam Hassib, Niels Henze, Albrecht Schmidt, Kai Steven Kunze

Research output: Chapter in Book/Report/Conference proceedingConference contribution

9 Citations (Scopus)

Abstract

Recognizing and summarizing persons' activities have proven to be effective for increasing self-awareness and enable to improve habits. Reading improves one's language skills and periodic relaxing improves one's health. Recognizing these activities and conveying the time spent would enable to ensure that users read and relax for an adequate time. Most previous attempts in activity recognition deduce mental activities by requiring expensive/bulky hardware or by monitoring behavior from the outside. Not all mental activities can, however, be recognized from the outside. If a person is sleeping, relaxing, or intensively thinks about a problem can hardly be differentiated by observing carried-out reactions. In contrast, we use simple wearable off-the-shelf single electrode brain computer interfaces. These devices have the potential to directly recognize user's mental activities. Through a study with 20 participants, we collect data for five representative activities. We describe the dataset collected and derive potential features. Using a Bayesian classifier we show that reading and relaxing can be recognized with 97% and 79% accuracy. We discuss how sensory tasks associated with different brain lobes can be classified using a single dry electrode BCI.

Original languageEnglish
Title of host publicationProceedings of the 5th Augmented Human International Conference, AH 2014
PublisherAssociation for Computing Machinery
ISBN (Print)9781450327619
DOIs
Publication statusPublished - 2014
Externally publishedYes
Event5th Augmented Human International Conference, AH 2014 - Kobe, Japan
Duration: 2014 Mar 72014 Mar 8

Other

Other5th Augmented Human International Conference, AH 2014
CountryJapan
CityKobe
Period14/3/714/3/8

Fingerprint

Brain computer interface
Electrodes
Conveying
Brain
Classifiers
Health
Hardware
Monitoring

Keywords

  • BCI
  • EEG
  • General knowledge
  • Reading
  • Wearable computing

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Software

Cite this

Shirazi, A. S., Hassib, M., Henze, N., Schmidt, A., & Kunze, K. S. (2014). What's on your mind? Mental task awareness using single electrode brain computer interfaces. In Proceedings of the 5th Augmented Human International Conference, AH 2014 [a45] Association for Computing Machinery. https://doi.org/10.1145/2582051.2582096

What's on your mind? Mental task awareness using single electrode brain computer interfaces. / Shirazi, Alireza Sahami; Hassib, Mariam; Henze, Niels; Schmidt, Albrecht; Kunze, Kai Steven.

Proceedings of the 5th Augmented Human International Conference, AH 2014. Association for Computing Machinery, 2014. a45.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Shirazi, AS, Hassib, M, Henze, N, Schmidt, A & Kunze, KS 2014, What's on your mind? Mental task awareness using single electrode brain computer interfaces. in Proceedings of the 5th Augmented Human International Conference, AH 2014., a45, Association for Computing Machinery, 5th Augmented Human International Conference, AH 2014, Kobe, Japan, 14/3/7. https://doi.org/10.1145/2582051.2582096
Shirazi AS, Hassib M, Henze N, Schmidt A, Kunze KS. What's on your mind? Mental task awareness using single electrode brain computer interfaces. In Proceedings of the 5th Augmented Human International Conference, AH 2014. Association for Computing Machinery. 2014. a45 https://doi.org/10.1145/2582051.2582096
Shirazi, Alireza Sahami ; Hassib, Mariam ; Henze, Niels ; Schmidt, Albrecht ; Kunze, Kai Steven. / What's on your mind? Mental task awareness using single electrode brain computer interfaces. Proceedings of the 5th Augmented Human International Conference, AH 2014. Association for Computing Machinery, 2014.
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