- 【Updated on May 12, 2025】 Integration of CiNii Dissertations and CiNii Books into CiNii Research
- Trial version of CiNii Research Knowledge Graph Search feature is available on CiNii Labs
- 【Updated on June 30, 2025】Suspension and deletion of data provided by Nikkei BP
- Regarding the recording of “Research Data” and “Evidence Data”
The Human Factors and Ergonomics of P300-Based Brain-Computer Interfaces
-
- J. Powers
- Department of English, North Carolina State University, Raleigh, NC 27695, USA
-
- Kateryna Bieliaieva
- Department of English, North Carolina State University, Raleigh, NC 27695, USA
-
- Shuohao Wu
- Fitts Department of Industrial and Systems Engineering, North Carolina State University, Raleigh, NC 27695, USA
-
- Chang Nam
- Fitts Department of Industrial and Systems Engineering, North Carolina State University, Raleigh, NC 27695, USA
Description
<jats:p>Individuals with severe neuromuscular impairments face many challenges in communication and manipulation of the environment. Brain-computer interfaces (BCIs) show promise in presenting real-world applications that can provide such individuals with the means to interact with the world using only brain waves. Although there has been a growing body of research in recent years, much relates only to technology, and not to technology in use—i.e., real-world assistive technology employed by users. This review examined the literature to highlight studies that implicate the human factors and ergonomics (HFE) of P300-based BCIs. We assessed 21 studies on three topics to speak directly to improving the HFE of these systems: (1) alternative signal evocation methods within the oddball paradigm; (2) environmental interventions to improve user performance and satisfaction within the constraints of current BCI systems; and (3) measures and methods of measuring user acceptance. We found that HFE is central to the performance of P300-based BCI systems, although researchers do not often make explicit this connection. Incorporation of measures of user acceptance and rigorous usability evaluations, increased engagement of disabled users as test participants, and greater realism in testing will help progress the advancement of P300-based BCI systems in assistive applications.</jats:p>
Journal
-
- Brain Sciences
-
Brain Sciences 5 (3), 318-356, 2015-08-10
MDPI AG
- Tweet
Details 詳細情報について
-
- CRID
- 1360576138669007744
-
- ISSN
- 20763425
-
- Data Source
-
- Crossref