Data-Driven User Feedback: An Improved Neurofeedback Strategy considering the Interindividual Variability of EEG Features
- Title
- Data-Driven User Feedback: An Improved Neurofeedback Strategy considering the Interindividual Variability of EEG Features
- Author
- 임창환
- Keywords
- TEST-RETEST RELIABILITY; REAL-TIME FMRI; MEDITATION; ATTENTION
- Issue Date
- 2016-09
- Publisher
- HINDAWI PUBLISHING CORP
- Citation
- BIOMED RESEARCH INTERNATIONAL, v. 2016, NO. 3939815, Page. 1-7
- Abstract
- It has frequently been reported that some users of conventional neurofeedback systems can experience only a small portion of the total feedback range due to the large interindividual variability of EEG features. In this study, we proposed a data-driven neurofeedback strategy considering the individual variability of electroencephalography (EEG) features to permit users of the neurofeedback system to experience a wider range of auditory or visual feedback without a customization process. The main idea of the proposed strategy is to adjust the ranges of each feedback level using the density in the offline EEG database acquired from a group of individuals. Twenty-two healthy subjects participated in offline experiments to construct an EEG database, and five subjects participated in online experiments to validate the performance of the proposed data-driven user feedback strategy. Using the optimized bin sizes, the number of feedback levels that each individual experienced was significantly increased to 139% and 144% of the original results with uniform bin sizes in the offline and online experiments, respectively. Our results demonstrated that the use of our data-driven neurofeedback strategy could effectively increase the overall range of feedback levels that each individual experienced during neurofeedback training.
- URI
- https://www.hindawi.com/journals/bmri/2016/3939815/https://repository.hanyang.ac.kr/handle/20.500.11754/80311
- ISSN
- 2314-6133; 2314-6141
- DOI
- 10.1155/2016/3939815
- Appears in Collections:
- COLLEGE OF ENGINEERING[S](공과대학) > ELECTRICAL AND BIOMEDICAL ENGINEERING(전기·생체공학부) > Articles
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- Data-Driven User Feedback An Improved Neurofeedback Strategy considering the Interindividual Variability of EEG Features.pdfDownload
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