Individual optimization of EEG channel and frequency ranges by means of genetic algorithm

• Published in: 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2012-01, Vol.2012, p.5290-5293
• Main Authors: Lee, Chungki, Jung, Jihee, Kwon, Gyuhyun, Kim, Laehyun
• Format: Article
• Language: English
• Subjects: Accuracy; Biological cells; Brain; Electrodes; Electroencephalography; Genetic algorithms; Optimization
• ISSN: 1094-687X; 1558-4615; 2694-0604
• DOI: 10.1109/EMBC.2012.6347188

It is well established that motor action/imagery provokes an event-related desynchronization (ERD) response at specific brain areas with specific frequency ranges, typically the sensory motor rhythm and beta bands. However, there are individual differences in both brain areas and frequency ranges which can be used to identify ERD. This often results in low classification accuracy of ERD, which makes it difficult to implement of BCI application such as the control of external devices and motor rehabilitation. To overcome this problem, an individually optimized solution may be desirable for enhancing the accuracy of detecting motor action/imagery with ERD rather than a global solution for all BCI users. This paper presents a method based on a genetic algorithm to find individually optimized brain areas and frequency ranges for ERD classification. To optimize these two components, we designed a chromosome consisting of 64-bit elements represented by a binary number and another 9-bit elements using 512 pre-defined frequency ranges (2^9). The average value of the significant level is set for the properties of the objective function for use in a t-test, (p