Movement Intention Detection from Autocorrelation of EEG for BCI
| Autor: | Yoshikastu Hayashi, Slawomir Nasuto, Yoshikatsu Hayashi, Maitreyee Wairagkar |
|---|---|
| Rok vydání: | 2015 |
| Předmět: |
Quantitative Biology::Neurons and Cognition
Resting state fMRI medicine.diagnostic_test Movement (music) business.industry Speech recognition Autocorrelation Computer Science::Human-Computer Interaction Electroencephalography Feature (computer vision) Finger tapping medicine Artificial intelligence Single trial Psychology business Brain–computer interface |
| Zdroj: | Brain Informatics and Health ISBN: 9783319233437 BIH |
| Popis: | Movement intention detection is important for development of intuitive movement based Brain Computer Interfaces (BCI). Various complex oscillatory processes are involved in producing voluntary movement intention. In this paper, temporal dynamics of electroencephalography (EEG) associated with movement intention and execution were studied using autocorrelation. It was observed that the trend of decay of autocorrelation of EEG changes before and during the voluntary movement. A novel feature for movement intention detection was developed based on relaxation time of autocorrelation obtained by fitting exponential decay curve to the autocorrelation. This new single trial feature was used to classify voluntary finger tapping trials from resting state trials with peak accuracy of 76.7%. The performance of autocorrelation analysis was compared with Motor-Related Cortical Potentials (MRCP). |
| Databáze: | OpenAIRE |
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