Preliminary Results on a New Algorithm for Blink Correction Adaptive to Inter- and Intra-Subject Variability
| Autor: | E. Guttmann-Flury, Xiangyang Zhu, Xinjun Sheng, Dingguo Zhang |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
medicine.diagnostic_test
Computer science Electrooculography Electroencephalography Signal Intra Subject Variability Statistical classification Amplitude Quantitative Biology - Neurons and Cognition FOS: Biological sciences medicine Preprocessor Neurons and Cognition (q-bio.NC) Time domain Algorithm |
| Zdroj: | NER |
| DOI: | 10.48550/arxiv.1910.14292 |
| Popis: | This paper presents a new preprocessing method to correct blinking artifacts in Electroencephalography (EEG) based Brain-Computer Interfaces (BCIs). This Algorithm for Blink Correction (ABC) directly corrects the signal in the time domain without the need for additional Electrooculogram (EOG) electrodes. The main idea is to automatically adapt to the blink's inter- and intra-subject variability by considering the blink's amplitude as a parameter. A simple Minimum Distance to Riemannian Mean (MDRM) is applied as the classification algorithm. Preliminary results on three subjects show a mean classification accuracy increase of 13.7% using ABC. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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