Adding Tactile Feedback and Changing ISI to Improve BCI Systems' Robustness: An Error-Related Potential Study
| Autor: | Farnaz Ghassemi, Bahareh Ahkami |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Computer science
Speech recognition Interface (computing) Feature extraction Interval (mathematics) 050105 experimental psychology Feedback 03 medical and health sciences 0302 clinical medicine Motor imagery Robustness (computer science) Humans 0501 psychology and cognitive sciences Radiology Nuclear Medicine and imaging Statistical analysis Brain–computer interface Radiological and Ultrasound Technology Event (computing) 05 social sciences Brain Electroencephalography Neurology Touch Brain-Computer Interfaces Neurology (clinical) Anatomy 030217 neurology & neurosurgery |
| Zdroj: | Brain topography. 34(4) |
| ISSN: | 1573-6792 |
| Popis: | Nowadays, the brain-computer interface (BCI) systems attract much more attention than before, yet they have not found their ways into our lives since their accuracy is not satisfying. Error Related Potential (ErRP) is a potential that occurs in human brain signals when an unintended event happens, against ones’ will and thoughts. An example is the occurrence of an error in BCI systems. Investigation of the ErRP could enable researchers to increase the accuracy of BCI systems by detecting instances of inaccuracy in the system. In this research the effects of two parameters on the ErRP are studied: (1) The Motor Imagery Time, also known as Inter-Stimulus Interval (ISI) and (2) different types of feedback (Visual and Tactile). The statistical analysis of the ErRP characteristics showed that feedback type meaningfully affects the ErRP in a cue-paced BCI system and it will affect the time of occurrence of this potential. To validate the proposed idea, different feature extraction, and classification techniques were used for the classification of the BCI system responses. It was shown that by proper selection of the parameters and features, the accuracy of the system could be improved. Tactile feedback together with higher ISI could increase the accuracy of finding erroneous trials up to 90%. The proposed method’s accuracy was significantly higher (p-value |
| Databáze: | OpenAIRE |
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