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Design of Embedded System for Multivariate Classification of Finger and Thumb Movements Using EEG Signals for Control of Upper Limb Prosthesis
- Source :
- BioMed Research International, BioMed Research International, Vol 2018 (2018)
- Publication Year :
- 2018
- Publisher :
- Hindawi, 2018.
-
Abstract
- Brain Computer Interface (BCI) determines the intent of the user from a variety of electrophysiological signals. These signals, Slow Cortical Potentials, are recorded from scalp, and cortical neuronal activity is recorded by implanted electrodes. This paper is focused on design of an embedded system that is used to control the finger movements of an upper limb prosthesis using Electroencephalogram (EEG) signals. This is a follow-up of our previous research which explored the best method to classify three movements of fingers (thumb movement, index finger movement, and first movement). Two-stage logistic regression classifier exhibited the highest classification accuracy while Power Spectral Density (PSD) was used as a feature of the filtered signal. The EEG signal data set was recorded using a 14-channel electrode headset (a noninvasive BCI system) from right-handed, neurologically intact volunteers. Mu (commonly known as alpha waves) and Beta Rhythms (8–30 Hz) containing most of the movement data were retained through filtering using “Arduino Uno” microcontroller followed by 2-stage logistic regression to obtain a mean classification accuracy of 70%.
- Subjects :
- Adult
Male
Article Subject
Computer science
Headset
Movement
0206 medical engineering
lcsh:Medicine
Artificial Limbs
02 engineering and technology
Electroencephalography
Thumb
Alpha wave
General Biochemistry, Genetics and Molecular Biology
Fingers
Upper Extremity
03 medical and health sciences
0302 clinical medicine
medicine
Humans
Beta Rhythm
Electrodes
Brain–computer interface
Signal processing
General Immunology and Microbiology
medicine.diagnostic_test
business.industry
lcsh:R
Signal Processing, Computer-Assisted
General Medicine
Index finger
Prostheses and Implants
Middle Aged
Hand
020601 biomedical engineering
medicine.anatomical_structure
Embedded system
Brain-Computer Interfaces
Female
business
030217 neurology & neurosurgery
Research Article
Subjects
Details
- Language :
- English
- ISSN :
- 23146133
- Database :
- OpenAIRE
- Journal :
- BioMed Research International
- Accession number :
- edsair.doi.dedup.....a087b055958db46dc81c2c0e94a5c26b
- Full Text :
- https://doi.org/10.1155/2018/2695106