NDLI: Detecting and classifying three different hand movement types through electroencephalography recordings for neurorehabilitation

Content Provider	Springer Nature Link
Author	Jochumsen, Mads Niazi, Imran Khan Dremstrup, Kim Kamavuako, Ernest Nlandu
Copyright Year	2015
Abstract	Brain–computer interfaces can be used for motor substitution and recovery; therefore, detection and classification of movement intention are crucial for optimal control. In this study, palmar, lateral and pinch grasps were differentiated from the idle state and classified from single-trial EEG using only information prior to the movement onset. Fourteen healthy subjects performed the three grasps 100 times, while EEG was recorded from 25 electrodes. Temporal and spectral features were extracted from each electrode, and feature reduction was performed using sequential forward selection (SFS) and principal component analysis (PCA). The detection problem was investigated as the ability to discriminate between movement preparation and the idle state. Furthermore, all task pairs and the three movements together were classified. The best detection performance across movements (79 ± 8 %) was obtained by combining temporal and spectral features. The best movement–movement discrimination was obtained using spectral features: 76 ± 9 % (2-class) and 63 ± 10 % (3-class). For movement detection and discrimination, the performance was similar across grasp types and task pairs; SFS outperformed PCA. The results show it is feasible to detect different grasps and classify the distinct movements using only information prior to the movement onset, which may enable brain–computer interface-based neurorehabilitation of upper limb function through Hebbian learning mechanisms.
Starting Page	1491
Ending Page	1501
Page Count	11
File Format	PDF
ISSN	01400118
Journal	Medical and Biological Engineering and Computing
Volume Number	54
Issue Number	10
e-ISSN	17410444
Language	English
Publisher	Springer Berlin Heidelberg
Publisher Date	2015-12-06
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Hand grasp Brain–computer interface Movement-related cortical potential Movement intention Signal processing Human Physiology Biomedical Engineering Imaging Radiology Computer Applications
Content Type	Text
Resource Type	Article
Subject	Biomedical Engineering Computer Science Applications

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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