NDLI: Does feedback modality affect performance of brain computer interfaces?

Content Provider	IEEE Xplore Digital Library
Author	Darvishi, S. Ridding, M.C. Abbott, D. Baumert, M.
Copyright Year	2015
Description	Author affiliation: Sch. of Pediatrics & Reproductive Health, Univ. of Adelaide, Adelaide, SA, Australia (Ridding, M.C.) \|\| Centre for Biomed. Eng., Univ. of Adelaide, Adelaide, SA, Australia (Darvishi, S.; Abbott, D.; Baumert, M.)
Abstract	Brain computer interfaces (BCI) are used for communication and rehabilitation. One of the main categories of BCI techniques is motor imagery based BCI (MI-BCI). A large number of studies have focused on machine learning approaches to optimize MI-BCI performance. However, enhancement of MI-BCI through provision of optimized feedback modalities has not received equal attention. Motor imagery and motor execution activate almost the same area of the brain. During motor skills performance, a combination of proprioceptive and direct visual feedback (PDVF) is provided. Thus, we hypothesized that MI-BCI that receives PDVF outperforms the traditional MI-BCI, which only uses indirect visual feedback (IVF). We studied 8 healthy subjects performing MI through (i) IVF and (ii) PDVF. We used 8 channel electroencephalogram (EEG) signals and extracted features using an autoregressive model and classified MIs using linear regression. On average, PDVF increased the accuracy of MI performance by 11%, and improved information transfer rate (ITR) by more than two times. In conclusion, using PDVF appears to improve MI-BCI performance according to the studied metrics, making this approach potentially more reliable.
Starting Page	232
Ending Page	235
File Size	617755
Page Count	4
File Format	PDF
ISBN	9781467363891
DOI	10.1109/NER.2015.7146602
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-04-22
Publisher Place	France
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Visualization brain-computer interfaces EEG accuracy motor imagery Brain-computer interfaces Electroencephalography Training information transfer rate Accuracy motor learning Feature extraction Monitoring
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
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
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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