NDLI: Motion Discrimination from EEG Using Logistic Regression and Schmitt-Trigger-Type Threshold

Content Provider	IEEE Xplore Digital Library
Author	Murakami, M. Nakatani, S. Araki, N. Konishi, Y. Mabuchi, K.
Copyright Year	2015
Description	Author affiliation: Grad. Sch. of Eng., Univ. of Hyogo, Himeji, Japan (Murakami, M.; Nakatani, S.; Araki, N.; Konishi, Y.) \|\| Grad. Sch. of Inf. Sci. & Technol., Univ. of Tokyo, Tokyo, Japan (Mabuchi, K.)
Abstract	In this study, a robot rehabilitation system is developed for motor paralysis using a brain -- machine interface (BMI) that estimates a patient's intention of motion from his electroencephalogram (EEG). Then, we consider the forcible movement of the patient's affected parts by an exoskeleton robot in synchronicity with his estimated intention. Further, we considered a motion discrimination method using an EEG that was measured when a healthy subject executed an upper-arm bending and stretching exercise. As a result, we used the10 -- 14 Hz band overall intensity of an EEG measured at the right parietal region as a feature of motion discrimination and proposed a method that employed logistic regression to obtain the likelihood function of the discriminated motion. Moreover, we used dual threshold processing, well-known as a "Schmitt-trigger gate" in the field of electronic engineering, to calculate the motion discrimination result using the obtained likelihood value. The effectiveness of our proposed method was confirmed through a motion discrimination experiment.
Starting Page	2338
Ending Page	2342
File Size	421533
Page Count	5
File Format	PDF
e-ISBN	9781479986972
DOI	10.1109/SMC.2015.409
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-10-09
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Electroencephalography Logistics Mathematical model Electrodes Motion measurement Logic gates Noise measurement Schmitt trigger Brain-machine interface Electroencephalogram Logistic regression
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
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