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Design and evaluation of action observation and motor imagery based BCIs using Near-Infrared Spectroscopy

Title
Design and evaluation of action observation and motor imagery based BCIs using Near-Infrared Spectroscopy
Author(s)
Abibullaev, BerdakhAn, Jin UngLee, Seung HyunMoon, Jeon Il
Issued Date
2017-02
Citation
Measurement, v.98, pp.250 - 261
Type
Article
Author Keywords
Brain-computer interfaceNear-infrared spectroscopyMirror therapyHaptic devicePCAMultiple support vector machinesChannel localizationBCI for neural rehabilitation
Keywords
BRAIN-COMPUTER INTERFACEVIRTUAL-REALITYCLASSIFICATIONFNIRSREHABILITATIONTHERAPYSIGNALSFMRI
ISSN
0263-2241
Abstract
The integration of Brain-Computer-Interfaces (BCI) into rehabilitation research is a promising approach that may substantially impact the rehabilitation success. Yet, there is still significant challenges that needs to be addressed before the BCI technology can be fully used effectively in a clinical setting as a neural prosthesis for motor impaired users. As it is still unknown whether the conventional BCI induction strategies that use different the types of stimuli and/or mental tasks induce cortical reorganization for disabled users. This paper presents a design and evaluation of a real-time Near-Infrared Spectroscopy (NIRS) based BCI protocol to control an external haptic device, and an interesting source of brain signals that may convey complementary information for inducing neuroplasticity. The protocol is based on the ideas derived from Mirror-based Therapy (MT) in which subjects not only perform literal motor imagery tasks but also combine their intents with visual action observation of a related motor imagery task. The NIRS-BCI system then commands a haptic device in real-time to move in opposing directions of leftward and rightward movement. We also compare the proposed protocol to the conventional limb motor imagery task and verify its efficacy with online decoding accuracies up to 94.99%. The initial validation of the experimental setup was done with seven healthy subjects. Nonetheless we contend that the design of the current NIRS-BCI method hold promise with patient populations for effective stroke rehabilitation therapy, because the beneficial effects of MT alone in post-stroke recovery has already been manifested in the literature. © 2016 Elsevier Ltd
URI
http://hdl.handle.net/20.500.11750/17108
DOI
10.1016/j.measurement.2016.12.001
Publisher
Elsevier BV
Related Researcher
  • 안진웅 An, Jinung 지능형로봇연구부
  • Research Interests
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Appears in Collections:
Division of Intelligent Robotics 1. Journal Articles
Division of Intelligent Robotics Brain Robot Augmented InteractioN(BRAIN) Laboratory 1. Journal Articles

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