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

Design and evaluation of action observation and motor imagery based BCIs using Near-Infrared Spectroscopy
Abibullaev, B.[Abibullaev, Berdakh]An, J.[An, Jin Ung]Lee, S.H.[Lee, Seung Hyun]Moon, J.I.[Moon, Jeon Il]
DGIST Authors
An, J.[An, Jin Ung]; Moon, J.I.[Moon, Jeon Il]
Issue Date
Measurement: Journal of the International Measurement Confederation, 98, 250-261
Article Type
Bci For Neural RehabilitationBrain-Computer InterfaceBrain Computer InterfaceChannel LocalizationCortical ReorganizationDesign and EvaluationsHaptic DeviceHaptic DevicesHaptic InterfacesHuman Rehabilitation EquipmentInduction StrategiesInfrared DevicesInterfaces (Computer)Mirror TherapiesMirror TherapyMirrorsMotor Impaired UsersMultiple Support Vector MachinesNear-Infrared SpectroscopyNear Infrared SpectroscopyPatient RehabilitationPatient TreatmentPCAStroke Rehabilitation
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
Elsevier B.V.
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