Brain computer interface (BCI) is a paradigm that offers an alternative communication channel between neural activity generated in the brain and the user’s external environment. BCI decodes the brain activity obtained from an electroencephalogram (EEG) signal and convert this information to a sensible output such as commands to control and communicate with the augmentative and assistive devices. Nevertheless, the majority of the existing BCI system associates with healthy subjects operate based on a combination of multiple limbs and bounded by capability of low dimensional control. Besides that, the acquired results also are not an appropriate platform to infer with the neurologically impaired patients (e.g. spinal cord injury patients). This is probably healthy subjects have full control over their limbs and their EEG signatures show a different pattern. On the other hand, neurologically impaired patients have limited access/control over their limbs and the EEG signatures are affected by the side effects of the prescribed medication, deafferentation and cortical reorganization of brain regions as a function of duration, level and type of disease.This study focuses on the feasibility of developing a multi degree of freedom control BCI system using imagination and intention of movement of a single limb for spinal cord injury (SCI) patients. A pilot study has been conducted on eleven healthy subjects to examine the feasibility of the proposed experimental protocol to record data for implementing the same procedure on SCI patients. In the present study, eighteen SCI patients from Queen Elizabeth National Spinal Injury Unit of the Queen Elizabeth University Hospital voluntarily participated as subjects. The participating subjects have performed and imagined performing right wrist movement towards four centre out directions using a custom made manipulandum triggered by a visual cue whilst EEG, electromyography (EMG) and movement signals are recorded simultaneously through NeuroScanTM Synamp system and CED 1401 (Cambridge Electronic Design). The EEG signal was analysed using signal processing and statistical analysis method. Our findings indicate the detection of Bereitschaft potential 500ms before onset of movement and 500ms after onset of the visual cue. Additionally, there are statistical differences in the relative power within vi the EEG signal rhythm components namely, delta, theta, alpha beta and gamma bands during imagination and intention of movement towards the four different directions.The significant changes of the estimated relative power of EEG components were extracted as features associated with direction. The features then were normalised, cross validated and dimensionality reduced before being classified using k nearest neighbour (k-NN), fuzzy k nearest neighbour (FKNN) and quadratic discriminant analysis (QDA) classifier. The single trial classification results for motor imagery and motor task by k-NN, FKNN and QDA classifier dwell within the range of 52.31%-94.14% and 52.20%-96.51%, respectively. These findings proved that it is possible to develop a functional multi degree of freedom BCI system that employs imagination/intention of movement using a single limb for the SCI population. On top of that the developed BCI system and classification also required no subject training at all.
|Date of Award||1 Apr 2016|
- University Of Strathclyde
|Supervisor||Heba Lakany (Supervisor)Bernard Conway (Supervisor)|