An Investigation of Motor Imagery and Virtual Reality for Post-Stroke Motor Function Recovery
Creators: name: Choy, Chi Sang
Publisher: name: RMIT University
Year: 2025
Subjects: classificationCode: 420703
subject: Motor control
classificationCode: 400304
subject: Biomedical imaging
classificationCode: 400310
subject: Rehabilitation engineering

description: Stroke is a life-threatening disease resulting in brain damage that often leads to physical disabilities profoundly disrupting the quality of life. Post-stroke recovery relies on the rewiring of neural networks, a process known as neuroplasticity. In particular, the motor cortex plays a pivotal role in motor-related processes for restoring motor functions. It is generally accepted in scientific discourse that neuroplasticity is most active within the subacute period (&lt;6 months) post-stroke and deteriorates over time. An effective recovery necessitates urgent rehabilitation as soon as patients have survived their stroke with stable vital signs. Nonetheless, severe stroke-induced motor impairment presents a formidable challenge, constraining rehabilitative options because the current standard intervention, such as physiotherapy and occupational therapy, often requires some residual movement from stroke patients in addition to passive movement therapy.

To address the physical limitations in rehabilitation, a novel strategy involving motor imagery (MI), action observation (AO) and virtual reality (VR) technology to enable stroke recovery requiring no patient mobility shows promise, yet there is mixed evidence in the literature. This thesis contributes to the body of evidence supporting the integration of MI, the ability to perform a mental movement, as a standard clinical practice for stroke rehabilitation, with VR for complementary assistance. To ensure the safety of this research, non-invasive neuroimaging techniques are utilised to capture brain signals via portable functional near-infrared spectroscopy (fNIRS) and electroencephalogram (EEG) with sufficiently high spatial and temporal resolutions, respectively. Additionally, EEG is used for its compatibility with VR. This research examines fNIRS and EEG signals through brain activation and connectivity analyses. Efficient algorithms are developed to optimise the workflow of this research. Normalisation complemented by statistical tests is employed to extract quantitative patterns of brain activity during different experimental tasks. These patterns are illustrative of brain activation in the context of motor function rehabilitation.

Regarding the influence of MI on brain activation, this research identifies the motor and frontal cortices as key regions activated by upper and lower limb MI tasks. Such an observation is indicative of the movement-related and organisational mental processes attributed to MI. In particular, MI tasks generally maximise oxygenated haemoglobin concentration changes in response to more intense brain activation around the motor cortices of healthy and stroke-affected individuals compared to relaxation and casual imagination, with statistically significant p-values (p&lt;0.017). The normalised EEG power spectral density and spectral entropy also reveal greater motor cortex activation in the motor-related frequency band (8-30 Hz) for stroke patients during MI tasks compared to relaxation, with statistical significance (p&lt;0.005). In addition, this research recognises the non-intuitive nature of MI; hence, AO is employed to enhance the performance of MI. Performing MI post-AO has been illustrated to assist both healthy and stroke-affected individuals in activating their motor and frontal cortices. Specifically, the motor cortices of healthy and stroke-affected individuals show a significantly higher increase of normalised changes in oxygenated haemoglobin (p&lt;0.017) after implementing AO. EEG power spectral analyses also illustrate intensified patterns around the motor cortices of stroke patients (p&lt;0.005) post-AO. Furthermore, the integration of VR provides an immersive environment for a more adaptive AO-assisted MI rehabilitation, offering an engaging approach to stroke rehabilitation. This is shown by EEG α and β band power peaks within 8-30 Hz over the motor cortices of the majority of stroke patients (p&lt;0.005) after AO via VR compared to non-VR tasks. This research further uncovers variations in motor cortex activation patterns among different individuals during both upper and lower-limb MI. Additionally, the significant distance correlation connectivity (dCorr&gt;0.85) for analysing the dependence of fNIRS channels of the motor cortex with other brain areas exhibits variations between relaxation and MI tasks, particularly for stroke patients. The significant coherence connectivity (coh&gt;0.35) for the EEG spectral analysis also indicates individual differences in brain connections. These findings emphasise the efficacy of exposure to diverse MI exercises for maximising motor cortex activation by increasing the likelihood of applying an effective type of MI from various MI tasks to accommodate inter-subject variability in MI ability.

These findings demonstrate that MI is viable for enhancing motor function recovery in stroke patients, with its efficacy enhanced by AO and VR. The integration of these techniques leads to intensified brain activation in motor-related regions, which is crucial for motor function recovery. Furthermore, variations in connectivity patterns reinforce the need for VR-customised MI tasks to accommodate individual differences in MI ability. These findings substantiate the adoption of MI, complemented by AO and VR, to enable early motor function recovery regardless of stroke patients’ mobility impairments.