This is a repo containing all necessary files for the Final Year Project
This project aimed to demonstrate the clinical applicability of a non-invasive spinal cord interface for eliciting sensory-motor responses. This interface was built on the tonic vibration reflex (TVR), in which sustained vibration over a target muscle induced a motor response via spinal reflex pathways. TVR has been experimentally verified as an effective mechanism for spinal loop neural-muscular signal interac- tion; however, its clinical implementation faced challenges due to the variability of individual responses and the need for strong stimulation. To address these issues, the project followed three stages. This project first determined the optimal stim- ulation parameters for clear TVR responses, including stimulator settings, numbers, and locations. These parameters were configured to induce TVR effectively while minimizing stimulation intrusiveness and discomfort for patients. Next, a mathematical model based on individual data was developed to estimate the expected TVR re- sponse level based on initial stimulation conditions. Various mathematical frameworks were evaluated, and the most robust one was selected based on evaluation metrics. Finally, novel bi-stimulator models were designed, evaluated, and compared to the default single-stimulator model to improve the robustness and effectiveness of the stimulator setup. The “Dual Proximal” model was capable of 100% stimulation of the TVR response in trained volunteers, outperforming the commonly used “ Single Proximal” model in terms of activity level. This novel system, which combines physio- logical and computational design, addressed current clinical issues and has the potential to evaluate the viability of TVR and other sensory feedback circuits as spinal cord interfaces.
- EMG signal processing in MATLAB
- Mathematical Modelling in Python
- Research Sample Physiological Data Set (Volunteers' data not available due to privacy)
