Group presentation on neural engineering.pptx

Group presentation on neural engineering

1. NEURAL ENGINEERING GROUP 8 BERYL AGGREY-MENSAH - 11198282  (GROUP LEADER) ESSEL-BINEY NANA BENYIN E.N - 11326879 ACQUAH JAMES - 11348871 JOSEPH BAMPOE - 11068675 NANA KOBINA AHINSAH ABBAN - 11140124

2. SUITABILITY OF TOPIC: Interdisciplinary Nature Relevance and Innovation Cutting-Edge Technology Positive Impact on Healthcare Foundation for future topics

3. INTRODUCTION: Neural engineering: A discipline within biomedical engineering that uses engineering techniques to understand, repair, replace, or enhance neural systems. Combines principles from neuroscience, engineering, and mathematics  ( Ereifej et al., 2019) . It holds the promise of groundbreaking advancements in medical treatment.

4. INTRODUCTION: It can be branched into; Neural Interfaces and Prosthetics Neural Signal Processing Neuromodulation Neural Tissue Engineering Neurorehabilitation

5. DEFINITIONS: Neural Interface and prosthetics; A direct communication pathway between the brain and an external device (Vidal et al., 2016). Neural Signal Processing; The analysis and interpretation of signals generated by the nervous system  (“Advances in Neural Signal Processing,” 2020) .

6. DEFINITIONS: Neurorehabilitation; A physician-supervised program designed for people with diseases, trauma, or disorders of the nervous system (Langhorne et al., 2009). Neuromodulation; The alteration of nerve activity through targeted delivery of a stimului , such as electrical or chemical signals (Lozano & Lipsman, 2013).  

7. DEFINITIONS: Neural Tissue Engineering; Creating artificial neural tissue for repairing or replacing damaged nervous system components (Li et al., 2021; Schmidt & Leach, 2003).

8. CONCEPTS AND PRINCIPLES: Understand: Interpret the Structure and Function of the Nervous System                                                                                                             

9. CONCEPTS AND PRINCIPLES: 2. Interface: Develop Technologies to Interact with the Nervous System                                                                                                                    (Peksa & Mamchur, 2023) 

10. CONCEPTS AND PRINCIPLES: 3. Restore: Repair or Replace Damaged Neural Tissue Ohm’s Law for Electrical Stimulation:                                     V=I⋅R This equation is fundamental for designing electrical stimulation devices used in neural prosthetics and neuromodulation  (Kandel, 2013). 

11. CONCEPTS AND PRINCIPLES: 4.  Enhance: Augment Cognitive and Motor Abilities Plasticity-Dependent Learning Rate:                                 Δw ij  =η⋅(x i  − θ i   )⋅( y j   − θ j   )        This equation represents Hebbian learning, where synaptic weights are adjusted based on the activity of pre- and post-synaptic neurons, underlying mechanisms of learning and memory enhancement .

12. DEVICES THAT UTILIZE NEURAL ENGINEERING: Brain-Computer Interfaces (BCIs) Neural Prosthetics Neuromodulation Devices Neurorehabilitation Tools

13. APPLICATION TO SOLVE HEATHCARE PROBLEMS: Development and deployment of neurorehabilitation tools, such as robotic exoskeletons and brain-computer interfaces for rehabilitation.   Portable neuromodulation devices for non-invasive treatment of neurological disorders, such as TMS devices that can be used in local clinics.

14. APPLICATION TO SOLVE HEATHCARE PROBLEMS: 3.  Implementation of Deep Brain Stimulation(DBS) and other neuromodulation therapies to manage symptoms of diseases like Parkinson's and Alzheimer's.

15. CONCLUSION: Neural engineering has great promise for improving human skills, improving the quality of life for those suffering from neurological illnesses, and offering easily accessible healthcare, particularly in underprivileged areas, through the creation of new technologies and techniques.

16. REFERENCES: Advances in Neural Signal Processing. (2020). In Advances in Neural Signal Processing.  https://doi.org/10.5772/intechopen.81424   Ereifej , E. S., Shell, C. E., Schofield, J. S., Charkhkar , H., Cuberovic , I., Dorval, A. D., Graczyk, E. L., Kozai, T. D. Y., Otto, K. J., Tyler, D. J., Welle, C. G., Widge , A. S., Zariffa , J., Moritz, C. T., Bourbeau, D. J., & Marasco, P. D. (2019). Neural engineering: The process, applications, and its role in the future of medicine. In Journal of Neural Engineering (Vol. 16, Issue 6).   https://doi.org/10.1088/1741-2552/ab4869    Kandel, E. R. (2013). principles of neural science 5 th. My Book Shelf.  Langhorne, P., Coupar, F., & Pollock, A. (2009). Motor recovery after stroke: a systematic review. In The Lancet Neurology (Vol. 8, Issue 8).  https://doi.org/10.1016/S1474-4422(09)70150-4

17. REFERENCES:  Li, Y., Ma, Z., Ren, Y., Lu, D., Li, T., Li, W., Wang, J., Ma, H., & Zhao, J. (2021). Tissue Engineering Strategies for Peripheral Nerve Regeneration. In Frontiers in Neurology (Vol. 12 https://doi.org/10.3389/fneur.2021.768267​  ​  Lozano, A. M., & Lipsman, N. (2013). Probing and Regulating Dysfunctional Circuits Using Deep Brain Stimulation. In Neuron (Vol. 77, Issue 3).  https://doi.org/10.1016/j.neuron.2013.01.020  Peksa, J., & Mamchur, D. (2023). State-of-the-Art on Brain-Computer Interface Technology. In Sensors (Vol. 23, Issue 13).  https://doi.org/10.3390/s23136001  Quian Quiroga, R., & Panzeri, S. (2009). Extracting information from neuronal populations: Information theory and decoding approaches. In Nature Reviews Neuroscience (Vol. 10, Issue 3).  https://doi.org/10.1038/nrn2578

18. REFERENCES:  Schmidt, C. E., & Leach, J. B. (2003). Neural tissue engineering: Strategies for repair and regeneration. In Annual Review of Biomedical Engineering (Vol. 5).  https://doi.org/10.1146/annurev.bioeng.5.011303.120731  Vidal, G. W. V., Rynes, M. L., Kelliher, Z., & Goodwin, S. J. (2016). Review of Brain-Machine Interfaces Used in Neural Prosthetics with New Perspective on Somatosensory Feedback through Method of Signal Breakdown. In Scientifica (Vol. 2016).   https://doi.org/10.1155/2016/8956432