ARTIFICIAL NEURAL NETWORK FOR NEURAL ACTION POTENTIAL DETECTION

Аннотация

Neural action potentials are electrical signals generated by neurons and are crucial for understanding the functioning of the nervous system. The project aims to develop a system that utilizes artificial neural networks (ANNs) for the detection of neural action potentials.

The project focuses on designing filters using ANNs in MATLAB to accurately detect and classify neural action potentials. The filters are trained using labelled data, where the input represents the electrical signals and the output indicates whether an action potential is present or not. The neural network learns to recognize patterns in the signals and makes predictions based on the training data.

The MATLAB program implements preprocessing techniques to remove noise and artifacts from the collected data. Relevant features are extracted from the preprocessed data to capture the characteristics of action potentials. These features include amplitude, duration, shape, and frequency content of the

electrical signals.

Overall, the project seeks to contribute to the development of accurate and efficient methods for neural action potential detection using artificial neural networks in MATLAB. The results obtained from this project can enhance our understanding of neural activity and have implications for various fields, including neuroscience, neurology, and brain-computer interfaces.