Developing an Advanced EEG Signal Analysis Tool with Wavelet Denoising and GPT-3.5
EEG Denoise Using Wavelets: Web App Dev with Python ChatGPT Flask Numpy Scipy Pandas and PYWD
In this video, I demonstrate the development of a user interface for EEG signal analysis, focusing on wavelet-based noise removal and signal visualization. I use GPT-3.5 to generate prompts and tackle various coding challenges, including integrating new features into the interface. The tool allows users to observe changes in EEG signals across different frequency bands, employing wavelet denoising algorithms and discrete wavelet transformations. I discuss the implementation details, troubleshoot issues, and explore different wavelet types suitable for EEG analysis. The video is a deep dive into the practical aspects of developing a signal analysis tool with a specific focus on EEG data.
(00:01) Introduction to the project
(01:01) Opening the new tool for EEG signal analysis
(03:31) Detailed description of the user interface
(07:04) Exploring the folder structure and code
(11:17) Troubleshooting and code generation with GPT-4
(18:27) Debugging JavaScript and Python code
(25:18) Running the application and testing new features
(31:35) Discussing EEG data and seizure analysis
(36:05) Integrating wavelet denoising into the interface
#EEG #SignalAnalysis #WaveletDenoising #UserInterface #GPT3.5 #Coding #JavaScript #Python #Flask #DataVisualization #Neuroscience #Electroencephalogram #SoftwareDevelopment #Debugging #WaveletTransformation
The tools I develop are available on https://bionichaos.com
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