iEEG Spectrum Visualization Application
Welcome to the iEEG Spectrum Visualization Application! This advanced tool provides a dynamic interface
for visualizing intracranial EEG data in both time and frequency domains, with an emphasis on detailed analysis
and user interactivity.
Interactive Features
- Wavelet Denoise: Toggle this feature to apply or remove wavelet denoising from the EEG data, enhancing signal clarity.
- Wavelet Type Selector: Choose from various wavelet types such as Discrete, Undecimated, Daubechies, Symlets, Coiflets, and Biorthogonal wavelets to customize the denoising process.
- Levels Selector: Adjust the level of wavelet decomposition to fine-tune the denoising effect.
- Detrend Toggle: This option, when activated, removes linear trends from the EEG data, enhancing the visualization clarity.
- Frequency Scale Selector: Switch between Linear and Log scales to explore EEG data in the frequency domain more effectively.
- Channel Selector: Navigate through 16 different EEG channels, enabling a comprehensive view of the data across various brain regions.
- Window Size Control: Adjust the viewing window size to zoom in or out on the EEG data, offering a range from 1 to 100 seconds.
- File Scroll Bar: A horizontal scroll bar allowing seamless navigation through the EEG data timeline.
Data Visualization
- Raw Signal Plot: Observe the raw EEG signals in real-time, providing insights into the unprocessed data.
- Spectrogram Display: A detailed view of the frequency spectrum of EEG data, offering insights into various frequency bands and their changes over time.
- Signal to Noise Ratio (SNR) and Mean Square Error (MSE): These metrics offer quantitative insights into the quality of the EEG signals, particularly useful in assessing the effectiveness of denoising and filtering techniques.
Technical Overview
The application leverages advanced signal processing techniques, including Butterworth bandpass filters, Fast Fourier Transform (FFT), and wavelet transforms to analyze and visualize EEG data. These techniques are pivotal in extracting meaningful information from complex brain signals.
Data Source
This application uses intracranial EEG data from NeuroVista, available at www.ieeg.org. This rich dataset offers a unique opportunity for exploring brain activities in various states.
Concluding Remarks
This tool is designed to assist researchers, students, and enthusiasts in understanding the complex nature of EEG data. By offering a range of interactive features and detailed visualizations, it provides a platform for in-depth exploration of brain activity patterns.
