Real-Time Biomedical Data Visualization: Creating Lissajous Curves with Python and Flask
Welcome to another live development session on BioniChaos! In this video, I dive into the process of developing BioCurveViz, a tool for visualizing biomedical data in the form of Lissajous curves using Python and Flask. We’ll explore how these curves can represent complex relationships in signals like EEG and ECG, and the challenges of integrating real-time data into visual applications.
Throughout this stream, I’ll demonstrate how I tweak parameters for frequency and phase shifts to visualize interactions between different data signals. I also share how to replace manual inputs with interactive sliders to make the visualization more intuitive and dynamic. This tool will soon be available on bionichaos.com/BioCurveViz, so make sure to check it out and provide your feedback.
If you enjoy the content and want to support my work, don’t hesitate to like, comment, and subscribe! You can also follow the progress of this project on BioniChaos.com, where I'll be adding more tools like BioCurveViz soon!
🔗 Try BioCurveViz Now: bionichaos.com/BioCurveViz
Hashtags:
#PythonFlask #BiomedicalData #LissajousCurves #RealTimeVisualization #BioCurveViz #EEGAnalysis #ECGVisualization #BioniChaos #DataScience #InteractiveLearning
0:00 - Introduction to BioniChaos tools
0:10 - Organizing upcoming tools and projects
0:19 - Jumping straight into development
0:30 - Traceback issue with Socket.IO and Flask setup
0:44 - Exploring Lissajous curves for biomedical data
0:57 - Discussing unique Lissajous curves for EEG and ECG data
1:09 - GPT-4’s suggestion on Lissajous curve generation
1:20 - Adding biomedical data for curve visualization
1:31 - Quick review of app setup for user parameters
1:45 - Moving from manually input parameters to data-driven generation
2:02 - Biomedical signal analysis for Lissajous curve generation
2:15 - Signal processing with Fourier analysis
2:32 - Automatic parameter calculation from biomedical data
3:00 - Switching between manual and automated inputs
3:31 - Real-time EEG and ECG visualization possibilities
4:00 - Visualizing resonance and signal interactions
5:00 - Understanding how different biomedical signals affect curves
6:00 - Integrating interactive sliders into the application
7:00 - Making real-time adjustments via sliders
7:45 - Enhancing the educational aspects of the app
8:30 - Troubleshooting slider and form issues
10:00 - Improving UX with live visual feedback
11:00 - Exploring different parameter ranges for phase shifts
12:30 - Updating JavaScript and HTML for dynamic values
15:00 - Fixing curve defaults and adjusting JavaScript behavior
17:00 - Real-time visualization updates and user feedback
19:00 - Troubleshooting remaining slider issues
20:30 - Wrapping up: Final fixes for the sliders
22:00 - Recap of key features and educational insights
23:00 - Further improvements to biomedical signal processing
24:00 - Next steps: Integrating more real-time biomedical data
26:00 - Reviewing project files and folder structure
28:00 - Flask backend updates for handling Lissajous curves
30:00 - Recap: Key improvements and user feedback integration
32:00 - Final thoughts: Improving the overall UX
34:00 - Exploring more features and signal comparisons
36:00 - Comparing EEG channels using Lissajous curves
38:00 - Addressing neurological conditions using signal analysis
40:00 - How Lissajous curves can aid in diagnosis and therapy
42:00 - Implementing further EEG data visualization features
44:00 - Real-time monitoring with EEG and ECG signals
46:00 - Final fixes for the app
48:00 - Wrapping up development and testing
50:00 - Conclusion and call to action: Visit https://bionichaos.com/BioCurveViz/
The tools I develop are available on https://bionichaos.com
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