Revolutionizing ECG Analysis with Machine Learning and Fuzzy Logic
Channel: BioniChaos
Date: 2024-03-10

Hey everyone! In this video, I dive deep into the fascinating world of ECG analysis using machine learning and fuzzy logic. I share insights on integrating these technologies with both EEG and ECG data. We'll look into HTML code, machine learning applications, and GitHub Copilot for code generation. Throughout the video, I emphasize the importance of concise communication and a bit of humor (but no emojis, I promise!). We'll explore the game logic of waveform analysis using fuzzy logic, the application of dynamic difficulty adjustments, and the nuances of feature extraction. I'll also explain the backend Flask application for the ECG scoring game. Join me as we analyze the specific features of ECG waveforms, such as dominant frequency, positive and negative peaks, and amplitude. By the end, we'll have covered everything from fuzzy set rules to feature calculation methods and the integration with the front-end system. So, let's get started on this exciting journey into the future of ECG analysis!

Try out the tool yourself: bionichaos.com/CardioBot

00:00:00 - Introduction to ECG Analysis and Tools
00:09:21 - Machine Learning in ECG: Combining Fuzzy Logic and Neural Networks
00:37:40 - Code Sharing and HTML Code Explanation
00:58:32 - GitHub Copilot for Code Generation
01:27:16 - Keeping Responses Short and Adding Humor
01:48:44 - Fuzzy Logic for Waveform Analysis
02:02:48 - Dynamic Difficulty Adjustment in Games
02:28:04 - Frontend and Backend Integration for ECG Scoring Game
03:10:32 - Feature Extraction from ECG Waveforms
03:56:00 - Analyzing ECG Waveforms Independently with Fuzzy Logic
04:07:40 - Extracted Features: Dominant Frequency, Peaks, Amplitude
05:03:12 - Improving Feature Extraction and Tuning Fuzzy Logic Rules
05:35:12 - Addressing Potential DC Offset Issues
06:21:12 - Refactoring Code and Normalized Amplitude
07:00:48 - Analyzing Normalized Signals
08:06:48 - Discussing Backend Features and Frontend Display
09:09:00 - Correcting Raw Negative Peaks in Code
10:12:36 - Membership Functions in Fuzzy Logic Analysis
11:06:12 - Validating Negative Peak Count
12:02:00 - Confirming Abnormality Scoring System
13:04:00 - Detailed Overview of Fuzzy Logic Decision Making
14:16:32 - Adjusting Membership Functions and Rules
15:00:36 - Regenerating Functions with New Membership Parameters
17:01:48 - Discussing the Importance of Amplitude in ECG Analysis
18:09:04 - Reviewing Frequency in Fuzzy Logic Analysis
19:45:52 - Final Thoughts on Fuzzy Logic System
20:55:44 - Concluding the Video and Inviting Feedback

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The tools I develop are available on https://bionichaos.com 
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