Knee Joint VAG Signal Analysis - Normal vs. Pathological

This project analyzes knee joint vibration arthrometry (VAG) signals to detect abnormalities by simulating normal and pathological signals.

This project focuses on analyzing knee joint vibration arthrometry (VAG) signals to detect abnormalities. It simulates normal and pathological signals, applies a bandpass filter (20-250 Hz) to reduce noise, and uses peak detection to identify differences. Pathological signals show additional high-frequency components and more peaks compared to normal ones. Spectrograms and filtered signals are visualized for better understanding. The method aids in early detection of knee joint abnormalities by combining signal processing, feature extraction, and diagnostic analysis.