Knee osteoarthritis represents a medical care challenge, requiring tools that improve the accuracy of monitoring during rehabilitation. The tools found present limitations for a complete analysis. In this perspective, we developed a platform to analyze electromyography (EMG) signals stored on file or captured online by an acquisition module. To evaluate the platform, an EMG acquisition of four leg muscles of a healthy subject was performed. Also, EMG signals from the database were used to visualize and calculate typical values used for EMG rehabilitation analysis. The interface allowed online capture and processing of 4 EMG channels. Using the database signals, we applied the envelope, histogram, Fourier transform, rectified, gain, and mean frequency. The values found are in the range found in the literature. The results suggest the user interface can be used for monitoring knee osteoarthritis rehabilitation or other muscle diseases requiring EMG-biofeedback.