Bayesian-optimized filtering and hybrid ViT-LSTM model for knee joint abnormality recognition using sEMG

Key Points

• Knee joint abnormality recognition shows significant improvement using the hybrid model—demonstrating a promising approach.
• Key evidence indicates that this innovative method reduces false positive rates by 20% in sEMG analysis for joint abnormalities.
• Assessment using a Bayesian-optimized filtering technique enhances data processing efficiency in medical diagnostics.
• This approach highlights the potential for advanced machine learning to improve diagnostic accuracy in physical therapy settings.