A hybrid neural network approach to gait analysis for remote patient care

Key Points

• Gait analysis shows improved accuracy with a hybrid neural network approach, indicating enhanced remote care capabilities.
• Key evidence reveals an 85% accuracy rate in tracking gait abnormalities using the developed algorithm.
• Analysis employed a hybrid neural network to process gait data effectively, integrating multiple input sources.
• Highlights the need for further research to validate findings in diverse patient populations and settings.