Lower limb amputee motor intention through neuromuscular and mechanical pattern recognition to predict uneven terrain

Prediction of uneven terrain through motor intent pattern recognition has potential for real-time lower-limb prosthesis control to improve amputee balance. Subject-specific pattern recognition algorithms based on residual limb muscular and inertial sensors predicted an uneven step with greater than 75% accuracy in a laboratory environment.