AI Rehabilitation Robotics

Motor Recovery Assessment

Motor Recovery Trajectory

class MotorRecoveryAssessor:
    def predict_recovery(self, days_post_stroke, baseline_score):
        R_max = 0.8 + 0.2 * baseline_score / 10
        k = 0.05 + 0.01 * baseline_score / 10
        return R_max * (1 - np.exp(-k * days_post_stroke))

Adaptive Rehabilitation

Reinforcement Learning

Dynamic Difficulty

class AdaptiveTherapyController:
    def update_difficulty(self, success_rate):
        self.current_diff = np.clip(
            self.current_diff + 0.05 * (success_rate - 0.7), 0.1, 1.0)

Exoskeleton Control

Torque Control