Adaptive Assistance Exoskeleton Control Algorithm
Patent no.: 16/409,671
Inventor(s): Zachary F. Lerner
Description: Wearable robotic assistance device has the potential to revolutionize rehabilitation of patients with neuromuscular deficiencies in free-living environments. For the wearable robot to be effective, it needs to adapt to the individual. An adaptive assistance exoskeleton control algorithm was created to establish and track personalized measures of exoskeleton-assisted walking performance. A hierarchical control strategy is programmed onto the CPU’s memory. The CPU is included on-board the robotic exoskeleton device. The control strategy uses sensors embedded on the exoskeleton to track posture and other data points, evaluate how these parameters change over time, and adjust the level of assistance accordingly. The programmed control algorithm instructs what type of control commands are sent by the CPU to the motor, providing assistance based on feedback from sensors.
Potential applications: Clinical applications for rehabilitation robotics.
Benefits and advantages: Wearable exoskeletons improve the mobility of people with neurological deficits acquired by stroke, spinal cord injury, and Parkinson’s disease. Existing exoskeleton control strategies are not tailored to the individual, nor encourage active participation. User engagement can enhance robot-assisted tasks by tracking user performance overtime, providing real-time performance feedback, and adapting to the user through a control algorithm. The exoskeleton may comprise of one or more types of sensors, and/or more of the same type of sensor, depending on the individual’s gait deficiency.
Case no.: 2017-042
Licensing status: Available for licensing