Instructional Leadership, emphasis: K-12 School Leadership (MEd)
Molecular structure and liquids used in research labs

Adaptive Assistance Exoskeleton Control Algorithm


Wearable robotic assistance device has the potential to revolutionize the 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 into the CPU’s memory. The CPU is included on board the robotic exoskeleton device. The control strategy uses sensors embedded in 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.

Additional information

Patent number and inventor


Zachary F. Lerner


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 do they encourage active participation. User engagement can enhance robot-assisted tasks by tracking user performance over time, providing real-time performance feedback, and adapting to the user through a control algorithm. The exoskeleton may be comprised of one or more types of sensors, and/or more of the same type of sensor, depending on the individual’s gait deficiency.

Case number and licensing status


This is available for licensing.