Robotic trunk system for human musculoskeletal support and training

This technology is a cable-driven robotic system that provides active trunk support and postural training for rehabilitation.

Unmet Need: Active postural training for improving trunk control

Current rehabilitation methods for patients with neurological and musculoskeletal disorders or injuries provide only passive management for lack of trunk control. These methods do not resolve paralysis or restore the postural muscle strength needed to sit independently. Moreover, these approaches often require extensive time with physical therapists and expensive equipment, making these treatments cost-prohibitive.

The Technology: Adaptive robotic trunk support trainer for human postural rehabilitation

This device, Trunk Support Trainer (TruST), is a robotic system that consists of multiple cables that connect the patient’s torso to motors mounted on a stationary frame. Tension sensors in TruST provide feedback for adjusting the force applied on the torso for an active training process. TruST uses a motion capture system as well as a real-time controller to implement a two-stage control, through which creative adaptive forces are adjusted as the subject builds strength and stability. This dynamic system allows for supported trunk movement and can be combined with a virtual reality environment for improved patient engagement.

This effectiveness of this technology has been demonstrated in children with cerebral palsy and healthy adults.

Applications:

• Postural training
• Rehabilitation for injured adults
• Antigravity rehabilitation for astronauts returning from space
• Training for children and adolescents with musculoskeletal and neurological disorders
• Virtual reality entertainment system
• Tool for tracking torso movement for musculoskeletal research
• Training tool for increased upper body strength and coordination in healthy individuals

Advantages:

• Facilitates safe and supported trunk movement
• Improves posture
• Helps achieve training goals without the need for physical therapists
• Real-time controller and motion capture for dynamic training
• Simultaneous training and data acquisition
• Safe and beneficial for children and adults
• Virtual reality increases engagement
• Customizable training regimens

Lead Inventor:

Sunil Agrawal, Ph.D.

Patent Information:

Patent Status

Related Publications:

• Khan MI, Santamaria V, Kang J, Bradley BM, Dutkowsky JP, Agrawal SK. “Enhancing Seated Stability Using Trunk Support Trainer (TruST)” IEEE Robot Autom Lett. 2017 Jul; 2(3): 1609-1616.

Tech Ventures Reference:

• IR CU17264

• Licensing Contact: Dovina Qu