Saturday, August 29, 2015

Musing: Limb Rehabilitation Robot Successfully Tested
         with Maplesoft Simulation

Dean Reinke
Deans’ Stroke Musing
Wednesday, August 19, 2015

I'm sure those of you with a little mechanical bent could easily duplicate this. But don't do that - Limb Rehabilitation Robot Successfully Tested with Maplesoft Simulation.

Robotic rehabilitation machines are often used in clinical settings to help exercise patients’ limbs after damaging experiences such as stroke. One of the hardest things to test when building a rehabilitation robot, though, is how it will most effectively interact with a patient. Researchers at the University of Waterloo created a musculoskeletal model of the human arm that can replicate the human action experienced by an upper limb rehabilitation robot, allowing the people designing and developing the robot to take human interaction into account.

A 2D rendition of the arm model used to test
the University of Waterloo's rehabilitation robot.
Image credit: Maplesoft

Researchers Boma Ghannadi and Dr. John McPhee modeled an end-effector based planar robot using Maplesoft’s MapleSim. The robot performs reaching movements in the horizontal plane, replicating the type of movements a human patient would be asked to perform during therapy of the shoulder and elbow. The arm model replicates a simplified planar 2D musculoskeletal arm model with two hinged links and six muscles, and assumes no tendon compliance. Using an impedance controller, the simulated model can adjust itself to replicate either a healthy arm or the variable levels of movement disorders that may affect rehab patients.

The two modes which stimulated a healthy arm were used to calibrate and tune the controller, while the two modes which replicated a post-stroke patient’s arm were used to evaluate its performance.

Hand position error and muscle activation levels were measured during the simulation. Thanks to the positive results, the team demonstrated that it was possible to evaluate the planar robot using musculoskeletal arm models.

The team chose between several simulation tools from multiple vendors before deciding to use MapleSim.

“Taking into account simulation times and quality of results, MapleSim, because of its symbolic computation technology together with optimized code generation, performed better than the other software platforms,” said McPhee.

Next, the researchers will build a working 3D musculoskeletal arm model with integrated muscle wrapping.

The robot is tested in partnership with Toronto Rehabilitation Institute (TRI) and Quanser Inc.

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