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Dynamic biomechanical model for assessing and monitoring robot-assisted upper-limb therapy
Author(s) -
Hussein A. Abdullah,
Cole Tarry,
Rahul Datta,
Gauri S. Mittal,
Mohamed Abderrahim
Publication year - 2007
Publication title -
the journal of rehabilitation research and development
Language(s) - English
Resource type - Journals
eISSN - 1938-1352
pISSN - 0748-7711
DOI - 10.1682/jrrd.2006.03.0025
Subject(s) - elbow , robot , torque , inverse dynamics , biomechanics , simulation , wrist , exoskeleton , computer science , forearm , trajectory , physical medicine and rehabilitation , rehabilitation , control theory (sociology) , artificial intelligence , kinematics , physical therapy , medicine , physics , physiology , surgery , control (management) , radiology , classical mechanics , pathology , astronomy , thermodynamics
This article describes the design, validation, and application of a dynamic biomechanical model that assesses and monitors trajectory, position, orientation, force, and torque generated by upper-limb (UL) movement during robot-assisted therapy. The model consists of two links that represent the upper arm and forearm, with 5 degrees of freedom (DOF) for the shoulder and elbow joints. The model is a useful tool for enhancing the functionality of poststroke robot-assisted UL therapy. The individualized inertial segment parameters were based on anthropometric measurements. The model performed inverse dynamic analysis of UL movements to calculate reaction forces and moments acting about the 3-DOF shoulder and 2-DOF elbow joints. Real-time fused biofeedback of a 6-DOF force sensor and three-dimensional (3-D) pose sensors supported the model validation and application. The force sensor was mounted between the robot manipulator and the subject's wrist, while the 3-D pose sensors were fixed at specific positions on the subject's UL segments. The model input and output parameters were stored in the subject's database, which is part of the rehabilitation information system. We assigned 20 nondisabled subjects three different therapy exercises to test and validate the biomechanical model. We found that when the biomechanical model is taught an exercise, it can accurately predict a subject's actual UL joint angles and torques and confirm that the exercise is isolating the desired movement.

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