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Published on: April 18, 2011
Quantitative evaluation of spasticity in upper limbs in hemiplegic subject using a mathmatical model
Takanori Uchiyama1, Ryoko Kato, Shitaro Obata
1Dept. Applied Physics and Physico-Informatics, Fac. Science and Technology, Keio University, Yokohama, Japan.
Summary
This study introduces a new method to measure upper limb spasticity in hemiplegic patients using mathematical modeling of elbow joint dynamics. Results show a correlation between calculated elasticity and the modified Ashworth scale.
Area of Science:
- Rehabilitation Medicine
- Biomedical Engineering
- Neuroscience
Background:
- Spasticity in hemiplegic patients affects upper limb function.
- Current spasticity evaluation methods, like the modified Ashworth scale, have limitations.
- Objective, quantitative measures are needed for spasticity assessment.
Purpose of the Study:
- To propose and validate a novel technique for evaluating upper limb spasticity.
- To quantify spasticity using biomechanical modeling and electromyography (EMG).
- To correlate the proposed measure with the established modified Ashworth scale.
Main Methods:
- Developed a mathematical model to represent elbow joint torque-angle relationships.
- Measured elbow joint angle, torque, and muscle EMGs in hemiplegic patients.
- Utilized the least squares and Runge-Kutta methods for model approximation and simulation.
Main Results:
- The mathematical model accurately approximated the relationship between elbow angle and torque.
- Obtained inertia and visco-elastic coefficients from the model.
- Calculated average elasticity showed a positive correlation with the modified Ashworth scale scores.
- Elasticity varied with patient posture (sitting vs. standing).
Conclusions:
- The proposed technique offers a quantitative and objective method for spasticity evaluation.
- The derived elasticity measure shows promise as a complementary tool to the modified Ashworth scale.
- Posture-dependent variations in elasticity highlight the need for standardized measurement conditions.
