Citation

Baydal-Bertomeu JM, Page AF, Belda-Lois JM, Garrido-Jaén D, Prat JM. Clin. Biomech. 2011; 26(1): 29-34.

Affiliation

Instituto de Biomecánica de Valencia, Universidad Politécnica de Valencia, Edificio 9C, Camino de Vera s/n. 46022, Valencia, Spain.

Copyright

(Copyright © 2011, Elsevier Publishing)

DOI

10.1016/j.clinbiomech.2010.08.008

PMID

20858573

Abstract

BACKGROUND: Whiplash-associated disorders have usually been explored by analyzing changes in the cervical motor system function by means of static variables such as the range of motion, whereas other behavioural features such as speed, variability or smoothness of movement have aroused less interest. METHODS: Whiplash patients (n=30), control subjects (n=29) and a group of people faking the symptoms of whiplash-associated-disorders (Simulators, n=30) performed a cyclical flexion-extension movement. This movement was recorded by means of video-photogrammetry. The computed variables were: range of motion, maxima angular velocity and acceleration, and two additional variables that quantify the repeatability of a motion and its spontaneity. Two comparisons were made: Control vs. Patients and Patients vs. Simulators. At each comparison we used ANOVA to detect differences between groups and discriminant analysis to evaluate the ability of these variables to classify individuals. FINDINGS: Comparison between Controls and Patients showed significant reductions in the range of motion, and both the maximum of angular velocity and acceleration in the Patients. The most efficient discriminant model only included the range of motion and maximum angular velocity. Comparison between Patients and Simulators showed a significant reduction in all measured variables in the Simulators. The best classification model was obtained with maximum angular velocity, spontaneity and repeatability of motion. INTERPRETATION: Our results suggest that the pathological patterns differ from those of Controls in amplitude and speed of motion, but not in repeatability or spontaneity of movement. These variables are especially useful for detecting abnormal movement patterns.

Language: en