A New Severity Index for Nondestructive Dynamic Analyses in Equinus Gait

نویسندگان

  • Yong-Hoon Rim
  • Young-Jin Kim
  • Sang-Sik Lee
  • Joung H. Mun
چکیده

Equinus gait, defined as walking on one forefoot or both forefeet, has long been considered an undesirable characteristic in patients with a variety of neuromuscular disorders. In the equinus gait, the heel contact pattern is changed according to the severity, because an excessive ankle plantar flexion instigates rearfoot lifting in patients. However, no biomechanical severity index exists to evaluate the rehabilitation procedure of equinus gait. Therefore, we developed an SIEG (Severity Index of Equinus Gait) for nondestructive evaluation of the equinus gait and to validate the index with regard to 11 kinematic and kinetic factors of gait analysis. In this study, the 3-D heel contact pattern was considered for the development of a severity index. In order to verify the result, we compared the developed severity index values with ankle joint kinematic and kinetic factors in 3 test groups. As a result, the average SIEG values ranged between 10.45 (Normal group) and 26.61 (Severe group) and the highest correlation with regard to the 3 groups was shown in the developed severity index. Additionally, we also presented a fuzzy model using Takagi-Sugeno-Kang(TSK) logic with regard to the 12 factors in order to more accurately classify equinus gait. Introduction Equinus gait is most commonly caused by ankle equinus, which is often identified as an impairment of individuals with spastic hemiplegia[2]. Individuals with ankle equinus present a characteristic gait pattern of forefoot rocking without rearfoot rocking or ankle rocking. This characteristic gait pattern generates excessive plantar flexion, moment, and power at the ankle because the rearfoot is lifted by dynamic tightness or fixed contracture of the triceps surae [3]. In the clinical gait analysis employing a 3-D motion capture system, joint relative angle, moment, and power of one gait cycle are most demanding information for the diagnosis of pathological gait. The ankle joint relative angle, moment, and power are especially important criteria used to diagnose the degree of ankle equinus, because equinus gait mainly causes pathological problems at the ankle joint due to dynamic tightness or fixed contracture of the triceps surae and the Achilles’ tendon. In recent literature, Armand et al.[1] used gait 10 factors based on the relative angle of the ankle, moment, and power to classify pathological gait patterns; most of the researchers who study about equinus gait have used a method which compared with ankle angle, moment, and power of normal walkers and toe walkers. However, because the human body is not rigid, gait analysis based on 3-D motion capture system results in experimental errors associated with skin movement artifacts[4]. Additionally, the errors caused by markers located on the skin directly above anatomical landmarks, such as the lateral malleolus and the head of the fibula, are larger than those caused by other markers[4]. Therefore, the values for the joint angle, moment, and power have errors due to this artifact of the skin movement. As a result, the accuracy of diagnosis for patients defined by the degree of ankle equinus may below. This study was: (1) to evaluate the reliability of ankle angle, moment, and power in equinus gait; (2) to develop an index for nondestructive evaluation of the equinus gait based on the heel marker * Corresponding author Key Engineering Materials Vols. 321-323 (2006) pp 1086-1089 online at http://www.scientific.net © (2006) Trans Tech Publications, Switzerland Online available since 2006/Oct/15 All rights reserved. No part of contents of this paper may be reproduced or transmitted in any form or by any means without the written permission of the publisher: Trans Tech Publications Ltd, Switzerland, www.ttp.net. (ID: 130.203.133.34-16/04/08,14:12:55) movement pattern, which has less error than markers located on anatomical landmarks; and (3) to provide a more accurate model based on a fuzzy logic for clinical decision making.

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تاریخ انتشار 2008