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International Journal of Recent Trends in Science and Technology, ISSN 2277-2812 E-ISSN: 2249-8109

Volume 6, Issue 1, Febraury 2013 pp 07-12

Research Article

Classifying Gait Patterns of Older Adults by Movement Control and Biomechanical Factors: Validation by Gait and Physical Performance Measures

 

Shyam D. Ganvir1*, Suvarna S.Ganvir 2, Amit V Nagrale 3, Abhijit D.Diwate4

{1Principal & Professor, 2Professor, 4Associate Professor} Padmashree Dr. Vithalrao Vikhe Patil Foundations, College of Physiotherapy, Ahmednagar, Maharashtra, INDIA.

3Associate Professor, Maharashtra Institute of Physiotherapy, Latur, Maharashtra, INDIA.

 

Academic Editor : Dr. Aher K.R.

Abstract

 

Background: While gait patterns of older adults with mobility problems vary, the patterns are rarely used to plan interventions. The purpose of this study was to establish concurrent validity of a clinically useful classification system using gait and physical performance measures. Methods: Community-dwelling male veterans (n=106; mean 76 ± 7.1) referred for mobility problems were videotaped for evaluation. Gait patterns have been classified using structured clinical observation and along movement control factors (consistent, inconsistent) & biomechanical factors (posture: usual, flexed, extended, crouched). Pair wise comparisons across various groups were performed to validate the gait classification using gait parameters (gait speed, step length, width and variability), lower extremity range of motion and muscle strength, physical function in ADL (Physical Performance Test, PPT) and gait abnormalities (GARS-M). Results: Consistent and inconsistent groups were different in gait speed (0.66 and 0.49m/s, respectively; p=0.003), step length (0.46 and 0.38m; p=0.008), step length variability (7.47% and 12.74%; p=0.043), the PPT (15.80 and 11.73; p<0.001) and GARS-M (5.83 and 10.66; p<0.001). Within both consistent and inconsistent groups, four groups defined by postural patterns, also differed in gait speed, step length, PPT and GARS-M scores (p<.05). Conclusion: Gait pattern classification based on movement control and biomechanical factors has good concurrent validity with respect to gait and physical performance measures of mobility.