Erik Kowalski1, Danilo S Catelli1, Mario Lamontagne2. 1. School of Human Kinetics, University of Ottawa, Ottawa, ON, Canada. 2. School of Human Kinetics, University of Ottawa, Ottawa, ON, Canada; Department of Orthopedic Surgery, The Ottawa Hospital, Ottawa, ON, Canada. Electronic address: mlamon@uottawa.ca.
Abstract
BACKGROUND: Various methods exist when comparing gait data between groups and include the analysis of a single limb, or taking an average of both limbs. Evidence exists suggesting that both limbs are not symmetrical, so statistical differences may exist in biomechanical variables when comparing gait with different limb-matching methods. RESEARCH QUESTION: Does limb-matching method have an effect on statistical outcome when comparing biomechanical variables during a gait task? METHODS: This retrospective study compared forty participants separated into a younger and older group as they completed a gait task. Twenty-five commonly used biomechanical variables were compared between the two groups using four different limb-matching methods: (i) average of both limbs; (ii) dominant limb; (iii) non-dominant limb; (iv) random limb. A mixed linear model was used to compare all the biomechanical variables between the younger and older group using the different limb-matching methods. RESULTS: Limb-matching methods only had a significant effect for 1/25 variables examined. Group effects between the younger and older groups were more prevalent, with the most significant effects occurring at the ankle joint. SIGNIFICANCE: Limb-matching methods do not have a direct effect on biomechanical outcomes when comparing gait in healthy young and old groups. Gait is cyclical, so limb symmetry is often assumed. However, if the complexity of the task increases, or when comparing against groups with impaired gait, both limbs may behave differently, so limb-matching method may become more crucial.
BACKGROUND: Various methods exist when comparing gait data between groups and include the analysis of a single limb, or taking an average of both limbs. Evidence exists suggesting that both limbs are not symmetrical, so statistical differences may exist in biomechanical variables when comparing gait with different limb-matching methods. RESEARCH QUESTION: Does limb-matching method have an effect on statistical outcome when comparing biomechanical variables during a gait task? METHODS: This retrospective study compared forty participants separated into a younger and older group as they completed a gait task. Twenty-five commonly used biomechanical variables were compared between the two groups using four different limb-matching methods: (i) average of both limbs; (ii) dominant limb; (iii) non-dominant limb; (iv) random limb. A mixed linear model was used to compare all the biomechanical variables between the younger and older group using the different limb-matching methods. RESULTS: Limb-matching methods only had a significant effect for 1/25 variables examined. Group effects between the younger and older groups were more prevalent, with the most significant effects occurring at the ankle joint. SIGNIFICANCE: Limb-matching methods do not have a direct effect on biomechanical outcomes when comparing gait in healthy young and old groups. Gait is cyclical, so limb symmetry is often assumed. However, if the complexity of the task increases, or when comparing against groups with impaired gait, both limbs may behave differently, so limb-matching method may become more crucial.
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