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Effects of cognitive, anthropometric, and gravitational conditions on gait variability

Blair, Matthew James
The overall purpose of this dissertation was to distinguish if gait variability could detect changes due to outside stimuli. Study 1’s objective was to define measures that can detect changes in gait patterns due to cognitive loading in healthy younger subjects. Study 2’s objective was to assess the effect of weight gains on gait variability, and ultimately the risk of falling. In addition, we wanted to quantify the effect of walking barefoot versus walking with athletic shoes. Study 3’s objective was to quantify the effect of gravity on the variability of two modes of locomotion (walking and running). For each study ten gait parameters were assessed: three temporal (step interval, stride interval, stance interval), five spatial (step length, stride length, sway, center of pressure in the anterior-posterior positions (COP AP), center of pressure in the medial-lateral directions (COP ML)), and two kinetic (max heel pressure, max toe pressure). For each parameter the coefficient of variability was used. Study 1 found that as a cognitive load increases the variability of two kinetic and one spatial parameters (max heel pressure, max toe pressure and COP ML) significantly increase. Study 2 found that both body mass index (BMI) and footwear had a significant effect on six of the gait parameters. As BMI was increased there was a significant increase in two temporal and two kinetic (step, stride, max heel pressure, max toe pressure). One spatial parameter (COP AP) showed a significant decrease as BMI was increased. Study 3 found that as gravity decreased there was a significant differences in variability for three temporal, two spatial, and two kinetic (step interval, stance interval, stride interval, COP displacement AP, sway, max heel pressure, and max toe pressure). We conclude that gait variability is more than simple noise and can be used to be an indicator to aid in fall prediction, disease diagnosis, and used in other clinical applications. All the sensitive gait parameters found can be obtained using non-invasive measures.