Abstract

On a daily basis, humans walk over a variety of terrains. Studies have shown that spatiotemporal gait parameters, such as stride length, stride frequency, stride variability, etc., change when humans walk down a decline and up an incline compared to level ground. However, these studies have been limited to using fixed speed treadmills or analyzing a small number of strides when conducted over ground. Thus, there is a need to investigate the fluctuations in spatiotemporal gait parameters of humans walking at their self-selected speed, which requires recording hundreds of strides. Here we hypothesized that subjects will walk with a slower speed and have greater stride variability on an incline or decline compared to level ground. We used a self-paced treadmill and had 7 young adults walk on three slopes (+9 degrees, incline; 0 degrees, level; -9 degrees, decline). A motion capture system was used to calculate spatiotemporal gait parameters. The results showed that subjects walked the fastest on level ground (1.15 +/- 0.17 m/s). Subjects walked more slowly during decline walking (1.06 +/- 0.14 m/s) and walked the slowest during incline walking (0.92 +/- 0.18 m/s). There was not a single steady-state speed that subjects used for all slopes. Instead, there were multiple periods when the subject was not at a steady state. Only ~60% of the strides could be classified as being at steady-state. When walking down a decline, subjects needed ~10 +/- 1 more strides to reach the first steady-state period. When walking on an incline and decline, stride length variability increased by ~1.6x (0.0014�2 ± 0.0008�2) and ~1.2x (0.0012�2 ± 0.0008�2 ) compared to level ground (0.0005 �2 ± 0.0003 �2). Stride width variability increased by ~20.6x (0.0108�2 ± 0.0121�2 ) and ~14.2x (0.0076�2 ± 0.0044�2 ) for incline and decline slopes compared to level ground (0.0005 �2 ± 0.0003 �2). These results provide greater insight on the fluctuations during self-selected walking speeds subjects use on different slopes. This could have implications on balance control and fall risk during walking.

Notes

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Graduation Date

2019

Semester

Spring

Advisor

Huang, Helen

Degree

Master of Science (M.S.)

College

College of Engineering and Computer Science

Department

Mechanical and Aerospace Engineering

Degree Program

Biomedical Engineering; Biomedical Engineering Biomechanics

Format

application/pdf

Identifier

CFE0007441

URL

http://purl.fcla.edu/fcla/etd/CFE0007441

Language

English

Release Date

May 2019

Length of Campus-only Access

None

Access Status

Masters Thesis (Open Access)

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