Abstract

Introducing perturbations on a self-paced treadmill allows participants to experience uncertain environments without restricting their ability to continuously change their walking speed and kinematics. In this dissertation, I evaluated how different self-paced treadmill controller sensitivities affected gait parameters and variability on decline, level, and incline slopes. I also investigated how healthy young and older adults adjust their gait strategies when responding to perturbations of varying unpredictability and whether the changes in gait strategies remained once the perturbations were no longer present. Lastly, I evaluated how differences in gait kinematics when responding to visual and mechanical perturbations at varying frequencies. I found that detrending gait kinematics could be used as a tool to compare gait kinematics when participants walk with varying walking speeds. Higher controller sensitivities lead to greater speed fluctuations and longer steps for decline, level, and incline slopes. When introducing mediolateral perturbations as participants walked on a self-paced treadmill, I found that young and older adults walked faster, not slower, when responding to the perturbations compared to walking with no perturbations. Additionally, I found that after removing mediolateral perturbations faster walking speeds are carry over and are not rapidly washed out. Our findings suggest that separating gait variability into speed-trend and detrended variability could be beneficial for interpreting gait variability among multiple self-paced treadmill studies and when comparing self- paced walking with fixed speed walking. Additionally, these findings are of interest to populations with slow walking speeds such as patients in rehabilitation because using perturbations such as discrete mediolateral treadmill shifts can potentially be designed to encourage participants to walk faster.

Notes

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Graduation Date

2023

Semester

Spring

Advisor

Huang, Helen

Degree

Doctor of Philosophy (Ph.D.)

College

College of Engineering and Computer Science

Department

Mechanical and Aerospace Engineering

Degree Program

Biomedical Engineering

Identifier

CFE0009496; DP0027498

URL

https://purls.library.ucf.edu/go/DP0027498

Language

English

Release Date

May 2023

Length of Campus-only Access

None

Access Status

Doctoral Dissertation (Open Access)

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