Graduation Year

2026

Document Type

Thesis

Degree

M.S.B.E.

Degree Name

MS in Biomedical Engineering (M.S.B.E.)

Degree Granting Department

Medical Engineering

Major Professor

Stephanie L. Carey, Ph.D.

Committee Member

Alex Otten, Ph.D.

Committee Member

M. Jason Highsmith, Ph.D.

Keywords

Biomechanics, Gait analysis, Orthoses, Prostheses, Wearable Sensors

Abstract

Laboratory-based motion capture systems are widely used for gait analysis but are limited by high cost, infrastructure requirements, and restricted external validity. Inertial measurement units (IMUs) offer a portable and low-cost alternative for assessing gait in both controlled and real-world environments; however, their accuracy and clinical utility require validation. The purpose of this thesis was to develop and evaluate a portable monitoring system using IMUs to quantify spatiotemporal gait parameters and gait asymmetry in both laboratory and community settings, with a focus on prosthetic and orthotic users.

Phase 1 of this study evaluated the agreement between IMU-derived gait metrics and a laboratory-based motion capture reference system in able-bodied participants and individuals with lower-limb amputation or orthotic use. Spatiotemporal parameters were computed and compared using statistical agreement analyses. Results demonstrated strong agreement for most temporal parameters and acceptable agreement for spatial parameters, supporting the validity of the IMU-based system in controlled conditions. Phase 2 extended the evaluation to real-world data collection, in which participants used the system in their daily environments over multi-day periods. Real-world gait metrics and asymmetry measures were examined and compared to in-laboratory values to assess feasibility and clinical relevance. Usability and user experience were also evaluated through participant feedback and usage observations.

Overall, this work demonstrates that a portable IMU-based monitoring system can provide reliable and clinically meaningful gait metrics both in and out of the laboratory. This approach has the potential to enhance real-world assessment of mobility, support longitudinal monitoring, and improve clinical decision-making for prosthetic and orthotic users.

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