Designing a Low-Cost, Wearable System to Accurately Detect Ground Contact Time Asymmetries Between Each Foot During Outdoor Running
School Name
Spring Valley High School
Grade Level
10th Grade
Presentation Topic
Engineering
Presentation Type
Non-Mentored
Abstract
Running biomechanics, including ground contact time (GCT) and gait asymmetry, play crucial roles in performance and injury risk (Moore et al., 2019). GCT, in particular, is a critical metric for understanding stride efficiency, optimizing training, and preventing injuries (Weber et al., 2024). However, current methods for measuring these parameters, such as motion capture systems or stationary force plates, are expensive and poorly suited for real-world environments (Dunn et al., 2020). This study investigated whether a low-cost, outdoor-capable wearable system could accurately measure GCT and detect gait asymmetries during running. Two identical IMU-based devices were built and attached to each foot, and their GCT measurements were compared to high-speed video analysis across multiple terrains, distances, and running speeds. Device-measured GCT values were evaluated using one-sample z-tests for trials with at least 30 strides and independent t-tests for trials with fewer than 30 strides. Results showed that the device consistently overestimated GCT compared to video validation, with almost all z-tests producing extremely large z-scores (p < .001), indicating statistically significant disagreement between the device and the validated measurements. Independent t-tests revealed inconsistent detection of left-right asymmetry, with only one trial showing comparable values between the left (M = .3275, SD = .0262) and right (M = .3314, SD = 0.0261) sides. Despite these outcomes, the project highlights clear areas for improving algorithmic thresholds, sensor placement, and hardware design in future low-cost wearable systems. The results contribute to the broader effort to develop accessible biomechanical tools for real-world environments.
Recommended Citation
Brandes, Connor, "Designing a Low-Cost, Wearable System to Accurately Detect Ground Contact Time Asymmetries Between Each Foot During Outdoor Running" (2026). South Carolina Junior Academy of Science. 63.
https://scholarexchange.furman.edu/scjas/2026/all/63
Location
Furman Hall 201
Start Date
3-28-2026 10:00 AM
Presentation Format
Oral and Written
Group Project
No
Designing a Low-Cost, Wearable System to Accurately Detect Ground Contact Time Asymmetries Between Each Foot During Outdoor Running
Furman Hall 201
Running biomechanics, including ground contact time (GCT) and gait asymmetry, play crucial roles in performance and injury risk (Moore et al., 2019). GCT, in particular, is a critical metric for understanding stride efficiency, optimizing training, and preventing injuries (Weber et al., 2024). However, current methods for measuring these parameters, such as motion capture systems or stationary force plates, are expensive and poorly suited for real-world environments (Dunn et al., 2020). This study investigated whether a low-cost, outdoor-capable wearable system could accurately measure GCT and detect gait asymmetries during running. Two identical IMU-based devices were built and attached to each foot, and their GCT measurements were compared to high-speed video analysis across multiple terrains, distances, and running speeds. Device-measured GCT values were evaluated using one-sample z-tests for trials with at least 30 strides and independent t-tests for trials with fewer than 30 strides. Results showed that the device consistently overestimated GCT compared to video validation, with almost all z-tests producing extremely large z-scores (p < .001), indicating statistically significant disagreement between the device and the validated measurements. Independent t-tests revealed inconsistent detection of left-right asymmetry, with only one trial showing comparable values between the left (M = .3275, SD = .0262) and right (M = .3314, SD = 0.0261) sides. Despite these outcomes, the project highlights clear areas for improving algorithmic thresholds, sensor placement, and hardware design in future low-cost wearable systems. The results contribute to the broader effort to develop accessible biomechanical tools for real-world environments.