Presenter Type
UNO Graduate Student (Doctoral)
Major/Field of Study
Biomechanics
Author ORCID Identifier
https://orcid.org/0000-0002-9220-4910
Advisor Information
Associate Professor
Advisor College
CEHHS
Location
CEC RM #201/205/209
Presentation Type
Poster
Start Date
22-3-2024 2:30 PM
End Date
22-3-2024 3:45 PM
Abstract
Gait symmetry is an essential measure of movement effectiveness and success in rehabilitation, typically assessed using sophisticated motion capture technology for in depth analysis. However, these systems are usually restricted to lab settings, making the m less useful for home monitoring. Considering this constraint, our research sought to fulfill the need for gait analysis tools that are both accessible and feasible for use outside of professional lab environments. Offering a promising alternative, our re search focused on hip angular acceleration, which can be determined through IMU data. Using IMUs and the application of advanced symmetry metrics, we aimed to explore the degree of correlation between metrics based on thigh angular acceleration and step length symmetry obtained from motion capture data. This study is the secondary analysis conducted by Kowalczyk et al. during split belt treadmill walking at different level of gait symmetry ( 1). Five events during the long term observation were adapted: Baseline, Early Adapt, Late Adapt, Early Post, and Late Post. We investigated the thigh angular acceleration derived from the motion data, which could be obtained from IMUs. The step length on the split belt was calculated following the Hoogkamer et al. ( and symmetry index was computed based on the Robinson et al. ( C ontinuous relative phase (CRP) and Pearson correlation based on the thigh angular acceleration were used. The signals of hip angular acceleration were computed as root mean square . T he mean Pearson correlation between right and left hip angular acceleration was calculated at different phases of the experiment. We evaluated how well both metrics correlate with the standard method of step length SI using repeated measures correlation The research revealed a strong link between thigh angular acceleration metrics and step length symmetry, as captured by motion data. Our analysis confirmed this theory, showing significant associations with a CRP of R = 0.74 (p = 0.0036) and a Pearson corr elation of R = 0.71 (p = 0.0062). The findings indicate that thigh based angular acceleration metrics, measured by IMUs, can accurately predict gait symmetry. These results support the use of thigh based measurements for evaluating gait symmetry and sugges t that IMU derived thigh angular acceleration is a reliable predictor of gait symmetry in this study, despite potential challenges in fully capturing step length symmetry. The study demonstrated how hip angular acceleration can be calculated from motion capture data to analyze gait in individuals with gait asymmetry at home, marking a significant advance in attaining gait symmetry outside of standard lab settings compared to other symmetry measurements. It revealed connections between the step length symmetry index from motion data and other symmetry metrics (CPR and Pearson correlation), proposing a novel method for improving gait symmetry and mobility in everyday environments. Moreover, the findings highlight the potential for tracking gait symmetry during interventions in those with gait asymmetry, providing a promising method to enhance rehabilitation processes.
Assessing Step Length Symmetry through Long Duration Home Measurements from IMU Based Angular Acceleration : An Exploration of Feasibility
CEC RM #201/205/209
Gait symmetry is an essential measure of movement effectiveness and success in rehabilitation, typically assessed using sophisticated motion capture technology for in depth analysis. However, these systems are usually restricted to lab settings, making the m less useful for home monitoring. Considering this constraint, our research sought to fulfill the need for gait analysis tools that are both accessible and feasible for use outside of professional lab environments. Offering a promising alternative, our re search focused on hip angular acceleration, which can be determined through IMU data. Using IMUs and the application of advanced symmetry metrics, we aimed to explore the degree of correlation between metrics based on thigh angular acceleration and step length symmetry obtained from motion capture data. This study is the secondary analysis conducted by Kowalczyk et al. during split belt treadmill walking at different level of gait symmetry ( 1). Five events during the long term observation were adapted: Baseline, Early Adapt, Late Adapt, Early Post, and Late Post. We investigated the thigh angular acceleration derived from the motion data, which could be obtained from IMUs. The step length on the split belt was calculated following the Hoogkamer et al. ( and symmetry index was computed based on the Robinson et al. ( C ontinuous relative phase (CRP) and Pearson correlation based on the thigh angular acceleration were used. The signals of hip angular acceleration were computed as root mean square . T he mean Pearson correlation between right and left hip angular acceleration was calculated at different phases of the experiment. We evaluated how well both metrics correlate with the standard method of step length SI using repeated measures correlation The research revealed a strong link between thigh angular acceleration metrics and step length symmetry, as captured by motion data. Our analysis confirmed this theory, showing significant associations with a CRP of R = 0.74 (p = 0.0036) and a Pearson corr elation of R = 0.71 (p = 0.0062). The findings indicate that thigh based angular acceleration metrics, measured by IMUs, can accurately predict gait symmetry. These results support the use of thigh based measurements for evaluating gait symmetry and sugges t that IMU derived thigh angular acceleration is a reliable predictor of gait symmetry in this study, despite potential challenges in fully capturing step length symmetry. The study demonstrated how hip angular acceleration can be calculated from motion capture data to analyze gait in individuals with gait asymmetry at home, marking a significant advance in attaining gait symmetry outside of standard lab settings compared to other symmetry measurements. It revealed connections between the step length symmetry index from motion data and other symmetry metrics (CPR and Pearson correlation), proposing a novel method for improving gait symmetry and mobility in everyday environments. Moreover, the findings highlight the potential for tracking gait symmetry during interventions in those with gait asymmetry, providing a promising method to enhance rehabilitation processes.