Presenter Type
UNO Graduate Student (Doctoral)
Major/Field of Study
Biomechanics
Other
Mechanical Engineer M.Eng.
Advisor Information
Assistant Professor
Location
CEC RM #128
Presentation Type
Oral Presentation
Start Date
22-3-2024 10:30 AM
End Date
22-3-2024 11:45 AM
Abstract
NEGATIVE IMPACT OF AGING ON GAIT AUTOCORRELATION: A MIXED-EFFECTS ANALYSIS OF STRIDE INTERVAL DYNAMICS
Theodore A. Deligiannis1*, Tyler M. Wiles1, Seung Kyeom Kim1, Nick Stergiou1,2, Aaron D. Likens1
1Department of Biomechanics, University of Nebraska at Omaha
*Corresponding author’s email: tdeligiannis@unomaha.edu
Presentation preference: Podium
Traditional gait metrics, like speed, cadence, coordination, as well as non-linear measures, appear related to Timed Up and Go (TUG). Timed Up and Go is a clinical measurement related to physical, socioeconomic, and psychological parameters, as well as overall health. TUG can be used as a health evaluation tool for adults older than 60, and we predicted that TUG would increase with age and degraded gait autocorrelation. Data were taken from the NONAN GaitPrint database. Two linear mixed effect models were used to characterize how the Hurst exponent changes with age, and in the subset of older adults, the degree to which the H predicts TUG scores, after controlling for age. The model relating TUG and H failed to reveal any reliable relationship. The model relating age and H revealed a significant negative relationship between age and the Hurst exponent (Estimate = -0.24, Std. Error = 0.09, df = 81.99, t = -2.78, p = 0.00669). This suggests that a 1 SD (17.35 years) change in age produces ~.24 SD (.13) reduction in H, indicating the degree of autocorrelation in stride intervals decreases over time. The significant negative association between age and the H of stride intervals suggests that older individuals tend to have less autocorrelation in their stride intervals over time. This could imply a decrease in gait stability or predictability with aging, potentially increasing the risk of mobility issues or falls. Future work will need to address other possible sources of individual differences to further elucidate variability in H across the lifespan. This study advances our understanding of how aging affects gait stability, as evidenced by the observed decrease in gait autocorrelation with age. By highlighting the role of individual differences in gait dynamics, it underscores the importance of personalized assessments in identifying and addressing age-related changes in gait. The findings have potential implications for developing targeted interventions aimed at enhancing mobility and reducing fall risk among older adults. This project was supported by NSF 212491, NIH P20GM109090 & R01NS114282, University of Nebraska Collaboration Initiative, the Center for Research in Human Movement Variability at the University of Nebraska at Omaha, NASA EPSCoR, IARPA.
NEGATIVE IMPACT OF AGING ON GAIT AUTOCORRELATION: A MIXED-EFFECTS ANALYSIS OF STRIDE INTERVAL DYNAMICS
CEC RM #128
NEGATIVE IMPACT OF AGING ON GAIT AUTOCORRELATION: A MIXED-EFFECTS ANALYSIS OF STRIDE INTERVAL DYNAMICS
Theodore A. Deligiannis1*, Tyler M. Wiles1, Seung Kyeom Kim1, Nick Stergiou1,2, Aaron D. Likens1
1Department of Biomechanics, University of Nebraska at Omaha
*Corresponding author’s email: tdeligiannis@unomaha.edu
Presentation preference: Podium
Traditional gait metrics, like speed, cadence, coordination, as well as non-linear measures, appear related to Timed Up and Go (TUG). Timed Up and Go is a clinical measurement related to physical, socioeconomic, and psychological parameters, as well as overall health. TUG can be used as a health evaluation tool for adults older than 60, and we predicted that TUG would increase with age and degraded gait autocorrelation. Data were taken from the NONAN GaitPrint database. Two linear mixed effect models were used to characterize how the Hurst exponent changes with age, and in the subset of older adults, the degree to which the H predicts TUG scores, after controlling for age. The model relating TUG and H failed to reveal any reliable relationship. The model relating age and H revealed a significant negative relationship between age and the Hurst exponent (Estimate = -0.24, Std. Error = 0.09, df = 81.99, t = -2.78, p = 0.00669). This suggests that a 1 SD (17.35 years) change in age produces ~.24 SD (.13) reduction in H, indicating the degree of autocorrelation in stride intervals decreases over time. The significant negative association between age and the H of stride intervals suggests that older individuals tend to have less autocorrelation in their stride intervals over time. This could imply a decrease in gait stability or predictability with aging, potentially increasing the risk of mobility issues or falls. Future work will need to address other possible sources of individual differences to further elucidate variability in H across the lifespan. This study advances our understanding of how aging affects gait stability, as evidenced by the observed decrease in gait autocorrelation with age. By highlighting the role of individual differences in gait dynamics, it underscores the importance of personalized assessments in identifying and addressing age-related changes in gait. The findings have potential implications for developing targeted interventions aimed at enhancing mobility and reducing fall risk among older adults. This project was supported by NSF 212491, NIH P20GM109090 & R01NS114282, University of Nebraska Collaboration Initiative, the Center for Research in Human Movement Variability at the University of Nebraska at Omaha, NASA EPSCoR, IARPA.