A method to concatenate multiple short time series for evaluating dynamic behaviour during walking

Abstract

Gait variability is a sensitive metric for assessing functional deficits in individuals with mobility impairments. To correctly represent the temporal evolution of gait kinematics, nonlinear measures require extended and uninterrupted time series. In this study, we present and validate a novel algorithm for concatenating multiple time-series in order to allow the nonlinear analysis of gait data from standard and unrestricted overground walking protocols. The full-body gait patterns of twenty healthy subjects were captured during five walking trials (at least 5 minutes) on a treadmill under different weight perturbation conditions. The collected time series were cut into multiple shorter time series of varying lengths and subsequently concatenated using a novel algorithm that identifies similar poses in successive time series in order to determine an optimal concatenation time point. After alignment of the datasets, the approach then concatenated the data to provide a smooth transition. Nonlinear measures to assess stability (Largest Lyapunov Exponent, LyE) and regularity (Sample Entropy, SE) were calculated in order to quantify the efficacy of the concatenation approach using intra-class correlation coefficients, standard error of measurement and paired effect sizes. Our results indicate overall good agreement between the full uninterrupted and the concatenated time series for LyE. However, SE was more sensitive to the proposed concatenation algorithm and might lead to false interpretation of physiological gait signals. This approach opens perspectives for analysis of dynamic stability of gait data from physiological overground walking protocols, but also the re-processing and estimation of nonlinear metrics from previously collected datasets.

Sensor-based Characterization of Daily Walking: A New Paradigm in Frailty Assessment

“…The ability to walk longer distances is instrumental for humans to perform various activities of daily living and lead an independent life. Walking requires complex mechanisms within the human sensory motor system to provide the necessary timing, coordination, and balance such that the interplay between the center of mass and the base of support are regulated in a repetitive manner (46,56).…”

Sensor-based Characterization of Daily Walking: A New Paradigm in Pre-frailty/Frailty Assessment

“…Further, within in-lab settings, it has been demonstrated that gait irregularity can differ between non-frail and pre-frail older adults (21). We used Sample Entropy (SampEn) assessment defined as equation (2), where was defined as the number of matches in the filtered acceleration signal length (distance function smaller than tolerance ) and as the number of matches of length ( ) (50)(51)(52)(53)(54).…”

“…The ability to walk longer distances is instrumental for humans to perform various activities of daily living and lead an independent life. Walking requires complex mechanisms within the human sensory motor system to provide the necessary timing, coordination, and balance such that the interplay between the center of mass and the base of support are regulated in a repetitive manner (51,61).…”

Sensor-based Characterization of Daily Walking: A New Paradigm in Pre-frailty/Frailty Assessment

“…The ability to walk longer distances is instrumental for humans to perform various activities of daily living and lead an independent life. Walking requires complex mechanisms within the human sensory motor system to provide the necessary timing, coordination, and balance such that the interplay between the center of mass and the base of support are regulated in a repetitive manner (54,64). Previous studies that explored the gait characteristics of non-disabled adults for two weeks to define walking duration, found that 81% of all walking bouts lasted about 60 seconds (35,36).…”