Gait analysis under the lens of statistical physics

Zanin, Massimiliano; Olivares, F.; Pulido-Valdeolivas, Irene; Rausell, Estrella; Gómez‐Andrés, David

doi:10.1016/j.csbj.2022.06.022

Cited by 6 publications

(2 citation statements)

References 168 publications

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“…Recently, a series of trunk acceleration-derived gait measures have been proposed to assess gait imbalance [29,[33][34][35][36][37][38][39][40][41][42][43]. Particularly, three indexes, namely the harmonic ratios (HRs), short-time longest Lyapunov's exponent (sLLE), and step-to-step coefficient of variation (CV), showed the best ability to characterize the trunk behavior during gait of swCA [36][37][38].…”

Section: Introductionmentioning

confidence: 99%

Local Dynamic Stability of Trunk During Gait is Responsive to Rehabilitation in Subjects with Primary Degenerative Cerebellar Ataxia

Castiglia,

Trabassi,

Conte

et al. 2024

Cerebellum

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This study aimed to assess the responsiveness to the rehabilitation of three trunk acceleration-derived gait indexes, namely the harmonic ratio (HR), the short-term longest Lyapunov’s exponent (sLLE), and the step-to-step coefficient of variation (CV), in a sample of subjects with primary degenerative cerebellar ataxia (swCA), and investigate the correlations between their improvements (∆), clinical characteristics, and spatio-temporal and kinematic gait features. The trunk acceleration patterns in the antero-posterior (AP), medio-lateral (ML), and vertical (V) directions during gait of 21 swCA were recorded using a magneto-inertial measurement unit placed at the lower back before (T0) and after (T1) a period of inpatient rehabilitation. For comparison, a sample of 21 age- and gait speed-matched healthy subjects (HSmatched) was also included. At T1, sLLE in the AP (sLLEAP) and ML (sLLEML) directions significantly improved with moderate to large effect sizes, as well as SARA scores, stride length, and pelvic rotation. sLLEML and pelvic rotation also approached the HSmatched values at T1, suggesting a normalization of the parameter. HRs and CV did not significantly modify after rehabilitation. ∆sLLEML correlated with ∆ of the gait subscore of the SARA scale (SARAGAIT) and ∆stride length and ∆sLLEAP correlated with ∆pelvic rotation and ∆SARAGAIT. The minimal clinically important differences for sLLEML and sLLEAP were ≥ 36.16% and ≥ 28.19%, respectively, as the minimal score reflects a clinical improvement in SARA scores. When using inertial measurement units, sLLEAP and sLLEML can be considered responsive outcome measures for assessing the effectiveness of rehabilitation on trunk stability during walking in swCA.

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Section: Introductionmentioning

confidence: 99%

Local Dynamic Stability of Trunk During Gait is Responsive to Rehabilitation in Subjects with Primary Degenerative Cerebellar Ataxia

Castiglia,

Trabassi,

Conte

et al. 2024

Cerebellum

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“…In assessing gait stability, entropy analysis provides insight into gait stability and adaptability under various conditions or perturbations. Differences in entropy measures between healthy individuals and those with gait disorders or pathological conditions can aid in diagnostic or prognostic evaluations [26]. Moreover, entropy-based analysis can elucidate how individuals adapt their gait patterns in response to environmental changes or interventions [14].…”

Section: Introductionmentioning

confidence: 99%

Influence of Perturbation’s Type and Location on Treadmill Gait Regularity

Błażkiewicz,

Hadamus

2024

Applied Sciences

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Background: This study aimed to investigate how —external perturbations caused by a treadmill belt’s acceleration (Acc) and deceleration (Dec) during the Initial-Contact (Initial), Mid-Stance (Mid), and Pre-Swing (ToeOff) phases affect gait regularity in young adults. Methods: Twenty-one healthy young females walked on a treadmill in a virtual environment (Motek GRAIL), in which four unexpected perturbations were applied to the left belt at the Initial, Mid, and ToeOff stages. Sample entropy (SampEn) was calculated for the center of mass (CoM) displacements for six perturbation scenarios in three directions—anterior–posterior (AP), medial–lateral (ML), and vertical (vert)—with SampEn vector lengths (m) ranging from 2 to 10. Results: The CoM displacement exhibited its highest regularity (low SampEn values) in the AP and vert directions during Dec–ToeOff, across all m values. Similarly, this pattern was observed in the ML direction, but exclusively for m = 2 and 4. The least-regular CoM trajectories (high SampEn values) were for Dec–Mid in the AP direction, across all m values. This trend persisted in the ML direction only for m = 2 and 4. However, the most irregular CoM displacements in the ML direction occurred during Dec–ToeOff for the remaining m values. Vertical CoM displacements exhibited the highest irregularities during Dec–Initial for m ≥ 4. Conclusions: Evaluating the regularity of CoM displacements using SampEn can be a useful tool for assessing how gait perturbations are handled.

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Fractals in Neuropsychology and Cognitive Neuroscience

Cerasa

2024

Advances in Neurobiology

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Gait analysis under the lens of statistical physics

Cited by 6 publications

References 168 publications

Local Dynamic Stability of Trunk During Gait is Responsive to Rehabilitation in Subjects with Primary Degenerative Cerebellar Ataxia

Local Dynamic Stability of Trunk During Gait is Responsive to Rehabilitation in Subjects with Primary Degenerative Cerebellar Ataxia

Influence of Perturbation’s Type and Location on Treadmill Gait Regularity

Fractals in Neuropsychology and Cognitive Neuroscience

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