ArticleEntropy (Basel, Switzerland)2018
Characterizing Normal and Pathological Gait through Permutation Entropy.
Article in Entropy (Basel, Switzerland), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Article
- Exploring the Relationship Between Physical Activity and ICF Domains in Young Adults with Cerebral Palsy: A Comparison of Unilateral and Bilateral Cases.Journal of clinical medicine · 2026Article
- Age-related and dual task-induced gait alterations and asymmetry: optimizing the Semmelweis Study gait assessment protocol.GeroScience · 2025Article
- Entropy, Irreversibility, and Time-Series Deep Learning of Kinematic and Kinetic Data for Gait Classification in Children with Cerebral Palsy, Idiopathic Toe Walking, and Hereditary Spastic Paraplegia.Sensors (Basel, Switzerland) · 2025Article
- The influence of walking speed and effects of signal processing methods on the level of human gait regularity during treadmill walking.BMC sports science, medicine & rehabilitation · 2022Article
- Gait analysis under the lens of statistical physics.Computational and structural biotechnology journal · 2022Review
- Monitoring Gait Complexity as an Indicator for Running-Related Injury Risk in Collegiate Cross-Country Runners: A Proof-of-Concept Study.Frontiers in sports and active living · 2021Article
- Classification of Actigraphy Records from Bipolar Disorder Patients Using Slope Entropy: A Feasibility Study.Entropy (Basel, Switzerland) · 2020Article
- On the Application of Entropy Measures with Sliding Window for Intrusion Detection in Automotive In-Vehicle Networks.Entropy (Basel, Switzerland) · 2020Article
- A New Underwater Acoustic Signal Denoising Technique Based on CEEMDAN, Mutual Information, Permutation Entropy, and Wavelet Threshold Denoising.Entropy (Basel, Switzerland) · 2018Article
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Authors and funding
7 authors.
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Abstract
Cerebral palsy is a physical impairment stemming from a brain lesion at perinatal time, most of the time resulting in gait abnormalities: the first cause of severe disability in childhood. Gait study, and instrumental gait analysis in particular, has been receiving increasing attention in the last few years, for being the complex result of the interactions between different brain motor areas and thus a proxy in the understanding of the underlying neural dynamics. Yet, and in spite of its importance, little is still known about how the brain adapts to cerebral palsy and to its impaired gait and, consequently, about the best strategies for mitigating the disability. In this contribution, we present the hitherto first analysis of joint kinematics data using permutation entropy, comparing cerebral palsy children with a set of matched control subjects. We find a significant increase in the permutation entropy for the former group, thus indicating a more complex and erratic neural control of joints and a non-trivial relationship between the permutation entropy and the gait speed. We further show how this information theory measure can be used to train a data mining model able to forecast the child's condition. We finally discuss the relevance of these results in clinical applications and specifically in the design of personalized medicine interventions.
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