Benefits of nonlinear analysis indices of walking stride interval in the evaluation of neurodegenerative diseases

AbstractThough self-paced walking is highly stereotyped, the stride interval fluctuates from one stride to the next around an average value with a measurable statistical variability. In clinical gait analysis, this variability is usually assessed with indices such the standard deviation or the coefficient of variation (CV). The aim of this study is to understand the added value that nonlinear indices of walking stride interval variability, such as Hurst exponent (H) and Minkowski fractal dimension (D), can provide in a clinical context and to suggest a clinical significance of these indices in the most common neurodegenerative diseases: Parkinson, Huntington, and amyotrophic lateral sclerosis. Although evidence have been accumulated that the stride interval organization at long range displays a more random, less autocorrelated, gait pattern in neurodegenerative diseases compared with young healthy individuals, it is today necessary to recompute CV, H, and D indices in a unified way and to take into account aging impact on these indices. In fact, computed nonlinear indices of variability are mainly dependent on stride interval time series length and algorithms used, making quantitative comparisons between different studies difficult or even impossible. Here, we recompute these indices from available stride interval time series, either coming from our lab or from online databases, or made available to us by the authors of previously conducted research. We confirm that both linear and nonlinear variability indices are relevant indicators of aging process and neurodegenerative diseases. CV is sensitive to aging process and pathology but does not allow to discriminate between specific neurodegenerative diseases. D shows no significative change in pathological groups. However, since H index is correlated with Hoehn & Yahr scores and significantly lowered in patients suffering from Huntington’s disease, we recommend it as a relevant supplement to CV.

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String Grammar Unsupervised Possibilistic Fuzzy C-Medians for Gait Pattern Classification in Patients with Neurodegenerative Diseases

Computational Intelligence and Neuroscience ◽

10.1155/2018/1869565 ◽

2018 ◽

Vol 2018 ◽

pp. 1-10 ◽

Cited By ~ 1

Author(s):

Atcharin Klomsae ◽

Sansanee Auephanwiriyakul ◽

Nipon Theera-Umpon

Keyword(s):

Neurodegenerative Diseases ◽

Nearest Neighbor ◽

Gait Pattern ◽

Time Interval ◽

K Nearest Neighbor ◽

Symbolic Aggregate Approximation ◽

Average Accuracy ◽

Stride Interval ◽

Gait Abnormalities

Neurodegenerative diseases that affect serious gait abnormalities include Parkinson's disease (PD), amyotrophic lateral sclerosis (ALS), and Huntington disease (HD). These diseases lead to gait rhythm distortion that can be determined by stride time interval of footfall contact times. In this paper, we present a new method for gait classification of neurodegenerative diseases. In particular, we utilize a symbolic aggregate approximation algorithm to convert left-foot stride-stride interval into a sequence of symbols using a symbolic aggregate approximation. We then find string prototypes of each class using the newly proposed string grammar unsupervised possibilistic fuzzy C-medians. Then in the testing process the fuzzy k-nearest neighbor is used. We implement the system on three 2-class problems, i.e., the classification of ALS against healthy patients, that of HD against healthy patients , and that of PD against healthy patients. The system is also implemented on one 4-class problem (the classification of ALS, HD, PD, and healthy patients altogether) called NDDs versus healthy. We found that our system yields a very good detection result. The average correct classification for ALS versus healthy is 96.88%, and that for HD versus healthy is 97.22%, whereas that for PD versus healthy is 96.43%. When the system is implemented on 4-class problem, the average accuracy is approximately 98.44%. It can provide prototypes of gait signals that are more understandable to human.

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Nonlinear Analysis of Stride Interval Time Series in Gait Maturation Using Distribution Entropy

IRBM ◽

10.1016/j.irbm.2021.02.001 ◽

2021 ◽

Author(s):

V. Alcan

Keyword(s):

Time Series ◽

Nonlinear Analysis ◽

Interval Time ◽

Stride Interval ◽

Interval Time Series

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Autophagy and ageing: implications for age-related neurodegenerative diseases

Essays in Biochemistry ◽

10.1042/bse0550119 ◽

2013 ◽

Vol 55 ◽

pp. 119-131 ◽

Cited By ~ 37

Author(s):

Bernadette Carroll ◽

Graeme Hewitt ◽

Viktor I. Korolchuk

Keyword(s):

Neurodegenerative Diseases ◽

Energy Availability ◽

Future Studies ◽

Intracellular Degradation ◽

Age Related ◽

Autophagy Induction ◽

Social Importance ◽

Cellular Dysfunction ◽

Autophagy Activity ◽

Intense Research

Autophagy is a process of lysosome-dependent intracellular degradation that participates in the liberation of resources including amino acids and energy to maintain homoeostasis. Autophagy is particularly important in stress conditions such as nutrient starvation and any perturbation in the ability of the cell to activate or regulate autophagy can lead to cellular dysfunction and disease. An area of intense research interest is the role and indeed the fate of autophagy during cellular and organismal ageing. Age-related disorders are associated with increased cellular stress and assault including DNA damage, reduced energy availability, protein aggregation and accumulation of damaged organelles. A reduction in autophagy activity has been observed in a number of ageing models and its up-regulation via pharmacological and genetic methods can alleviate age-related pathologies. In particular, autophagy induction can enhance clearance of toxic intracellular waste associated with neurodegenerative diseases and has been comprehensively demonstrated to improve lifespan in yeast, worms, flies, rodents and primates. The situation, however, has been complicated by the identification that autophagy up-regulation can also occur during ageing. Indeed, in certain situations, reduced autophagosome induction may actually provide benefits to ageing cells. Future studies will undoubtedly improve our understanding of exactly how the multiple signals that are integrated to control appropriate autophagy activity change during ageing, what affect this has on autophagy and to what extent autophagy contributes to age-associated pathologies. Identification of mechanisms that influence a healthy lifespan is of economic, medical and social importance in our ‘ageing’ world.

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Nanotheranostic agents for neurodegenerative diseases

Emerging Topics in Life Sciences ◽

10.1042/etls20190141 ◽

2020 ◽

Vol 4 (6) ◽

pp. 645-675

Author(s):

Parasuraman Padmanabhan ◽

Mathangi Palanivel ◽

Ajay Kumar ◽

Domokos Máthé ◽

George K. Radda ◽

...

Keyword(s):

Drug Delivery ◽

Neurodegenerative Diseases ◽

Cell Types ◽

Specific Cell ◽

Ageing Population ◽

Target Tissue ◽

Therapeutic Approaches ◽

Surface Receptors ◽

Theranostic Agents ◽

Preclinical Animal Models

Neurodegenerative diseases (NDDs), including Alzheimer's disease (AD) and Parkinson's disease (PD), affect the ageing population worldwide and while severely impairing the quality of life of millions, they also cause a massive economic burden to countries with progressively ageing populations. Parallel with the search for biomarkers for early detection and prediction, the pursuit for therapeutic approaches has become growingly intensive in recent years. Various prospective therapeutic approaches have been explored with an emphasis on early prevention and protection, including, but not limited to, gene therapy, stem cell therapy, immunotherapy and radiotherapy. Many pharmacological interventions have proved to be promising novel avenues, but successful applications are often hampered by the poor delivery of the therapeutics across the blood-brain-barrier (BBB). To overcome this challenge, nanoparticle (NP)-mediated drug delivery has been considered as a promising option, as NP-based drug delivery systems can be functionalized to target specific cell surface receptors and to achieve controlled and long-term release of therapeutics to the target tissue. The usefulness of NPs for loading and delivering of drugs has been extensively studied in the context of NDDs, and their biological efficacy has been demonstrated in numerous preclinical animal models. Efforts have also been made towards the development of NPs which can be used for targeting the BBB and various cell types in the brain. The main focus of this review is to briefly discuss the advantages of functionalized NPs as promising theranostic agents for the diagnosis and therapy of NDDs. We also summarize the results of diverse studies that specifically investigated the usage of different NPs for the treatment of NDDs, with a specific emphasis on AD and PD, and the associated pathophysiological changes. Finally, we offer perspectives on the existing challenges of using NPs as theranostic agents and possible futuristic approaches to improve them.

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