Literature DB >> 33535366

The Potential Application of Multiscale Entropy Analysis of Electroencephalography in Children with Neurological and Neuropsychiatric Disorders.

Yen-Ju Chu1, Chi-Feng Chang2, Jiann-Shing Shieh2,3,4, Wang-Tso Lee1,5.   

Abstract

Electroencephalography (EEG) is frequently used in functional neurological assessment of children with neurological and neuropsychiatric disorders. Multiscale entropy (MSE) can reveal complexity in both short and long time scales and is more feasible in the analysis of EEG. Entropy-based estimation of EEG complexity is a powerful tool in investigating the underlying disturbances of neural networks of the brain. Most neurological and neuropsychiatric disorders in childhood affect the early stage of brain development. The analysis of EEG complexity may show the influences of different neurological and neuropsychiatric disorders on different regions of the brain during development. This article aims to give a brief summary of current concepts of MSE analysis in pediatric neurological and neuropsychiatric disorders. Studies utilizing MSE or its modifications for investigating neurological and neuropsychiatric disorders in children were reviewed. Abnormal EEG complexity was shown in a variety of childhood neurological and neuropsychiatric diseases, including autism, attention deficit/hyperactivity disorder, Tourette syndrome, and epilepsy in infancy and childhood. MSE has been shown to be a powerful method for analyzing the non-linear anomaly of EEG in childhood neurological diseases. Further studies are needed to show its clinical implications on diagnosis, treatment, and outcome prediction.

Entities:  

Keywords:  EEG; Tourette syndrome; attention deficit/hyperactivity disorder; autism; epilepsy; multiscale entropy; neonatal seizure

Year:  2017        PMID: 33535366     DOI: 10.3390/e19080428

Source DB:  PubMed          Journal:  Entropy (Basel)        ISSN: 1099-4300            Impact factor:   2.524


  3 in total

1.  Diagnosis of attention deficit hyperactivity disorder using non-linear analysis of the EEG signal.

Authors:  Yasaman Kiani Boroujeni; Ali Asghar Rastegari; Hamed Khodadadi
Journal:  IET Syst Biol       Date:  2019-10       Impact factor: 1.615

2.  Cognitive Outcome Prediction in Infants With Neonatal Hypoxic-Ischemic Encephalopathy Based on Functional Connectivity and Complexity of the Electroencephalography Signal.

Authors:  Noura Alotaibi; Dalal Bakheet; Daniel Konn; Brigitte Vollmer; Koushik Maharatna
Journal:  Front Hum Neurosci       Date:  2022-01-27       Impact factor: 3.169

3.  Impairment of Cardiac Autonomic Nerve Function in Pre-school Children With Intractable Epilepsy.

Authors:  Zhao Yang; Tung-Yang Cheng; Jin Deng; Zhiyan Wang; Xiaoya Qin; Xi Fang; Yuan Yuan; Hongwei Hao; Yuwu Jiang; Jianxiang Liao; Fei Yin; Yanhui Chen; Liping Zou; Baomin Li; Yuxing Gao; Xiaomei Shu; Shaoping Huang; Feng Gao; Jianmin Liang; Luming Li
Journal:  Front Neurol       Date:  2021-06-25       Impact factor: 4.003

  3 in total

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