Effects of the series length on Lempel-Ziv Complexity during sleep

Rivolta, Massimo W.; Migliorini, Matteo; Aktaruzzaman, Md.; Sassi, Roberto; Bianchi, Anna Maria

doi:10.1109/embc.2014.6943685

Cited by 11 publications

(11 citation statements)

References 11 publications

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“…Lempel-Ziv complexity (LZC): To compute the LZC [75,[99][100][101]103] biomarker of an N-sample EEG data sequence x(1), x(2), . .…”

Section: Higuchi Fractal Dimension (Hfd)mentioning

confidence: 99%

“…HFD is a fast nonlinear computational method for obtaining the fractal dimension of time series signals [96][97][98] and yields biomarkers which are significantly lower in AD patients than in normal subjects [85][86][87]. LZC is a nonparametric and nonlinear method that provides a way to quantify the complexity of the EEG [99,100] and has been used to analyse the EEG complexity in AD [101][102][103].…”

Section: Introductionmentioning

confidence: 99%

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Robust EEG Based Biomarkers to Detect Alzheimer’s Disease

et al. 2021

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Biomarkers to detect Alzheimer’s disease (AD) would enable patients to gain access to appropriate services and may facilitate the development of new therapies. Given the large numbers of people affected by AD, there is a need for a low-cost, easy-to-use method to detect AD patients. Potentially, the electroencephalogram (EEG) can play a valuable role in this, but at present no single EEG biomarker is robust enough for use in practice. This study aims to provide a methodological framework for the development of robust EEG biomarkers to detect AD with clinically acceptable performance by exploiting the combined strengths of key biomarkers. A large number of existing and novel EEG biomarkers associated with slowing of EEG, reduction in EEG complexity. and decrease in EEG connectivity were investigated. Support vector machine and linear discriminate analysis methods were used to find the best combination of the EEG biomarkers to detect AD with significant performance. A total of 325,567 EEG biomarkers were investigated, and a panel of six biomarkers was identified and used to create a diagnostic model with high performance (>=85% for sensitivity and 100% for specificity).

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“…Lempel-Ziv complexity (LZC): To compute the LZC [75,[99][100][101]103] biomarker of an N-sample EEG data sequence x(1), x(2), . .…”

Section: Higuchi Fractal Dimension (Hfd)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Robust EEG Based Biomarkers to Detect Alzheimer’s Disease

et al. 2021

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“…LZC is a nonparametric and nonlinear method that provides a powerful method for quantifying the complexity of finite length sequences [75,76]. It has previously been used to analyze EEG complexity in patients with AD [41,77].…”

Section: Reduction In Eeg Complexitymentioning

confidence: 99%

“…The reduction of LZC values may therefore be a good biomarker for AD [41,77,78]. It is a simple and powerful approach used in a number of biomedical applications [76]. LZC relies on coarse-grain measurement processing [77], and can be directly applied to the physiological signal without pre-processing [78].…”

Section: Reduction In Eeg Complexitymentioning

confidence: 99%

Electroencephalogram Based Biomarkers for Detection of Alzheimer’s Disease

Al-nuaimi¹

2020

Neuroimaging - Neurobiology, Multimodal and Network Applications

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Alzheimer's disease (AD) is an age-related progressive and neurodegenerative disorder, which is characterized by loss of memory and cognitive decline. It is the main cause of disability among older people. The rapid increase in the number of people living with AD and other forms of dementia due to the aging population represents a major challenge to health and social care systems worldwide. Degeneration of brain cells due to AD starts many years before the clinical manifestations become clear. Early diagnosis of AD will contribute to the development of effective treatments that could slow, stop, or prevent significant cognitive decline. Consequently, early diagnosis of AD may also be valuable in detecting patients with dementia who have not obtained a formal early diagnosis, and this may provide them with a chance to access suitable healthcare facilities. An early diagnosis biomarker capable of measuring brain cell degeneration due to AD would be valuable. Potentially, electroencephalogram (EEG) can play a valuable role in the early diagnosis of AD. EEG is noninvasive and low cost, and provides valuable information about brain dynamics in AD. Thus, EEG-based biomarkers may be used as a first-line decisionsupport tool in AD diagnosis and could complement other AD biomarkers.Keywords: EEG biomarkers, AD biomarkers, slowing of EEG, decrease in EEG coherence, reduction in EEG complexity, detection of Alzheimer's disease Neuroimaging -Neurobiology, Multimodal and Network Applications 2 an enormous financial. However, many dementia sufferers are not diagnosed early [7,8]. It is estimated that up to 50% of individuals with dementia may not have been diagnosed formally [8, 9]. In 2011, 28 million people out of 36 million people with dementia were not diagnosed worldwide [10].Degeneration of brain cells due to AD begins many years before clinical manifestations become noticeable [5,[11][12][13][14][15]. Early diagnosis of AD will help to the development of efficient treatments that could mitigate, stop, or prevent significant cognitive impairment [14, 16, 17]. Early diagnosis of AD may also be valuable in detecting patients with dementia who have not obtained a formal early diagnosis, and this may provide them with a chance to access suitable healthcare facilities [18][19][20].An early diagnosis biomarker that can measure brain cell degeneration due to AD would be valuable [2,[21][22][23]. But this may involve dealing with an extremely large number of individuals, as up to 50% of individuals with dementia may not have been diagnosed formally. Therefore, Simple, non-invasive, low-cost and reliable biomarkers are necessary for early diagnosis that can be accessed in clinical practice [5,24,25]. Recent guidelines support the use of biomarkers for biochemical and neuroimaging to promote AD diagnosis. AD testing of cerebral spinal fluid (CSF) is not commonly used in clinical practice as it involves lumbar puncture, an invasive procedure [2,26,27]. Neuroimaging is expensive, accessible only in specialized centers [28], and may ...

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“…Although Kolmogorov complexity cannot be directly measured, Lempel and Ziv (1976) proposed a data compression algorithm based on the Kolmogorov's idea, which is used in measuring randomness in finite-time-series. Lempel-Ziv's approach has been used in several disciplines, including, biomedical engineering (Ib añez-Molina et al, 2015;Rivolta et al, 2014;Y. Zhang et al, 2016)…”

Section: Kolmogorov Complexitymentioning

confidence: 99%

The Origin of Culture: Selective Conditions for Horizontal Information Transfer

Gonzalez

Watson²,

Noble³

et al. 2014

Artificial Life 14: Proceedings of the Fourteenth International Conference on the Synthesis and Simulation of Living Systems

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This article presents an approach to the assessment of operational manufacturing systems complexity based on the irregularities hidden in manufacturing key performance indicator time-series by employing three complementary algorithmic complexity measures: Kolmogorov complexity, Kolmogorov complexity spectrum's highest value and overall Kolmogorov complexity. A series of computer simulations derived from discrete manufacturing systems are used to investigate the measures' potentiality. The results showed that the presented measures can be used in quantitatively identifying operational system complexity, thereby supporting operational shop-floor decision-making activities.

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Effects of the series length on Lempel-Ziv Complexity during sleep

Cited by 11 publications

References 11 publications

Robust EEG Based Biomarkers to Detect Alzheimer’s Disease

Robust EEG Based Biomarkers to Detect Alzheimer’s Disease

Electroencephalogram Based Biomarkers for Detection of Alzheimer’s Disease

The Origin of Culture: Selective Conditions for Horizontal Information Transfer

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