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Journal articles on the topic 'Higuchi fractal dimension'

Author: Grafiati

Published: 3 June 2025

Last updated: 31 July 2025

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1

Wanliss, J., R. Hernandez Arriaza, G. Wanliss, and S. Gordon. "OPTIMIZATION OF THE HIGUCHI METHOD." International Journal of Research -GRANTHAALAYAH 9, no. 11 (2021): 202–13. http://dx.doi.org/10.29121/granthaalayah.v9.i11.2021.4393.

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Background and Objective: Higuchi’s method of determining fractal dimension (HFD) occupies a valuable place in the study of a wide variety of physical signals. In comparison to other methods, it provides more rapid, accurate estimations for the entire range of possible fractal dimensions. However, a major difficulty in using the method is the correct choice of tuning parameter (kmax) to compute the most accurate results. In the past researchers have used various ad hoc methods to determine the appropriate kmax choice for their particular data. We provide a more objective method of determining,

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Bykova, M. O., and V. A. Balandin. "Methodological features of the analysis of the fractal dimension of the heart rate." Russian Technological Journal 11, no. 2 (2023): 58–71. http://dx.doi.org/10.32362/2500-316x-2023-11-2-58-71.

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Objectives. The aim of the present work is to determine the fractal dimension parameter calculated for a sequence of R–R intervals in order to identify the boundaries of its change for healthy and sick patients, as well as the possibility of its use as an additional factor in the detection of cardiac pathology.Methods. In order to determine the fractal dimension parameter, the Hurst-, Barrow-, minimum coverage area-, and Higuchi methods are used. For assessing the stationarity of a number of electrocardiography (ECG) intervals, a standard method is used to compare arithmetic averages and varia

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MORENO-GOMEZ, ALEJANDRO, JOSE M. MACHORRO-LOPEZ, JUAN P. AMEZQUITA-SANCHEZ, CARLOS A. PEREZ-RAMIREZ, MARTIN VALTIERRA-RODRIGUEZ, and AURELIO DOMINGUEZ-GONZALEZ. "FRACTAL DIMENSION ANALYSIS FOR ASSESSING THE HEALTH CONDITION OF A TRUSS STRUCTURE USING VIBRATION SIGNALS." Fractals 28, no. 07 (2020): 2050127. http://dx.doi.org/10.1142/s0218348x20501273.

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During the last years, civil infrastructure has experienced an increasing development to satisfy the society’s demands such as communication, transportation, work and living spaces, among others. In this sense, the development and application of methods to guarantee the structure optimal operation, known as Structural Health Monitoring schemes, are necessary in order to avoid economic and human losses. Modern schemes employ the structure vibration response as any damage will modify the structure physical properties, which will be reflected in the vibration response. Thus, by measuring the wave

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Benavides-Bravo, Francisco Gerardo, Dulce Martinez-Peon, Ángela Gabriela Benavides-Ríos, Otoniel Walle-García, Roberto Soto-Villalobos, and Mario A. Aguirre-López. "A Climate-Mathematical Clustering of Rainfall Stations in the Río Bravo-San Juan Basin (Mexico) by Using the Higuchi Fractal Dimension and the Hurst Exponent." Mathematics 9, no. 21 (2021): 2656. http://dx.doi.org/10.3390/math9212656.

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When conducting an analysis of nature’s time series, such as meteorological ones, an important matter is a long-range dependence to quantify the global behavior of the series and connect it with other physical characteristics of the region of study. In this paper, we applied the Higuchi fractal dimension and the Hurst exponent (rescaled range) to quantify the relative trend underlying the time series of historical data from 17 of the 34 weather stations located in the Río Bravo-San Juan Basin, Mexico; these data were provided by the National Water Commission CONAGUA) in Mexico. In this way, th

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Li, Yuxing, Shuai Zhang, Lili Liang, and Qiyu Ding. "Multivariate Multiscale Higuchi Fractal Dimension and Its Application to Mechanical Signals." Fractal and Fractional 8, no. 1 (2024): 56. http://dx.doi.org/10.3390/fractalfract8010056.

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Fractal dimension, as a common nonlinear dynamics metric, is extensively applied in biomedicine, fault diagnosis, underwater acoustics, etc. However, traditional fractal dimension can only analyze the complexity of the time series given a single channel at a particular scale. To characterize the complexity of multichannel time series, multichannel information processing was introduced, and multivariate Higuchi fractal dimension (MvHFD) was proposed. To further analyze the complexity at multiple scales, multivariate multiscale Higuchi fractal dimension (MvmHFD) was proposed by introducing multi

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Sabrine, Ben, and Aguili Taoufik. "Application of Fractal Dimension for Cardiac Arrhythmias Classification." Computational Biology and Bioinformatics 12, no. 1 (2024): 12–17. http://dx.doi.org/10.11648/j.cbb.20241201.12.

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Fractal analysis is crucial for understanding complex, irregular patterns found in nature, finance, and various scientific fields. It helps to reveal self-similarity, where structures repeat at different scales, providing insights into chaotic systems like weather patterns, stock markets, and biological growth. By applying fractal analysis, researchers can model phenomena that traditional geometric methods cannot easily describe, enabling better predictions and deeper comprehension of dynamic systems. The Fractals are a fascinating mathematical tool for modeling the roughness of nature and und

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Garner, David M., Naiara Maria de Souza, and Luiz Carlos M. Vanderlei. "Heart Rate Variability Analysis: Higuchi and Katz’s Fractal Dimensions in Subjects with Type 1 Diabetes Mellitus." Romanian Journal of Diabetes Nutrition and Metabolic Diseases 25, no. 3 (2018): 289–95. http://dx.doi.org/10.2478/rjdnmd-2018-0034.

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Abstract Background and aims: Statistical markers are valuable when assessing physiological status over periods of time and in certain disease states. We assess if type 1 diabetes mellitus promote modification in the autonomic nervous system using the main two types of algorithms to estimate a Fractal Dimension: Higuchi and Katz. Material and methods: 46 adults were divided into two equal groups. The autonomic evaluation consisted of recording heart rate variability (HRV) for 30 minutes in supine position in absence of any other stimuli. Fractal dimensions ought then able to determine which se

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Kumar, Sanjeev, Amod Kumar, Anjan Trikha, Sneh Anand, and Prashanth Gantla. "Higuchi fractal dimension as a measure of analgesia." International Journal of Medical Engineering and Informatics 4, no. 1 (2012): 66. http://dx.doi.org/10.1504/ijmei.2012.045304.

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Pamela, Yolanda Gandes, and Dwi Juniati. "KLASIFIKASI JENIS DELPHINIDAE (LUMBA-LUMBA) DENGAN DIMENSI FRAKTAL MENGGUNAKAN METODE HIGUCHI DAN KNN (K-NEAREST NEIGHBOR)." MATHunesa: Jurnal Ilmiah Matematika 9, no. 1 (2021): 204–11. http://dx.doi.org/10.26740/mathunesa.v9n1.p204-211.

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The delphinidae family belongs to the Cetacean Order and is a member of the Odontocetes. The delphinidae family has characterized by the physical characteristics and frequency ranges of sound signals produced. Living in the sea and being a rare animal makes delphinidae very difficult to find and if we want to be classified, we have to capture and analyze the physicality of delphinidae. By using the fractal dimension we can analyze the sounds of the delphinidae family based on the characteristics of their sound signals to classify them. In this research, members of the delphinidae family will b

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Gvozdarev, Alexey, and Roman Parovik. "On the Relationship between the Fractal Dimension of Geomagnetic Variations at Altay and the Space Weather Characteristics." Mathematics 11, no. 16 (2023): 3449. http://dx.doi.org/10.3390/math11163449.

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The fractal dimension of geomagnetic field component variations (horizontal—H, vertical—Z and magnetic declination—D) at the Baigazan magnetic station at Russian Altay, for the period 2011–2013, were calculated using the Higuchi method. The daily variation of Higuchi Fractal Dimension (HFD) for the D, H, Z components of the geomagnetic field were investigated, and its contribution to the variability of HFD was found to be from 30 to 40 percent of the total variance. A correlation analysis of the fractal dimension of the variations of the D, H, Z components with the Auroral Electrojet (AE) inde

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Mozo Luis, Edwin E., Thiago A. de Assis, and Fernando A. Oliveira. "Unveiling the connection between the global roughness exponent and interface fractal dimension in EW and KPZ lattice models." Journal of Statistical Mechanics: Theory and Experiment 2022, no. 8 (2022): 083202. http://dx.doi.org/10.1088/1742-5468/ac7e3f.

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Abstract A connection between the global roughness exponent and the fractal dimension of a rough interface, whose dynamics are expected to be described by stochastic continuum models, still needs more support from simulations in lattice models, which are key to provide completeness for the characterization of a given universality class. In this work, we investigate the asymptotic fractal dimension of interfaces that evolve according to some specific lattice models in d + 1 dimensions (d = 1, 2), which are expected to belong to the Edwards–Wilkinson or Kardar–Parisi–Zhang universality classes.

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Shi, Chang-Ting. "Signal Pattern Recognition Based on Fractal Features and Machine Learning." Applied Sciences 8, no. 8 (2018): 1327. http://dx.doi.org/10.3390/app8081327.

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As a typical pattern recognition method, communication signal modulation involves many complicated factors. Fractal theory can be used for signal modulation feature extraction and recognition because of its good ability to express complex information. In this paper, we conduct a systematic research study by using the fractal dimension as the feature of modulation signals. Box fractal dimension, Katz fractal dimension, Higuchi fractal dimension, Petrosian fractal dimension, and Sevcik fractal dimension are extracted from eight different modulation signals for signal pattern recognition. Meanwhi

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Li, Zhiwei, Jun Li, Yousheng Xia, Pingfa Feng, and Feng Feng. "Variation Trends of Fractal Dimension in Epileptic EEG Signals." Algorithms 14, no. 11 (2021): 316. http://dx.doi.org/10.3390/a14110316.

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Epileptic diseases take EEG as an important basis for clinical judgment, and fractal algorithms were often used to analyze electroencephalography (EEG) signals. However, the variation trends of fractal dimension (D) were opposite in the literature, i.e., both D decreasing and increasing were reported in previous studies during seizure status relative to the normal status, undermining the feasibility of fractal algorithms for EEG analysis to detect epileptic seizures. In this study, two algorithms with high accuracy in the D calculation, Higuchi and roughness scaling extraction (RSE), were used

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Dehipawala, Sunil, Eric Cheung, George Tremberger, and Tak Cheung. "Entropy and Fractal Dimension Study of the TDP-43 Protein Low Complexity Domain Sequence in ALS Disease Severity and SARS-CoV-2 Gene Sequences in Virulence Variability." Entropy 23, no. 8 (2021): 1038. http://dx.doi.org/10.3390/e23081038.

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The low complexity domain (LCD) sequence has been defined in terms of entropy using a 12 amino acid sliding window along a protein sequence in the study of disease-related genes. The amyotrophic lateral sclerosis (ALS)-related TDP-43 protein sequence with intra-LCD structural information based on cryo-EM data was published recently. An application of entropy and Higuchi fractal dimension calculations was described using the Znf521 and HAR1 sequences. A computational analysis of the intra-LCD sequence entropy and Higuchi fractal dimension values at the amino acid level and at the ATCG nucleotid

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Khoa, Truong Quang Dang, Vo Quang Ha, and Vo Van Toi. "Higuchi Fractal Properties of Onset Epilepsy Electroencephalogram." Computational and Mathematical Methods in Medicine 2012 (2012): 1–6. http://dx.doi.org/10.1155/2012/461426.

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Epilepsy is a medical term which indicates a common neurological disorder characterized by seizures, because of abnormal neuronal activity. This leads to unconsciousness or even a convulsion. The possible etiologies should be evaluated and treated. Therefore, it is necessary to concentrate not only on finding out efficient treatment methods, but also on developing algorithm to support diagnosis. Currently, there are a number of algorithms, especially nonlinear algorithms. However, those algorithms have some difficulties one of which is the impact of noise on the results. In this paper, in addi

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Armonaite, Karolina, Livio Conti, Elzbieta Olejarczyk, and Franca Tecchio. "Insights on neural signal analysis with Higuchi fractal dimension." Communications in Applied and Industrial Mathematics 15, no. 2 (2024): 17–27. http://dx.doi.org/10.2478/caim-2024-0009.

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Abstract Neurophysiological signal analysis is crucial for understanding the complex dynamics of brain function and its deviations in various pathological conditions. Traditional linear methods, while insightful, often fail to capture the full spectrum of inherently non-linear brain dynamics. This review explores the efficacy and applicability of the Higuchi fractal dimension (HFD) in interpreting neurophysiological signals such as scalp electroencephalography (EEG) and stereotactic intracranial encephalography (sEEG). We focus on three case studies: i) distinguishing between Alzheimer’s disea

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Rizal, Achmad, Risanuri Hidayat, Hanung Adi Nugroho, and Willy Anugrah Cahyadi. "Lung sound classification using multiresolution Higuchi fractal dimension measurement." International Journal of Electrical and Computer Engineering (IJECE) 13, no. 5 (2023): 5091. http://dx.doi.org/10.11591/ijece.v13i5.pp5091-5100.

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<span lang="EN-GB">Lung sound is one indicator of abnormalities in the lungs and respiratory tract. Research for automatic lung sound classification has become one of the interests for researchers because lung disease is one of the diseases with the most sufferers in the world. The use of lung sounds as a source of information because of the ease in data acquisition and auscultation is a standard method in examining pulmonary function. This study simulated the potential use of Higuchi fractal dimension (HFD) as a feature extraction method for lung sound classification. HFD calculations w

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Rizal, Achmad, Risanuri Hidayat, Hanung Adi Nugroho, and Willy Anugrah Cahyadi. "Lung sound classification using multiresolution Higuchi fractal dimension measurement." International Journal of Electrical and Computer Engineering (IJECE) 13, no. 5 (2023): 5091–100. https://doi.org/10.11591/ijece.v13i5.pp5091-5100.

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Lung sound is one indicator of abnormalities in the lungs and respiratory tract. Research for automatic lung sound classification has become one of the interests for researchers because lung disease is one of the diseases with the most sufferers in the world. The use of lung sounds as a source of information because of the ease in data acquisition and auscultation is a standard method in examining pulmonary function. This study simulated the potential use of Higuchi fractal dimension (HFD) as a feature extraction method for lung sound classification. HFD calculations were run on a series of k

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Moldovanu, Simona, Felicia Anisoara Damian Michis, Keka C. Biswas, Anisia Culea-Florescu, and Luminita Moraru. "Skin Lesion Classification Based on Surface Fractal Dimensions and Statistical Color Cluster Features Using an Ensemble of Machine Learning Techniques." Cancers 13, no. 21 (2021): 5256. http://dx.doi.org/10.3390/cancers13215256.

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(1) Background: An approach for skin cancer recognition and classification by implementation of a novel combination of features and two classifiers, as an auxiliary diagnostic method, is proposed. (2) Methods: The predictions are made by k-nearest neighbor with a 5-fold cross validation algorithm and a neural network model to assist dermatologists in the diagnosis of cancerous skin lesions. As a main contribution, this work proposes a descriptor that combines skin surface fractal dimension and relevant color area features for skin lesion classification purposes. The surface fractal dimension i

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GUZMAN-VARGAS, L., E. CALLEJA-QUEVEDO, and F. ANGULO-BROWN. "FRACTAL CHANGES IN HEART RATE DYNAMICS WITH AGING AND HEART FAILURE." Fluctuation and Noise Letters 03, no. 01 (2003): L83—L89. http://dx.doi.org/10.1142/s0219477503001117.

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In this work we analyze interbeat cardiac time series arising of three groups: healthy young and healthy elderly subjects and patients with congestive heart failure. We use the fractal dimension method proposed by Higuchi. We find that fractal organization is different for each group. In the case of healthy young subjects only one value of the fractal dimension is necessary to fit the interbeat data, whereas in the cases of healthy elderly and patients with congestive heart failure a crossover behavior in the fractal dimension is present but in opposite directions. By means of a "zoom" on the

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Andronache, Ion. "Application of fractal analysis in interpreting 2D and 3D grayscale images: Methodologies and case studies." Journal of the Bulgarian Geographical Society 52 (June 20, 2025): 157–82. https://doi.org/10.3897/jbgs.e145478.

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This study investigates the application and performance of several fractal analysis methods for interpreting complex spatial patterns in 2D and 3D grayscale images. Using synthetic datasets with known properties, we systematically evaluate the accuracy of multiple fractal metrics. Among these, Fast Fourier Transform (FFT) dimension and Higuchi dimension proved the most effective in capturing both isotropic and anisotropic structural complexity. The methods were then applied to case studies that address land use change, deforestation, reveal fragmentation patterns, and spatial heterogeneity. No

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Yoder, Keith J., Geoffrey Brookshire, Ryan M. Glatt, et al. "Fractal Dimension Distributions of Resting-State Electroencephalography (EEG) Improve Detection of Dementia and Alzheimer’s Disease Compared to Traditional Fractal Analysis." Clinical and Translational Neuroscience 8, no. 3 (2024): 27. http://dx.doi.org/10.3390/ctn8030027.

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Across many resting-state electroencephalography (EEG) studies, dementia is associated with changes to the power spectrum and fractal dimension. Here, we describe a novel method to examine changes in the fractal dimension over time and within frequency bands. This method, which we call fractal dimension distributions (FDD), combines spectral and complexity information. In this study, we illustrate this new method by applying it to resting-state EEG data recorded from patients with subjective cognitive impairment (SCI) or dementia. We compared the performance of FDD with the performance of stan

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Wawrzaszek, Anna, Renata Modzelewska, Agata Krasińska, Agnieszka Gil, and Vasile Glavan. "Fractal Dimension Analysis of Earth Magnetic Field during 26 August 2018 Geomagnetic Storm." Entropy 24, no. 5 (2022): 699. http://dx.doi.org/10.3390/e24050699.

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We analyse the fractal nature of geomagnetic field northward and eastward horizontal components with 1 min resolution measured by the four stations Belsk, Hel, Sodankylä and Hornsund during the period of 22 August–1 September, when the 26 August 2018 geomagnetic storm appeared. To reveal and to quantitatively describe the fractal scaling of the considered data, three selected methods, structure function scaling, Higuchi, and detrended fluctuation analysis are applied. The obtained results show temporal variation of the fractal dimension of geomagnetic field components, revealing differences be

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Gotoh, K., M. Hayakawa, and N. Smirnova. "Fractal analysis of the ULF geomagnetic data obtained at Izu Peninsula, Japan in relation to the nearby earthquake swarm of June–August 2000." Natural Hazards and Earth System Sciences 3, no. 3/4 (2003): 229–36. http://dx.doi.org/10.5194/nhess-3-229-2003.

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Abstract. In our recent papers we applied fractal methods to extract the earthquake precursory signatures from scaling characteristics of the ULF geomagnetic data, obtained in a seismic active region of Guam Island during the large earthquake of 8 August 1993. We found specific dynamics of their fractal characteristics (spectral exponents and fractal dimensions) before the earthquake: appearance of the flicker-noise signatures and increase of the time series fractal dimension. Here we analyze ULF geomagnetic data obtained in a seismic active region of Izu Peninsula, Japan during a swarm of the

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Simion, Adrian Gabriel, Ion Andronache, Helmut Ahammer, et al. "Particularities of Forest Dynamics Using Higuchi Dimension. Parâng Mountains as a Case Study." Fractal and Fractional 5, no. 3 (2021): 96. http://dx.doi.org/10.3390/fractalfract5030096.

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The legal or illegal losses and the natural disturbance regime of forest areas in Romania generate major imbalances in territorial systems. The main purpose of the current research was to examine the dynamics of the complexity of forests under the influence of forest loss but also to compare the applicability of Higuchi dimension. In this study, two fractal algorithms, Higuchi 1D (H1D) and Higuchi 2D (H2D), were used to determine qualitative and quantitative aspects based on images obtained from a Geographic Information System (GIS) database. The H1D analysis showed that the impact of forest l

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OMIDVARNIA, AMIR H., and ALI M. NASRABADI. "A NEW IRREGULARITY CRITERION FOR DISCRIMINATION OF STOCHASTIC AND DETERMINISTIC TIME SERIES." Fractals 16, no. 02 (2008): 129–40. http://dx.doi.org/10.1142/s0218348x08003879.

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In this paper, a new irregularity criterion based on fractal dimensions is introduced. In fact, this criterion (which is called ONH criterion) is the state space version of Higuchi fractal dimension, which can discriminate stochastic and deterministic time series from each other. To compute this criterion, we have exploited "the amount of state vectors fluctuations" in embedding space. By varying the reconstruction delay in embedding space, one can obtain a logarithmic diagram of overall changes corresponding to reconstructed state space versus delays. The slope of the linear region of this di

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Xu, Xin, Bin Lv, Jie Song, Wei Xiang Shi, Yan Ting Hu, and Shan Cheng Yan. "An Analysis Research for Digitized Features of Epileptic EEG Using SVM." Applied Mechanics and Materials 239-240 (December 2012): 1169–72. http://dx.doi.org/10.4028/www.scientific.net/amm.239-240.1169.

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Epilepsy is one of the most common neurological disorders that greatly disturb patients’ daily lives. Traditional epileptic diagnosis relies on tedious visual screening by neurologists from lengthy EEG recording that requires the presence of seizure (ictal) activities. We proposed to study automated epileptic diagnosis using interictal EEG data that was much easier to collect than ictal data. The research aims to develop an automated diagnostic system that can use interictal EEG data to diagnose whether the person is epileptic. This system could also test epileptic seizures in order to provide

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Geng, Shu Juan, Wei Dong Zhou, Qing Mei Yao, and Zhen Ma. "Nonlinear Analysis of EEG Using Fractal Dimension and Approximate Entropy." Advanced Materials Research 532-533 (June 2012): 988–92. http://dx.doi.org/10.4028/www.scientific.net/amr.532-533.988.

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The automated detection of seizures in EEG is significant for epilepsy monitoring, diagnosis and rehabilitation. In this work, we evaluated the differences between epileptic EEG, interictal EEG and normal EEG by computing their Higuchi Fractal Dimension (HFD) and Approximate Entropy (ApEn). The calculated results show that there are significant differences between epileptic EEG and normal EEG in the variations of HFD and ApEn. HFD and ApEn have been shown to be useful to characterize normal and epileptic brain electrical activities, and the degree of complexity of epileptic EEG is lower than t

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Flores, Silvia Eugenia, Alicia Magaly Leon, Betsabe Leon, Rosario Ysabel Bravo, and Wenceslao Teddy Medina. "Application of Uniaxial Compression Curve Fractal Dimension in the Identification of Cañihua (Chenopodium Pallidicaule Aellen) Grain Cultivars." Journal of the ASABE 66, no. 3 (2023): 539–48. http://dx.doi.org/10.13031/ja.15277.

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HIGHLIGHTS Grains of three cañihua cultivars were identified through the determination of fractal dimension of its force?deformation curves. A special test cell device was developed to mechanically assess small grains during compression tests. Cañihua cultivars form separate groups when results of fractal dimension of their force?deformation curves, force of rupture, and fracture force are analyzed with PCA. ABSTRACT.Cañihua is an ancient crop of the Andean regions in South America. High genetic diversity of this crop can be found around Lake Titicaca. Cañihua grain is an important source of f

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Choubey, Hemant, Sandeep Sharma, Rajendra Bahadur Singh, and Vimlesh Kumar Ray. "HFD and MCFET Based Feature Extraction Technique for Detection of Epilepsy Using ANN Classifier." Traitement du Signal 39, no. 2 (2022): 695–700. http://dx.doi.org/10.18280/ts.390233.

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A neurological disorder called Epilepsy which causes the sudden occurrence of epileptic seizures. The electroencephalogram (EEG) is the recorded electrical activities of the brain to examine the epileptic patient through EEG pattern for diagnosis. Epileptic seizure is one of the abnormality or brain disorder in which seizure patterns shows large spikes for specific time domain or area. This work mainly focused on detecting the Epileptic seizures or Epilepsy through the extracted feature like Higuchi Fractal Dimension (HFD) and Masking and Check-in based feature extraction technique (MCFET). Th

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Shankar Beriha, Siba. "Computer Aided Diagnosis System To Distinguish Adhd From Similar Behavioral Disorders." Biomedical and Pharmacology Journal 11, no. 2 (2018): 1135–41. http://dx.doi.org/10.13005/bpj/1474.

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ADHD is one of the most prevalent psychiatric disorder of childhood, characterized by inattention and distractibility, with or without accompanying hyperactivity. The main aim of this research work is to develop a Computer Aided Diagnosis (CAD) technique with minimal steps that can differentiate the ADHD children from the other similar children behavioral disorders such as anxiety, depression and conduct disorder based on the Electroencephalogram (EEG) signal features and symptoms. The proposed technique is based on soft computing and bio inspired computing algorithms. Four non-linear features

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Vivekanandhan, Gayathri, Mahtab Mehrabbeik, Karthikeyan Rajagopal, Sajad Jafari, Stephen G. Lomber, and Yaser Merrikhi. "Higuchi fractal dimension is a unique indicator of working memory content represented in spiking activity of visual neurons in extrastriate cortex." Mathematical Biosciences and Engineering 20, no. 2 (2022): 3749–67. http://dx.doi.org/10.3934/mbe.2023176.

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<abstract><p>Working memory has been identified as a top-down modulation of the average spiking activity in different brain parts. However, such modification has not yet been reported in the middle temporal (MT) cortex. A recent study showed that the dimensionality of the spiking activity of MT neurons increases after deployment of spatial working memory. This study is devoted to analyzing the ability of nonlinear and classical features to capture the content of the working memory from the spiking activity of MT neurons. The results suggest that only the Higuchi fractal dimension c

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LI, ZHIWEI, XIANG QIAN, FENG FENG, TIMING QU, YOUSHENG XIA, and WENMENG ZHOU. "A CONTINUOUS VARIATION OF ROUGHNESS SCALING CHARACTERISTICS ACROSS FRACTAL AND NON-FRACTAL PROFILES." Fractals 29, no. 05 (2021): 2150109. http://dx.doi.org/10.1142/s0218348x21501097.

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In this study, the scaling characteristics of root-mean-squared roughness ([Formula: see text]) was investigated for both fractal and non-fractal profiles by using roughness scaling extraction (RSE) method proposed in our previous work. The artificial profiles generated through Weierstrass–Mandelbrot (W–M) function and the actual profiles, including surface contours of silver thin films and electroencephalography signals, were analyzed. Based on the relationship curves between [Formula: see text] and scale, it was found that there was a continuous variation of the dimension value calculated wi

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SPASIC, SLADJANA, SRDJAN KESIC, ALEKSANDAR KALAUZI, and JASNA SAPONJIC. "DIFFERENT ANESTHESIA IN RAT INDUCES DISTINCT INTER-STRUCTURE BRAIN DYNAMIC DETECTED BY HIGUCHI FRACTAL DIMENSION." Fractals 19, no. 01 (2011): 113–23. http://dx.doi.org/10.1142/s0218348x1100521x.

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The complexity, entropy and other non-linear measures of the electroencephalogram (EEG), such as Higuchi fractal dimension (FD), have been recently proposed as the measures of anesthesia depth and sedation. We hypothesized that during unconciousness in rats induced by the general anesthetics with opposite mechanism of action, behaviorally and poligraphically controlled as appropriately achieved stable anesthesia, we can detect distinct inter-structure brain dynamic using mean FDs. We used the surrogate data test for nonlinearity in order to establish the existence of nonlinear dynamics, and to

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Xu, Xin, Jie Song, Yan Ting Hu, Wei Xiang Shi, and Xu Zhu. "An EEG Analysis Research For Epileptics Using Probabilistic Neural Network." Advanced Materials Research 605-607 (December 2012): 2270–73. http://dx.doi.org/10.4028/www.scientific.net/amr.605-607.2270.

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Nowadays, diagnosis for epilepsy depends on many systems helping the neurologists to quickly find interesting segments from the lengthy signal by automatic seizure detection. However, we notice that it is very difficult, to obtain long-term EEG data with seizure activities for epilepsy patients in areas lack of medical resources and trained neurologists. Therefore, we propose to study automated epileptic diagnosis using interictal EEG data that is much easier to collect than ictal data. The research, therefore, aims to develop an automated diagnostic system that can use interictal EEG data to

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Kesic, S., Ljiljana Nikolic, Branka Janac, and Sladjana Spasic. "Using Higuchi’s fractal dimension in fine analysis of the effects of 2.7 mT and 10 mT static magnetic fields on the complex bursting activity of the snail BR neuron." Archives of Biological Sciences 66, no. 2 (2014): 563–72. http://dx.doi.org/10.2298/abs1402563k.

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The components of complex bioelectrical activity ? action potential (AP), interspike interval (ISI) and the quiet interburst interval (IBI), along with the effects of 2.7 mT and 10 mT static magnetic fields, were identified and examined in the spontaneously active Br neuron of the subesophageal ganglion complex of the garden snail Helix pomatia by fractal analysis using Higuchi?s fractal dimension (FD). The normalized mean of the empirical FD distributions of bursting activity of the Br neuron were formed under different experimental conditions: before (Control), during (MF), and after exposur

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Molina-Tenorio, Yanqueleth, Alfonso Prieto-Guerrero, and Rafael Aguilar-Gonzalez. "A Novel Multiband Spectrum Sensing Method Based on Wavelets and the Higuchi Fractal Dimension." Sensors 19, no. 6 (2019): 1322. http://dx.doi.org/10.3390/s19061322.

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In this work, two novel methodologies for the multiband spectrum sensing in cognitive radios are implemented. Methods are based on the continuous wavelet transform (CWT) and the multiresolution analysis (MRA) to detect the edges of available holes in the considered wideband spectrum. Besides, MRA is also combined with the Higuchi fractal dimension (a non-linear measure) to establish the decision rule permitting the detection of the absence or presence of one or multiple primary users in the studied wideband spectrum. Methods were tested on simulated and real signals showing a good performance.

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Ferenets, Rain, Ann Vanluchene, Tarmo Lipping, Björn Heyse, and Michel M. R. F. Struys. "Behavior of Entropy/Complexity Measures of the Electroencephalogram during Propofol-induced Sedation." Anesthesiology 106, no. 4 (2007): 696–706. http://dx.doi.org/10.1097/01.anes.0000264790.07231.2d.

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Background Several new measures based on the regularity of the electroencephalogram signal for the assessment of depth of anesthesia/sedation have been proposed recently. In this study we analyze the influence of remifentanil and electroencephalogram frequency content of the performance of a set of such measures. Methods Forty-five patients with American Society of Anesthesiologists physical status I were randomly allocated to one of three groups according to the received dose of predicted effect compartment-controlled remifentanil (0, 2, and 4 ng/ml). All 45 patients received stepwise increas

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Shamsi, Elham, Mohammad Ali Ahmadi-Pajouh, and Tirdad Seifi Ala. "Higuchi fractal dimension: An efficient approach to detection of brain entrainment to theta binaural beats." Biomedical Signal Processing and Control 68 (July 2021): 102580. http://dx.doi.org/10.1016/j.bspc.2021.102580.

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Wajnsztejn, Rubens, Tatiana Dias de Carvalho, David M. Garner, et al. "Higuchi fractal dimension applied to RR intervals in children with Attention Defi cit Hyperactivity Disorder." Journal of Human Growth and Development 26, no. 2 (2016): 147. http://dx.doi.org/10.7322/jhgd.119256.

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Li, Yuxing, Shuai Zhang, Lili Liang, and Junxian Wu. "Optimized dispersion Higuchi fractal dimension and its refined composite multi-scale version for signal analysis." Applied Acoustics 224 (September 2024): 110161. http://dx.doi.org/10.1016/j.apacoust.2024.110161.

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Kitio Kwuimy, C. A., T. Haj Mohamad, and C. Nataraj. "Using the Gottwald and Melbourne’s 0-1 test and the Hugichi fractal dimension to detect chaos in defective and healthy ball bearings." MATEC Web of Conferences 241 (2018): 01017. http://dx.doi.org/10.1051/matecconf/201824101017.

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The paper considers the identification of chaotic behavior dynamics using the data extracted from an experimental model of rotor supported on rolling elements. A description of the methodis provided as well as an illustration using a standard dynamic map. The 0-1 test for chaos and the Higuchi dimension are shown to be eﬀective tool in the identification of chaotic behavior of the systembearing with and without faults.

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Stojadinovic, Gordana, Ljiljana Martac, Jelena Podgorac, et al. "The effects of nembutal on the intracerebellar EEG activity revealed by spectral and fractal analysis." Archives of Biological Sciences 72, no. 3 (2020): 425–32. http://dx.doi.org/10.2298/abs200524036s.

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A detailed analysis of the anesthetic-induced modulation of intracerebellar electrical activity is an important step to understand the functional brain responses to anesthesia. We examined the electrical activity recorded from different cortical layers: molecular layer (ML), Purkinje cell layer (PCL), granular layer (GL) and the white matter (WM) in the vermian part of rat cerebellar lobule V during Nembutal anesthesia using spectral and fractal analysis. Spectral analysis revealed a difference in the mean relative power of delta (0.1-4.0 Hz) and theta (4.1-8.0 Hz) frequencies through the cere

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Ramírez-Rojas, A., E. L. Flores-Márquez, L. Guzmán-Vargas, G. Gálvez-Coyt, L. Telesca, and F. Angulo-Brown. "Statistical features of seismoelectric signals prior to M7.4 Guerrero-Oaxaca earthquake (México)." Natural Hazards and Earth System Sciences 8, no. 5 (2008): 1001–7. http://dx.doi.org/10.5194/nhess-8-1001-2008.

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Abstract. In this paper a statistical analysis of seismoelectric ULF signals prior to the M7.4 Guerrero-Oaxaca earthquake (EQ) occurred at the Mexican Pacific coast on 14 September 1995, has been performed. The signals were simultaneously recorded at three monitoring stations from the last months of 1994 until July of 1996. The nonlinear time series methods of Higuchi fractal dimension (HFD) and detrended fluctuation analysis (DFA) have been used. In the three data sets we found some complex dynamical behaviors that seemingly reflect a relaxation-EQ preparation-main shock-relaxation process. I

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Wijayanto, I., S. Hadiyoso, S. Aulia, and B. S. Atmojo. "Detecting Ictal and Interictal Condition of EEG Signal using Higuchi Fractal Dimension and Support Vector Machine." Journal of Physics: Conference Series 1577 (July 2020): 012016. http://dx.doi.org/10.1088/1742-6596/1577/1/012016.

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Nikolopoulos, Dimitrios, Ermioni Petraki, Panayiotis H. Yannakopoulos, Georgios Priniotakis, Ioannis Voyiatzis, and Demetrios Cantzos. "Long-Lasting Patterns in 3 kHz Electromagnetic Time Series after the ML = 6.6 Earthquake of 2018-10-25 near Zakynthos, Greece." Geosciences 10, no. 6 (2020): 235. http://dx.doi.org/10.3390/geosciences10060235.

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This paper reports one-month 3 kHz EM disturbances recorded at Kardamas, Ilia, Greece after a strong M L = 6.6 earthquake occurred on 2018/10/25 near Zakynthos and Ilia. During this period 17 earthquakes occurred with magnitudes M L = 4.5 and M L = 5.5 and depths between 3 km and 17 km, all near Zakynthos and Ilia. A two-stage, fully computational methodology was applied to the outcomes of five different time-evolving chaos analysis techniques (DFA, fractal dimension analysis through Higuchi, Katz and Sevcik methods and power-law analysis). Via literature-based thresholds, the out-of-threshold

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LI, JIN, XIAN ZHANG, JINZHE GONG, et al. "SIGNAL-NOISE IDENTIFICATION OF MAGNETOTELLURIC SIGNALS USING FRACTAL-ENTROPY AND CLUSTERING ALGORITHM FOR TARGETED DE-NOISING." Fractals 26, no. 02 (2018): 1840011. http://dx.doi.org/10.1142/s0218348x1840011x.

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A new technique is proposed for signal-noise identification and targeted de-noising of Magnetotelluric (MT) signals. This method is based on fractal-entropy and clustering algorithm, which automatically identifies signal sections corrupted by common interference (square, triangle and pulse waves), enabling targeted de-noising and preventing the loss of useful information in filtering. To implement the technique, four characteristic parameters — fractal box dimension (FBD), higuchi fractal dimension (HFD), fuzzy entropy (FuEn) and approximate entropy (ApEn) — are extracted from MT time-series.

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Gunay, Samet, and Kerem Kaşkaloğlu. "Seeking a Chaotic Order in the Cryptocurrency Market." Mathematical and Computational Applications 24, no. 2 (2019): 36. http://dx.doi.org/10.3390/mca24020036.

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In this study, we investigate the existence of chaos in the global cryptocurrency market. Specifically, we analyze parameters of chaotic order, nonlinearity, sensitivity to the initial conditions, monofractality, and multifractality. For this purpose, we conduct a comprehensive series of tests, including Brock–Dechert–Scheinkman (BDS) test, largest Lyapunov exponent, box-counting, and monogram analysis for fractal dimension, and multiple tests for long-range dependence (Aggregated Variances, Peng, Higuchi, R/S Analysis, and Multifractal Detrended Fluctuation Analysis (MFDFA)). All tests are pe

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Joy, R. Catherine, S. Thomas George, A. Albert Rajan, et al. "Detection and Classification of ADHD from EEG Signals Using Tunable Q-Factor Wavelet Transform." Journal of Sensors 2022 (September 15, 2022): 1–17. http://dx.doi.org/10.1155/2022/3590973.

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The automatic identification of Attention Deficit Hyperactivity Disorder (ADHD) is essential for developing ADHD diagnosis tools that assist healthcare professionals. Recently, there has been a lot of interest in ADHD detection from EEG signals because it seemed to be a rapid method for identifying and treating this disorder. This paper proposes a technique for detecting ADHD from EEG signals with the nonlinear features extracted using tunable Q-wavelet transform (TQWT). The 16 channels of EEG signal data are decomposed into the optimal amount of time-frequency sub-bands using the TQWT filter

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Brari, Zayneb, and Safya Belghith. "A Novel Machine Learning Model for the Detection of Epilepsy and Epileptic Seizures Using Electroencephalographic Signals Based on Chaos and Fractal Theories." Mathematical Problems in Engineering 2021 (August 9, 2021): 1–10. http://dx.doi.org/10.1155/2021/2107113.

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Machine learning is an expanding research area. Its main application is in the medical field and particularly the detection of epilepsy and epileptic seizures through electroencephalographic signals (EEG). It aims to design an intelligent framework that enables an immediate diagnosis of this disease without neurological consultation and thus saves the lives of the epileptic patients by detecting seizures and warning them before it happens. However, as a real-time application, this kind of framework faces several challenges such as accuracy, fast responses, and optimal memory usage. Within this

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