Article
Multidisciplinary Sciences
Javier Marin-Morales, Juan Luis Higuera-Trujillo, Jaime Guixeres, Carmen Llinares, Mariano Alcaniz, Gaetano Valenza
Summary: The study found differences in arousal and emotion recognition between real and virtual environments, with the support vector machine algorithm showing good performance in automatic arousal recognition.
Article
Mathematics, Applied
Boyi Zhang, Pengjian Shang, Xuegeng Mao, Jinzhao Liu
Summary: This paper proposes a dispersion heterogeneous recurrence analysis method for exploring the intrinsic characteristics and structure of complex systems. The method retains valuable information better than traditional recurrence plots and avoids the challenge of choosing a threshold. Experimental results demonstrate the ability of the method to detect changes in system characteristics and its potential for fault detection in railway vehicle systems.
COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION
(2023)
Article
Physics, Mathematical
Snir Ben Ovadia
Summary: In a Riemannian, boundaryless, and compact manifold with dim M >= 2, the existence of a hyperbolic SRB measure is linked to the presence of an unstable leaf containing hyperbolic points that return to a Pesin set with positive frequency. This observation provides an answer to a question raised by Pesin.
COMMUNICATIONS IN MATHEMATICAL PHYSICS
(2021)
Article
Mathematics, Applied
Venetia Voutsa, Michail Papadopoulos, Vicky Papadopoulou Lesta, Marc-Thorsten Huett
Summary: Stylized models of dynamical processes on graphs provide insights into the relationship between network architecture and dynamics across different disciplines. By translating dynamical observations into functional connectivity (FC) and comparing them quantitatively with structural connectivity (SC), we find that SC/FC relationships vary significantly with coupling strength in coupled logistic maps. Interestingly, noise enhances SC/FC correlations by creating a more uniform sampling of attractors. In terms of methodology, we introduce cellular automata as a data analysis tool for dynamics on graphs.
Article
Physics, Multidisciplinary
Pierre Bouny, Laurent M. Arsac, Emma Toure Cuq, Veronique Deschodt-Arsac
Summary: Recent research has revealed the existence of a networked system involving cortical and subcortical circuitry regulating cognition and cardiac autonomic control, which is dynamically organized based on cognitive demand. Entropy and (multi)fractality in heart period time series are suitable for capturing emergent behavior of the cognitive-autonomic network coordination.
Article
Mathematics, Applied
William C. Abram, Jeffrey C. Lagarias, Daniel J. Slonim
Summary: This paper investigates subsets of one-sided shift spaces on a finite alphabet, examining decimation and interleaving operations and their algebraic relations. Additionally, n-fold closure operations and weakly shift-stable sets are studied, along with their impact on entropy.
ADVANCES IN APPLIED MATHEMATICS
(2021)
Article
Mathematics, Applied
Nick Ramsey
Summary: This paper studies a finite type subshift S and a finite set S of finite words. It defines a subshift S(S) that avoids S and establishes a general criterion for bounding the entropy perturbation h(S) - h(S(S)) from above. As an application, it proves that this entropy difference tends to zero with a sequence of such sets S1, S2, ... under various assumptions on the S-i.
ERGODIC THEORY AND DYNAMICAL SYSTEMS
(2023)
Article
Biotechnology & Applied Microbiology
Lorenzo Frassineti, Antonio Lanata, Benedetta Olmi, Claudia Manfredi
Summary: The complex dynamics of neonatal seizures pose challenges for detection, while timely diagnosis and treatment are crucial for prognosis and neurodevelopment. Multiscale entropy analysis of heart rate variability shows promise as a valuable pre-screening tool for timely detection of seizure events in newborns.
BIOENGINEERING-BASEL
(2021)
Article
Biotechnology & Applied Microbiology
Benedetta Olmi, Claudia Manfredi, Lorenzo Frassineti, Carlo Dani, Silvia Lori, Giovanna Bertini, Cesarina Cossu, Maria Bastianelli, Simonetta Gabbanini, Antonio Lanata
Summary: This article introduces an ECG-based seizure detection system for newborns, using heart rate variability analysis as a marker. The results show that the system has comparable performance in detecting neonatal seizures.
BIOENGINEERING-BASEL
(2022)
Article
Acoustics
Zayrit Soumaya, Belhoussine Drissi Taoufiq, Nsiri Benayad, Korkmaz Yunus, Ammoumou Abdelkrim
Summary: Speech signals contain hidden information that can be used to identify speakers and detect neurological diseases. Evolutionary algorithms such as genetic algorithm GA and supervised machine learning like SVM were used in the study, resulting in an accuracy of 91.18%.
Article
Physics, Multidisciplinary
Mariano Matilla-Garcia, Isidro Morales, Jose Miguel Rodriguez, Manuel Ruiz Marin
Summary: Modeling and predicting chaotic time series require proper reconstruction of the state space by choosing appropriate time delay and embedding dimension. This paper proposes a simple method based on symbolic analysis and entropy to estimate time delays, showing better performance than traditional methods in numerical simulations. The method is validated on various chaotic time series, demonstrating its effectiveness for practitioners.
Article
Computer Science, Artificial Intelligence
Bilal Yaseen Al-Mualemi, Lu Lu
Summary: A machine learning-based scheme for fast and accurate sepsis identification is proposed in this study, which utilizes power spectrum and mean estimation for data classification and achieves good detection accuracy.
Article
Mathematics
Jerome Buzzi, Sylvain Crovisier, Omri Sarig
Summary: We prove that C-infinity-surface diffeomorphisms with positive topological entropy generally have only finitely many ergodic measures of maximal entropy, and exactly one in the topologically transitive case.
ANNALS OF MATHEMATICS
(2022)
Article
Multidisciplinary Sciences
Karolina Majerova, Milan Zvarik, Itay Ricon-Becker, Tsipi Hanalis-Miller, Iveta Mikolaskova, Vladimir Bella, Boris Mravec, Luba Hunakova
Summary: Experimental and clinical studies have shown that sympathetic nervous system stimulation can promote cancer progression and reduce treatment efficacy. Heart rate variability (HRV) can be used to identify cancer survivors with excessive sympathetic modulation. Non-linear HRV analysis appears to be more sensitive than linear analysis and can detect significant differences even in survivors after initial treatment.
SCIENTIFIC REPORTS
(2022)
Article
Physics, Multidisciplinary
Chang Yan, Peng Li, Meicheng Yang, Yang Li, Jianqing Li, Hongxing Zhang, Chengyu Liu
Summary: This study investigated the complexity or irregularity of RR interval time series in different sleep stages and explored their values in sleep staging. The results showed that entropy measures significantly varied across different sleep stages and played an important role in sleep staging.
Article
Medicine, General & Internal
Damaris Vazquez-Guevara, Sandra Badial-Ochoa, Karen M. Caceres-Rajo, Ildefonso Rodriguez-Leyva
Summary: This case report describes a middle-aged woman with symptoms of encephalitis after contracting COVID-19, including fever, neurological alterations, and characteristic brain features. The patient responded well to treatment and showed significant improvement upon discharge.
Review
Clinical Neurology
Ana A. Renteria-Palomo, Jose L. Montes-Ochoa, Adriana Martinez-Mayorga, Jorge Guillermo Reyes-Vaca, Ildefonso Rodriguez-Leyva
Summary: This study aimed to investigate the correlation between hippocampal atrophy and epilepsy severity in patients with temporal lobe epilepsy. The results showed a significant relationship between hippocampal volume loss and severity of epilepsy based on EEG evaluations.
FRONTIERS IN NEUROLOGY
(2021)
Article
Instruments & Instrumentation
Fabiola Leon-Bejarano, Martin O. Mendez, Alfonso Alba, Ildefonso Rodriguez-Leyva, Francisco J. Gonzalez, Maria del Carmen Rodriguez-Aranda, Edgar Guevara, Ricardo A. Guirado-Lopez, Miguel G. Ramirez-Elias
Summary: This study investigates the detection of aggregated alpha-synuclein in skin biopsies of Parkinson's disease patients using Raman spectroscopy. The results show significant frequency shifts and intensity variations in the Raman spectra of PD patients compared to healthy subjects, indicating changes in protein conformation and aggregation behavior. These findings suggest that Raman spectroscopy could be a valuable tool for diagnosing alpha-synuclein related diseases.
APPLIED SPECTROSCOPY
(2022)
Article
Medicine, General & Internal
Marcela Garcia-Villa, Arturo Gonzalez-Lara, Ildefonso Rodriguez-Leyva
Summary: Thunderclap headache is a severe and sudden-onset headache that can be caused by cerebrovascular or non-vascular life-threatening conditions. We present a case of cryptococcal meningitis in an immunocompetent patient with repetitive severe, abrupt-onset headaches.
Article
Medicine, General & Internal
Melissa Hernandez-Vega, Sandra Badial-Ochoa, Francisco Javier Rivas-Ruvalcaba, Ildefonso Rodriguez-Leyva
Summary: Kluver-Bucy syndrome is a rare neurobehavioral disorder characterized by various clinical manifestations, and it does not require all symptoms to be present for diagnosis.
Article
Medicine, General & Internal
Francisco Rivas Ruvalcaba, Katia Mabiel Moreno-Cortez, Sandra Badial-Ochoa, Ildefonso Rodriguez-Leyva
Summary: This article presents a case of a woman in her 40s who presented with hypertension and optic ataxia, and was diagnosed with transient headache and neurological deficits syndrome with cerebrospinal fluid lymphocytosis. The patient showed improvement after cerebrospinal fluid drainage and fully recovered 21 days after discharge.
Article
Mathematics, Interdisciplinary Applications
L. E. Mendez-Magdaleno, G. Dorantes-Mendez, S. Charleston-Villalobos, T. Aljama-Corrales, J. Gonzalez-Hermosillo, R. Gonzalez-Camarena
Summary: This study used the HUTT to assess the ANS regulation in VVS patients, and found that the VVS patients showed significant changes in cardiac vagal modulation and impaired sympathetic modulation to the vasculature during the orthostatic phase.
FLUCTUATION AND NOISE LETTERS
(2023)
Article
Medicine, General & Internal
Melissa Hernandez-Vega, Alejandro Orozco-Narvaez, Jorge Guillermo Reyes-Vaca, Ildefonso Rodriguez-Leyva
Summary: Neuromyelitis optica is an autoimmune disease that affects the central nervous system, primarily the optic nerve and spinal cord, and is associated with antibodies, complement cascade activation, and lymphocytic infiltration. There have been reports of inflammatory diseases of the central nervous system after SARS-CoV-2 vaccination, but the association with neuromyelitis optica remains unclear.
Article
Clinical Neurology
Ildefonso Rodriguez-Leyva, Karla Cantu-Flores, Arturo Dominguez-Frausto, Anna Elisabetta Vaudano, John Archer, Boris Bernhardt, Lorenzo Caciagli, Fernando Cendes, Yotin Chinvarun, Paolo Federico, William D. Gaillard, Eliane Kobayashi, Godwin Ogbole, Stefan Rampp, Irene Wang, Shuang Wang, Luis Concha
Summary: The ILAE Neuroimaging Task Force published educational case reports on neuroimaging in epilepsy. Neurocysticercosis is highly endemic in resource-limited countries and is increasingly seen in non-endemic regions due to migration. This article presents two cases with different clinical features to illustrate the varying severity of symptoms caused by this parasitic infestation, as well as examples of imaging characteristics that emphasize the central role of neuroimaging in diagnosing neurocysticercosis.
EPILEPTIC DISORDERS
(2023)
Article
Clinical Neurology
Marcela Garcia-Villa, Raul Leal-Cantu, Rosa G. Madrigal-Salas, Ildefonso Rodriguez-Leyva, Mariana A. Quintana-Diaz, Conne L. Gonzalez-Garcia
Summary: This study is the first registry in Michoacan to focus on the characteristics, development, and treatment of patients with Parkinson's disease (PD). The findings show that PD occurs without gender distinction in this population, and pharmacological treatment is the primary approach. Comprehensive management requires the support of rehabilitation, psychiatrists, and nutritionists.
REVISTA MEXICANA DE NEUROCIENCIA
(2022)
Review
Clinical Neurology
Laura Gil, Gabriela Capdeville, Ildefonso Rodriguez-Leyva, Sandra A. Nino, Maria E. Jimenez-Capdeville
Summary: Dementia, with Alzheimer's disease as its most common cause, has seen a significant increase in recent years. The nuclear origin of AD suggests that neuronal DNA repair mechanisms may lead to the accumulation of Tau protein in the cytoplasm, resulting in dementia.
REVISTA MEXICANA DE NEUROCIENCIA
(2021)
Review
Clinical Neurology
Jorge E. Guerrero-De Leon, Marco A. Zenteno-Castellanos, Angel Lee, Ildefonso Rodriguez-Leyva
Summary: This article reviews the diverse pathologies that can affect the spinal cord, emphasizing the importance of thorough clinical history and neurological examination in approaching these conditions. Neuroimaging studies are crucial for a better determination of the problem. The focus is on spinal vascular anatomy, pathogenesis and pathology of arteriovenous malformations, classification, imaging findings, and treatment approaches related to sAVMs due to their rare nature.
REVISTA MEXICANA DE NEUROCIENCIA
(2021)
Article
Engineering, Biomedical
Wenwen Wu, Yanqi Huang, Xiaomei Wu
Summary: In this study, a 2D deep learning classification network SRT was proposed to improve automatic ECG analysis. The model structure was enhanced with the CNN and Transformer-encoder modules, and a novel attention module and Dilated Stem structure were introduced to improve feature extraction. Comparative experiments showed that the proposed model outperformed several advanced methods.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2024)
Article
Engineering, Biomedical
Chiheb Jamazi, Ghaith Manita, Amit Chhabra, Houssem Manita, Ouajdi Korbaa
Summary: In this study, a new dynamic and intelligent clustering method for brain tumor segmentation is proposed by combining the improved Aquila Optimizer (AO) and the K-Means algorithm. The proposed MAO-Kmeans approach aims to automatically extract the correct number and location of cluster centers and the number of pixels in each cluster in abnormal MRI images, and the experimental results demonstrate its effectiveness in improving the performance of conventional K-means clustering.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2024)
Article
Engineering, Biomedical
Alberto Hernando, Maria Dolores Pelaez-Coca, Eduardo Gil
Summary: This study applied a new algorithm to decompose the photoplethysmogram (PPG) pulse and identified changes in PPG pulse morphology due to pressure. The results showed that there was an increase in amplitude, width, and area values of the PPG pulse, and a decrease in ratios when pressure increased, indicating vasoconstriction. Furthermore, some parameters were found to be related to the pulse-to-pulse interval.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2024)
Article
Engineering, Biomedical
Jens Moeller, Eveline Popanda, Nuri H. Aydin, Hubert Welp, Iris Tischoff, Carsten Brenner, Kirsten Schmieder, Martin R. Hofmann, Dorothea Miller
Summary: In this study, a method based on texture features is proposed, which can classify healthy gray and white matter against glioma degrees 4 samples with reasonable classification performance using a relatively low number of samples for training. The method achieves high classification performance without the need for large datasets and complex machine learning approaches.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2024)
Article
Engineering, Biomedical
Amrutha Bhaskaran, Manish Arora
Summary: The study evaluates a cyclic repetition frequency-based algorithm for fetal heart rate estimation. The algorithm improves accuracy and reliability for poor-quality signals and performs well for different gestation weeks and clinical settings.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2024)
Article
Engineering, Biomedical
Manan Patel, Harsh Bhatt, Manushi Munshi, Shivani Pandya, Swati Jain, Priyank Thakkar, Sangwon Yoon
Summary: Electroencephalogram (EEG) signals have been effectively used to measure and analyze neurological data and brain-related ailments. Artificial Intelligence (AI) algorithms, specifically the proposed CNN-FEBAC framework, show promising results in studying the EEG signals of autistic patients and predicting their response to stimuli with 91% accuracy.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2024)
Article
Engineering, Biomedical
Wencheng Gu, Kexue Sun
Summary: This research proposes an improved version of YOLOv5 (AYOLOv5) based on the attention mechanism to address the issue of low recognition rate in cell detection. Experimental results demonstrate that AYOLOv5 can accurately identify cell targets and improve the quality and recognition performance of cell pictures.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2024)
Article
Engineering, Biomedical
Anita Gade, V. Vijaya Baskar, John Panneerselvam
Summary: Analysis of exhaled breath is an increasingly used diagnostic technique in medicine. This study introduces a new NICBGM-based model that utilizes various features and weight optimization for accurate data interpretation and result optimization.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2024)
Article
Engineering, Biomedical
Arsalan Asemi, Keivan Maghooli, Fereidoun Nowshiravan Rahatabad, Hamid Azadeh
Summary: Biometric authentication systems can perform identity verification with optimal accuracy in various environments and emotional changes, while the performance of signature verification systems can be affected when people are under stress. This study examines the performance of a signature verification system based on muscle synergy patterns as biometric characteristics for stressed individuals. EMG signals from hand and arm muscles were recorded and muscle synergies were extracted using Non-Negative Matrix Factorization. The extracted patterns were classified using Support Vector Machine for authentication of stressed individuals.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2024)
Article
Engineering, Biomedical
Tianjiao Guo, Jie Yang, Qi Yu
Summary: This paper proposes a CNN-based approach for segmenting four typical DR lesions simultaneously, achieving competitive performance. This approach is significant for DR lesion segmentation and has potential in other segmentation tasks.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2024)
Article
Engineering, Biomedical
G. Akilandasowmya, G. Nirmaladevi, S. U. Suganthi, A. Aishwariya
Summary: This study proposes a technique for skin cancer detection and classification using deep hidden features and ensemble classifiers. By optimizing features to reduce data dimensionality and combining ensemble classifiers, the proposed method outperforms in skin cancer classification and improves prediction accuracy.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2024)
Article
Engineering, Biomedical
Tuuli Uudeberg, Juri Belikov, Laura Paeske, Hiie Hinrikus, Innar Liiv, Maie Bachmann
Summary: This article introduces a novel feature extraction method, the in-phase matrix profile (pMP), specifically adapted for electroencephalographic (EEG) signals, for detecting major depressive disorder (MDD). The results show that pMP outperforms Higuchi's fractal dimension (HFD) in detecting MDD, making it a promising method for future studies and potential clinical use for diagnosing MDD.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2024)
Article
Engineering, Biomedical
P. Nancy, M. Parameswari, J. Sathya Priya
Summary: Stroke is the third leading cause of mortality worldwide, and early detection is crucial to avoid health risks. Existing research on disease detection using machine learning techniques has limitations, so a new stroke detection system is proposed. The experimental results show that the proposed method achieves a high accuracy rate in stroke detection.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2024)
Article
Engineering, Biomedical
Shimin Liu, Zhiwen Huang, Jianmin Zhu, Baolin Liu, Panyu Zhou
Summary: In this study, a continuous blood pressure (BP) monitoring method based on random forest feature selection (RFFS) and a gray wolf optimization-gradient boosting regression tree (GWO-GBRT) prediction model was developed. The method extracted features from electrocardiogram (ECG) and photoplethysmography (PPG) signals, and employed RFFS to select sensitive features highly correlated with BP. A hybrid prediction model of gray wolf optimization (GWO) technique and gradient boosting regression tree (GBRT) algorithm was established to learn the relationship between BP and sensitive features. Experimental results demonstrated the effectiveness and advancement of the proposed method.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2024)
Article
Engineering, Biomedical
Weijun Gong, Yurong Qian, Weihang Zhou, Hongyong Leng
Summary: The recognition of dynamic facial expressions is challenging due to various factors, and obtaining discriminative expression features has been difficult. Traditional deep learning networks lack understanding of global and temporal expressions. This study proposes an enhanced spatial-temporal learning network to improve dynamic facial expression recognition.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2024)
