Article
Biology
Gianfranco Piccirillo, Federica Moscucci, Ilaria Di Diego, Martina Mezzadri, Cristina Caltabiano, Myriam Carnovale, Andrea Corrao, Ilaria Lospinuso, Sara Stefano, Claudia Scinicariello, Marco Giuffre, Valerio De Santis, Susanna Sciomer, Pietro Rossi, Emiliano Fiori, Damiano Magri
Summary: The autonomic nervous system (ANS) can modulate the oscillation of electrocardiogram segments and their intervals, including the myocardial repolarization phase. This study investigates the influence of head-up/-down tilt on ECG segments, suggesting that cardiopulmonary postural reflexes can modulate ECG interval oscillations. T wave amplitude decreases during head-up tilt and correlates with left ventricular end-systolic volume. Head-up/-down tilt acutely modifies the autonomic nervous system balance through deactivation of cardiopulmonary reflexes.
Article
Engineering, Biomedical
Slawomir Kujawski, Katarzyna Buszko, Agnieszka Cudnoch-Jedrzejewska, Joanna Slomko, Djordje G. Jakovljevic, Julia L. Newton, Pawel Zalewski
Summary: The impact of 31 hours of total sleep deprivation on cardiovascular autonomic modulation was evaluated in professional fire brigade officers. Results showed changes in heart rate and blood pressure entropy after TSD, indicating alterations in cardiac and vascular functioning. TSD also resulted in significant changes in blood pressure spectral analysis and entropy in response to orthostatic stress.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2021)
Article
Pediatrics
Ying Wang, Shuo Wang, Runmei Zou, Siyang Chen, Fang Li, Yuwen Wang, Yi Xu, Cheng Wang
Summary: This study investigated the relationship between unexplained chest pain in children and Head-up Tilt Test (HUTT). The results showed that HUTT-positive patients were older and females were more likely to be HUTT-positive. The study found that unexplained chest pain in children is mainly caused by an imbalanced autonomic nervous function.
FRONTIERS IN PEDIATRICS
(2022)
Article
Cardiac & Cardiovascular Systems
Jenni K. Koskela, Anna Tahvanainen, Antti J. Tikkakoski, Pauliina Kangas, Marko Uitto, Jari Viik, Mika Kahonen, Jukka Mustonen, Ilkka Porsti
Summary: Resting heart rate (HR) is related to heart rate variability (HRV), with higher resting HR associated with higher sympathovagal balance (LF/HF ratio) and lower resting HR associated with lower sympathovagal balance. The association of HR with HRV during head-up tilt remains significant, indicating that resting HR can predict HRV levels during tilt-testing.
SCANDINAVIAN CARDIOVASCULAR JOURNAL
(2022)
Article
Cardiac & Cardiovascular Systems
J. -N. Hoenemann, S. Moestl, A. Diedrich, E. Mulder, T. Frett, G. Petrat, W. Pustowalow, M. Arz, M. -T. Schmitz, K. Heusser, S. M. C. Lee, J. Jordan, J. Tank, F. Hoffmann
Summary: This study aimed to investigate the effectiveness of using artificial gravity (through short-arm centrifugation) on the adaptive changes in autonomic function during head-down tilt bed rest. The results showed that daily 30 minutes of artificial gravity did not prevent changes in autonomic cardiovascular control following 60 days of head-down tilt bed rest.
FRONTIERS IN CARDIOVASCULAR MEDICINE
(2023)
Review
Neurosciences
Konstantin G. Heimrich, Thomas Lehmann, Peter Schlattmann, Tino Prell
Summary: Recent evidence suggests that autonomic dysfunction, particularly in the vagus nerve, plays a significant role in the pathogenesis of Parkinson's disease. Heart rate variability analysis can be used to investigate cardiac activity regulation. Studies have shown that there may be decreased parasympathetic tone in patients with Parkinson's disease based on heart rate variability analysis.
Article
Biology
Gabriel Dias Rodrigues, Angelica Carandina, Costanza Scata, Chiara Bellocchi, Lorenzo Beretta, Pedro Paulo da Silva Soares, Eleonora Tobaldini, Nicola Montano
Summary: Systemic sclerosis (SSc) patients often experience cardiovascular autonomic dysfunction, leading to arrhythmic complications and mortality. This study aimed to evaluate the progression of cardiac autonomic impairment over time in different subsets of SSc patients. The results showed that the worsening of cardiac autonomic dysfunction was associated with the diffuse cutaneous (dcSSc) subset, which had a more extent of skin and internal organs fibrosis.
Article
Medicine, General & Internal
Malgorzata Maciorowska, Pawel Krzesinski, Robert Wierzbowski, Beata Uzieblo-Zyczkowska, Grzegorz Gielerak
Summary: This study assessed the correlation between heart rate variability (HRV) and the hemodynamic profile of arterial hypertension (AH) patients. The results showed that HRV parameters were correlated with arterial blood pressure, left ventricular function, and afterload.
JOURNAL OF CLINICAL MEDICINE
(2022)
Article
Engineering, Biomedical
Thais Marques da Silva, Carlos Alberto Aguiar Silva, Helio Cesar Salgado, Rubens Fazan Jr, Luiz Eduardo Virgilio Silva
Summary: The study investigated the influence of the autonomic nervous system on heart rate fragmentation (HRF) in rats. Results showed that sympathetic and parasympathetic influences similarly decrease HRF, with parasympathetic control markedly affecting the type of inflection points. Further studies are needed to explore the role of the autonomic nervous system in diseases marked by autonomic imbalance.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2021)
Review
Neurosciences
J. Galuszka, K. Vykoupil, M. Kaiserova, J. Zapletalova, M. Kamasova, D. Galuszkova, M. Taborsky
Summary: This study compared the analysis of heart rate variability during different phases and selected time periods of head-up tilt testing in patients with syncope history. The results showed statistically significant changes in heart rate variability parameters in the bradycardiac group within the first minute after termination of tilting. Ultra-short-term heart rate variability analysis in time periods directly related to syncope can provide more accurate assessment of autonomic regulation of blood circulation.
CESKA A SLOVENSKA NEUROLOGIE A NEUROCHIRURGIE
(2022)
Review
Sport Sciences
Alberto Calleja-Romero, German Vicente-Rodriguez, Nuria Garatachea
Summary: Running a long-distance race has a considerable acute effect on the autonomic nervous system, hemodynamics, and vascular properties, with a decrease in markers of parasympathetic activity, blood pressure, and arterial stiffness.
JOURNAL OF SPORTS SCIENCES
(2022)
Article
Physiology
Beatrice De Maria, Daniela Lucini, Mariana de Oliveira Gois, Aparecida Maria Catai, Francesca Perego, Mara Malacarne, Massimo Pagani, Alberto Porta, Laura Adelaide Dalla Vecchia
Summary: QT interval variability analysis can provide pathophysiological and prognostic information in cardiac and non-cardiac diseases, complementary to heart period variability analysis. Long-term moderate exercise can reduce cardiovascular risk and improve cardiac control complexity.
FRONTIERS IN PHYSIOLOGY
(2022)
Article
Clinical Neurology
Masashi Suzuki, Tomohiko Nakamura, Masaaki Hirayama, Masamichi Ueda, Mai Hatanaka, Yumiko Harada, Masahiro Nakatochi, Daisuke Nakatsubo, Satoshi Maesawa, Ryuta Saito, Koichi Fujiwara, Masahisa Katsuno
Summary: This study examined the HRV in Parkinson's disease patients using wearable sensors and found that the minimum values of SDNN and CVRR were significantly decreased in PD. Analyzing these minimum values in long-term recordings may be appropriate for detecting the decrease in HRV in PD.
JOURNAL OF NEURAL TRANSMISSION
(2022)
Article
Physiology
Rafal Pawlowski, Katarzyna Buszko, Julia L. Newton, Slawomir Kujawski, Pawel Zalewski
Summary: This study aimed to assess the cardiovascular system response to orthostatic stress in 133 healthy men using heart rate asymmetry methods. The research found that orthostatic stress affects the variability and asymmetry of human heart rate. Therefore, short-term HRA may serve as a potential tool to increase sensitivity in conditions where HUTT is a diagnostic tool.
FRONTIERS IN PHYSIOLOGY
(2021)
Article
Environmental Sciences
Minna Tang, Yu He, Xiaochun Zhang, Huichu Li, Chang Huang, Cuiping Wang, Ya Gao, Yinliang Li, Haidong Kan, Jialu Hu, Renjie Chen
Summary: The study found that temperature variability is negatively associated with heart rate variability, especially on the same day. The exposure-response relationships were almost linear for most parameters. The increase in temperature variability is significantly associated with the decrease in heart rate variability, with females being more affected.
ENVIRONMENTAL RESEARCH
(2021)
Article
Rehabilitation
Fabrizio Natali, Laura Corradini, Cristiano Sconza, Patricia Taylor, Raffaello Furlan, Stewart W. Mercer, Roberto Gatti
Summary: This study translated and cross-culturally adapted the CARE measure into Italian, and examined its validity and reliability in a rehabilitation setting. The results showed that the Italian version of the CARE measure had high face validity, internal reliability, and construct validity.
DISABILITY AND REHABILITATION
(2023)
Article
Computer Science, Interdisciplinary Applications
Davide Ottolina, Beatrice Cairo, Tommaso Fossali, Claudio Mazzucco, Antonio Castelli, Roberto Rech, Emanuele Catena, Alberto Porta, Riccardo Colombo
Summary: The study aimed to differentiate the impact of three ventilatory modes on cardiorespiratory phase coupling in critically ill patients. The highest synchronization was found during PCV ventilation, while the lowest was observed with NAVA. PCV induced a significant amount of cardiorespiratory phase synchronization, while patient-driven ventilatory modes had weaker synchronization, reaching the minimum with NAVA.
MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING
(2023)
Article
Physiology
Alberto Porta, Francesca Gelpi, Vlasta Bari, Beatrice Cairo, Beatrice De Maria, Anielle C. M. Takahashi, Aparecida M. M. Catai, Riccardo Colombo
Summary: This study proposes a model-based parametric approach for estimating the baroreflex bandwidth, which provides different information compared to baroreflex sensitivity. The method takes into account the action of mechanisms changing heart rate irrespective of systolic arterial pressure. The study found that the baroreflex bandwidth changes with different degrees of head-up tilt.
AMERICAN JOURNAL OF PHYSIOLOGY-REGULATORY, INTEGRATIVE AND COMPARATIVE PHYSIOLOGY
(2023)
Article
Physics, Multidisciplinary
Alberto Porta, Vlasta Bari, Francesca Gelpi, Beatrice Cairo, Beatrice De Maria, Davide Tonon, Gianluca Rossato, Luca Faes
Summary: Nonlinear markers of coupling strength are utilized to typify cardiorespiratory and cerebrovascular regulations, and the computation of these indices requires techniques describing nonlinear interactions between respiration and heart period, and between mean arterial pressure and mean cerebral blood velocity. Two model-free methods, cross-sample entropy (CSampEn) and k-nearest-neighbor cross-unpredictability (KNNCUP), were compared for assessing dynamic interactions. The study found that KNNCUP is more reliable than CSampEn in evaluating coupling strength when interactions occur according to a causal structure, and it is more powerful in characterizing cardiorespiratory and cerebrovascular variability interactions in healthy subjects.
Article
Biophysics
Francesca Gelpi, Vlasta Bari, Beatrice Cairo, Beatrice De Maria, Rachel Wells, Mathias Baumert, Alberto Porta
Summary: Transfer entropy was used to assess the interactions between cardiovascular and cerebrovascular variabilities, revealing an exaggerated sympathetic response in POTS subjects and impairments in baroreflex activation. This study highlights the importance of evaluating specific regulatory mechanisms and sensitivity to different respiratory aspects.
PHYSIOLOGICAL MEASUREMENT
(2023)
Article
Biophysics
Alberto Porta, Beatrice Cairo, Vlasta Bari, Francesca Gelpi, Beatrice De Maria, Riccardo Colombo
Summary: This study investigates the variability between heart rate (HP) and systolic arterial pressure (SAP) in healthy men during head-down tilt (HDT) using model-based spectral causality analysis. The findings suggest that HDT reduces the involvement of the baroreflex in regulating the relationship between HP and SAP in the low frequency band, but does not affect the action of mechanical feedforward mechanisms in both low and high frequency bands.
PHYSIOLOGICAL MEASUREMENT
(2023)
Article
Chemistry, Analytical
Monica Parati, Matteo Gallotta, Beatrice De Maria, Annalisa Pirola, Matteo Morini, Luca Longoni, Emilia Ambrosini, Giorgio Ferriero, Simona Ferrante
Summary: This study discusses the use of smartphone applications to measure knee joint ROM during walking and tests the reliability, validity, and usability of the collected measurements. The results show that both applications have good reliability, validity, and usability, making them suitable for assessing knee ROM in neurological patients.
Article
Clinical Neurology
Simone Toffoli, Francesca Lunardini, Monica Parati, Matteo Gallotta, Beatrice De Maria, Luca Longoni, Maria Elisabetta Dell'Anna, Simona Ferrante
Summary: This study presents a novel smart ink pen for spiral drawing assessment, aiming to better characterize Parkinson's disease motor symptoms. The device, used on paper as a normal pen, is enriched with motion and force sensors. Machine learning classification models were applied to test the indicators' ability to discriminate between Parkinsonian patients and age-matched controls. The results showed that the indicators were able to significantly identify Parkinson's disease motor symptoms, supporting the introduction of the smart ink pen as a time-efficient tool to complement clinical assessment.
FRONTIERS IN NEUROLOGY
(2023)
Article
Biophysics
Beatrice De Maria, Laura Adelaide Dalla Vecchia, Vlasta Bari, Beatrice Cairo, Francesca Gelpi, Francesca Perego, Anielle Christine Medeiros Takahashi, Juliana Cristina Milan-Mattos, Vinicius Minatel, Patricia Rehder-Santos, Murray Esler, Elisabeth Lambert, Mathias Baumert, Aparecida Maria Catai, Alberto Porta
Summary: This study found that the level of cardiac and sympathetic baroreflex engagement decreases with age and increases with postural stimulus intensity. Additionally, postural challenge magnitude leads to an increase in the percentages of sympathetic baroreflex patterns. Interestingly, the involvement of the cardiac and sympathetic arms of the baroreflex is not influenced by the absolute value or direction of arterial pressure changes.
PHYSIOLOGICAL MEASUREMENT
(2023)
Article
Biophysics
Vlasta Bari, Francesca Gelpi, Beatrice Cairo, Martina Anguissola, Sara Pugliese, Beatrice De Maria, Enrico Giuseppe Bertoldo, Valentina Fiolo, Edward Callus, Carlo De Vincentiis, Marianna Volpe, Raffaella Molfetta, Marco Ranucci, Alberto Porta
Summary: This study aimed to characterize the cardiovascular (CV) and cerebrovascular (CBV) controls in aortic valve stenosis (AVS) patients before and after surgical aortic valve replacement (SAVR). The study found that CV regulation is impaired in AVS patients, worsens after SAVR, and recovers after a three-month follow-up. However, CBV regulation remains preserved in AVS patients and is not affected by SAVR. The findings suggest the importance of monitoring CV and CBV controls in AVS patients and evaluating the effects of SAVR on these controls.
PHYSIOLOGICAL MEASUREMENT
(2023)
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)