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arXiv 2025年

作者： Bhagubai, Miguel Chatzichristos, Christos Swinnen, Lauren Macea, Jaiver Zhang, Jingwei Lagae, Lieven Jansen, Katrien Schulze-Bonhage, Andreas Sales, Francisco Mahler, Benno Weber, Yvonne Van Paesschen, Wim De Vos, Maarten STADIUS Center for Dynamical Systems Signal Processing and Data Analytics KU Leuven Leuven3001 Belgium Laboratory for Epilepsy Research UZ Leuven Leuven3000 Belgium Department of Development and Regeneration KU Leuven Leuven3000 Belgium Department of Pediatric Neurology UZ Leuven Leuven3000 Belgium Epilepsy Center University Medical Center Freiburg University Freiburg79106 Germany Epilepsy Reference Center Coimbra University Hospital Coimbra3004-504 Portugal Department of Neurology Karolinska University Hospital Stockholm171 77 Sweden Department of Epileptology and Neurology RWTH University of Aachen Aachen52074 Germany

The increasing technological advancements towards miniaturized physiological measuring devices have enabled continuous monitoring of epileptic patients outside of specialized environments. The large amounts of data that can be recorded with such devices holds significant potential for developing automated seizure detection frameworks. In this work, we present SeizeIT2, the first open dataset of wearable data recorded in patients with focal epilepsy. The dataset comprises more than 11,000 hours of multimodal data, including behind-the-ear electroencephalography, electrocardiography, electromyography and movement (accelerometer and gyroscope) data. The dataset contains 886 focal seizures recorded from 125 patients across five different European Epileptic Monitoring Centers. We present a suggestive training/validation split to propel the development of AI methodologies for seizure detection, as well as two benchmark approaches and evaluation metrics. The dataset can be accessed on OpenNeuro and is stored in Brain Imaging data Structure (BIDS) format. © 2025, CC BY-NC-ND.

关键词： Electroencephalography

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Upregulation of IL-4 receptor signaling pathway in circulating ILC2s from asthma patients

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Journal of Allergy and Clinical Immunology: Global 2022年第4期1卷 299-304页

作者： Baba, Rie Kabata, Hiroki Shirasaki, Yoshitaka Kamatani, Takashi Yamagishi, Mai Irie, Misato Watanabe, Risa Matsusaka, Masako Masaki, Katsunori Miyata, Jun Moro, Kazuyo Uemura, Sotaro Fukunaga, Koichi Division of Pulmonary Medicine Department of Medicine Keio University School of Medicine Tokyo Japan Graduate School of Pharmaceutical Sciences The University of Tokyo Tokyo Japan Laboratory for Medical Science Mathematics Department of Biological Sciences Graduate School of Science The University of Tokyo Tokyo Japan Department of AI Technology Development M&D Data Science Center Tokyo Medical and Dental University Tokyo Japan Division of Precision Cancer Medicine Tokyo Medical and Dental University Hospital Tokyo Japan Live Cell Diagnosis Ltd Saitama Asaka Japan Division of Infectious Diseases and Respiratory Medicine Department of Internal Medicine National Defense Medical College Saitama Japan Laboratory for Innate Immune Systems RIKEN Center for Integrative Medical Sciences Kanagawa Yokohama Japan Laboratory for Innate Immune Systems Department of Microbiology and Immunology Graduate School of Medicine Osaka University Osaka Suita Japan Laboratory for Innate Immune Systems Immunology Frontier Research Center Osaka University Osaka Suita Japan Department of Biological Sciences Graduate School of Science The University of Tokyo Tokyo Japan

Background: Group 2 innate lymphoid cells (ILC2s) produce type 2 cytokines by stimulation with epithelial cell–derived cytokines and are implicated in the pathogenesis of various allergic diseases, including asthma. However, differences in the molecular characteristics of ILC2s between patients with asthma and healthy subjects remain unclear. Objective: We sought to evaluate differences in cytokine production capacity and gene expression profile of ILC2s in the peripheral blood of patients with asthma and healthy subjects. Methods: We evaluated ILC2s derived from 15 patients with asthma and 7 healthy subjects using flow cytometry, live-cell imaging of secretion activity analysis, and RNA-sequencing. Results: ILC2s were sorted as CD45⁺Lineage⁻CRTH2⁺CD127⁺CD161⁺ cells from the peripheral blood of patients with asthma and healthy subjects, and the number of ILC2s was decreased in patients with asthma (851 ± 1134 vs 2679 ± 3009 cells/20 mL blood;P = .0066). However, patient-derived ILC2s were activated to produce more IL-5 and IL-13 in response to stimulation with IL-2, IL-33, and thymic stromal lymphopoietin compared with healthy subject–derived ILC2s (P = .0032 and P = .0085, respectively). Furthermore, RNA-sequencing analysis revealed that patient-derived ILC2s had different gene expression profiles, such as increased expression in cell growth–related genes (CDKN1b, CCNG2, CCND2, CCN1), prostaglandin E receptor (PTGER2), and IL-4 receptor. In addition, a gene set of the IL-4 receptor signaling pathway was significantly upregulated in ILC2s in patients with asthma (P = .042). Conclusions: Our results suggest that circulating ILC2s in patients with asthma are preactivated via the IL-4 receptor signaling pathway and produce IL-5 and IL-13 vigorously by stimulation. © 2022 The Author(s)

关键词： Asthma biomarker group 2 innate lymphoid cells live cell imaging

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Understanding Social Inequalities in Childhood Asthma: Quantifying the Mediating Role of Modifiable Early-Life Risk Factors in Seven European Birth Cohorts

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Journal of Allergy and Clinical Immunology: In Practice 2025年第6期13卷 1385-1396页

作者： Pinot de Moira, Angela Aurup, Anne V. Avraam, Demetris Zugna, Daniela Jensen, Aksel Karl Georg Welten, Marieke Cadman, Timothy de Lauzon-Guillain, Blandine Duijts, Liesbeth Elhakeem, Ahmed Esplugues, Ana Garcia-Aymerich, Judith García-Baquero, Gonzalo González Safont, Llúcia Harris, Jennifer R. Iñiguez, Carmen Jaddoe, Vincent W.V. McEachan, Rosemary R.C. Nader, Johanna L.T. Santa Marina, Loreto Swertz, Morris A. Tafflet, Muriel Vrijheid, Martine Wright, John Yang, Tiffany C. Taylor-Robinson, David Richiardi, Lorenzo Nybo Andersen, Anne-Marie School of Public Health Imperial College London London United Kingdom Department of Public Health University of Copenhagen Copenhagen Denmark Department of Nutrition Exercise and Sports University of Copenhagen Copenhagen Denmark Department of Public Health Policy and Systems University of Liverpool Liverpool United Kingdom Cancer Epidemiology Unit Department of Medical Sciences University of Turin Turin Italy Department of Pediatrics Erasmus MC University Medical Center Rotterdam Rotterdam Netherlands Generation R Study Group Erasmus MC University Medical Center Rotterdam Rotterdam Netherlands Genomics Coordination Center University Medical Center Groningen University of Groningen Groningen Netherlands Department of Genetics University Medical Center Groningen University of Groningen Groningen Netherlands Université Paris Cité and Université Sorbonne Paris Nord INSERM INRAE Centre for Research in Epidemiology and Statistics Paris France Population Health Science Bristol Medical School Bristol United Kingdom MRC Integrative Epidemiology Unit at the University of Bristol Bristol United Kingdom Spanish Consortium for Research on Epidemiology and Public Health (CIBERESP) Madrid Spain Department of Nursing University of Valencia Valencia Spain Epidemiology and Environmental Health Joint Research Unit the Foundation for the Promotion of Health and Biomedical Research of Valencia Region Universitat Jaume I-Universitat de València Valencia Spain Barcelona Institute for Global Health (ISGlobal) Barcelona Spain Universitat Pompeu Fabra (UPF) Barcelona Spain CEADIR Faculty of Biology University of Salamanca Campus Miguel de Unamuno Avda Licenciado Méndez Nieto s/n Salamanca Spain Biodonostia Environmental Epidemiology and Child Development Group San Sebastian Spain Centre for Fertility and Health Norwegian Institute of Public Health Oslo Norway Department of Statistics and Operational Research Universitat de València València Spain Bradford Institute f

Background: Children growing up in disadvantaged socioeconomic circumstances (SECs) have an increased risk of asthma. Objective: To increase our understanding of the pathways to inequalities in asthma and potential targets for intervention by (1) examining how the social patterning of asthma and its early-life risk factors varies across countries and (2) quantifying the mediation of observed inequalities by early-life risk factors. Methods: We used data for 107,884 mother-child dyads from 7 European birth cohorts across 6 countries. Maternal education was the primary exposure measure of early-life SECs. The outcome was current asthma in childhood (3-12 years). Inequalities were examined using multivariable regression and random effects meta-analysis. The mediating effects of early-life risk factors (maternal smoking during pregnancy, adverse birth outcomes, and breastfeeding duration) were examined using counterfactual mediation analysis. Results: In meta-analysis, children of mothers with low/medium versus high education had a 17% (95% confidence interval: 8%-27%, I² = 21.6%) increased risk of asthma. Cohort-specific risk ratios ranged between 1.07 (0.97-1.18, Danish National Birth Cohort, Denmark) and 1.61 (1.08-2.40, study on the pre- & early postnatal determinants of child health & development, France). The early-life risk factors were similarly socially patterned, but with greater heterogeneity across cohorts (I² range = 66.2%-95.3%). The mediation analysis suggested that these factors play a relevant role in mediating observed inequalities (proportion mediated range: 0.08-0.72). Conclusions: There was a consistent tendency for children from disadvantaged SECs to be at greater risk of asthma in the European cohorts examined. Our results suggest that early-life risk factors partially mediate these disparities and, therefore, that public health interventions in the perinatal period may help to address inequalities in asthma. © 2025 The Autho

关键词： Birth cohort Childhood asthma Cross-cohort Inequalities Meta-analysis Socioeconomic

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Landscape dynamic network biomarker analysis reveals the tipping point of transcriptome reprogramming to prevent skin photodamage

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Journal of Molecular Cell Biology 2021年第11期13卷 822-833页

作者： Chengming Zhang Hong Zhang Jing Ge Tingyan Mi Xiao Cui Fengjuan Tu Xuelan Gu Tao Zeng Luonan Chen State Key Laboratory of Cell Biology Shanghai Institute of Biochemistry and Cell BiologyCenter for Excellence in Molecular Cell ScienceChinese Academy of SciencesShanghai 200031China University of the Chinese Academy of Sciences Chinese Academy of SciencesBeijing 100049China Unilever Research&Development Centre Shanghai Shanghai 200335China Bio-Med Big Data Center Shanghai Institute of Nutrition and HealthUniversity of Chinese Academy of SciencesChinese Academy of SciencesShanghai 200031China School of Life Science and Technology ShanghaiTech UniversityShanghai 201210China Key Laboratory of Systems Health Science of Zhejiang Province Hangzhou Institute for Advanced StudyUniversity of Chinese Academy of SciencesChinese Academy of SciencesHangzhou 310024China Guangdong Institute of Intelligence Science and Technology Zhuhai 519031China

Skin,as the outmost layer of human body,is frequently exposed to environmental stressors including pollutants and ultraviolet(UV),which could lead to skin ***,skin response process to ultraviolet B(UVB)irradiation is a nonlinear dynamic process,with unknown underlying molecular mechanism of critical ***,the landscape dynamic network biomarker(lDNB)analysis of time series transcriptome data on 3D skin model was conducted to reveal the complicated process of skin response to UV irradiation at both molecular and network *** advanced l-DNB analysis approach showed that:(i)there was a tipping point before critical transition state during pigmentation process,validated by 3D skin model;(ii)13 core DNB genes were identified to detect the tipping point as a network biomarker,supported by computational assessment;(iii)core DNB genes such as COL7A1 and CTNNB1 can effectively predict skin lightening,validated by independent human skin ***,this study provides new insights for skin response to repetitive UVB irradiation,including dynamic pathway pattern,biphasic response,and DNBs for skin lightening change,and enables us to further understand the skin resilience process after external stress.

关键词： single-sample network tipping point UVB irradiation living skin equivalent model time series data skin lightening

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systems biology approach reveals succinyl-CoA and hydroxycitrate as potential therapeutics for the treatment of vulvovaginal candidiasis

Next Research

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Next research 2025年第2期2卷

作者： Abhishek Sengupta Sudeepti Kulshrestha Ritu Redhu Ankur Chaurasia Payal Gupta Muskan Syed Pooja Vijayaraghavan Somesh Gupta Priyanka Narad Systems Biology and Data Analytics Research Lab Amity Institute of Biotechnology Amity University Uttar Pradesh Noida 201313 India Anti-mycotic Drug Susceptibility Laboratory Amity Institute of Biotechnology Amity University Noida India Department of Dermatology & Venereology All India Institute of Medical Sciences New Delhi India Division of Development Research Indian Council of Medical Research Ansari Nagar New Delhi India

Vulvovaginal candidiasis (VVC) is a prevalent fungal infection characterized by Candida species ’ proliferation in the female reproductive system. This study focuses on the identification of therapeutic targets in pathogenic Candida strains, specifically targeting the C. albicans WO-1 strain. We employed an extensive in-silico pipeline including critical studies, including Human Non-Homolog Protein discovery, Human Vaginal Metagenome screening, and Subcellular Localization prediction using Psort and Deeploc. Subsequently, network construction was performed, and hub genes were identified within the fungal biological system usingtc Cytoscape's cytohubba plugin. This was followed by the prediction of ADME properties, molecular docking, and molecular dynamics (MD) simulations of the top five docked complexes using Schrödinger software. CIT1 was identified as the most effective therapeutic target, while succinyl-CoA and Hydroxycitrate were identified as potential drugs for VVC treatment. This approach offers a comprehensive approach to combating infections caused by the C. albicans WO-1 strain.

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IMU-Based Monitoring for Assistive Disease Diagnosis and Management of IoHT: A Review

TechRxiv

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TechRxiv 2022年

作者： Bo, Fan Yerebakan, Mustafa Dai, Yanning Wang, Weibing Li, Jia Gao, Shuo Hu, Boyi The Smart Sensing Research and Development Center Institute of Microelectronics Chinese Academy of Sciences Beijing100029 China The School of Microelectronics University of Chinese Academy of Sciences Beijing100049 China The School of Instrumentation and Optoelectronic Engineering Beihang University Beijing100191 China The Beijing Advanced Innovation Center for Big Data-Based Precision Medicine Beihang University Beijing100191 China The Department of Industrial and Systems Engineering University of Florida GainesvilleFL32611 United States

With the rapid development of Internet of Things (IoT) technologies, traditional disease diagnosis carried out in medical institutions can now be performed remotely at home or even ambient environments, yielding the concept of Internet of Health Things (IoHT). Among the diverse IoHT applications, inertial measurement units (IMUs) based systems play a significant role in the detection of diseases in many fields, such as neurological, musculoskeletal, and mental. However, traditional numerical interpretation methods have proven to be challenging to provide satisfying detection accuracies owing to the low quality of raw data especially under strong electromagnetic interference (EMI). To address this issue, in recent years, machine learning (ML) based techniques have been proposed to smartly map IMU captured data on disease detection and progress. After a decade of development, the combination of IMUs and ML algorithms for assistive disease diagnosis has become a hot topic, with an increasing number of studies reported yearly. To help readers comprehensively understand the fundamentals and state-of-the-art techniques, this article systematically reviews this field, by introducing and explaining relevant application scenarios, discussing challenges, and predicting foreseeable future trends. © 2022, CC BY.

关键词： Machine learning

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Enhancement of Security in IoT using Secure Hash Cryptography Algorithm with Double Encryption (SHCA-DE)

Enhancement of Security in IoT using Secure Hash Cryptograph...

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International Conference on Communication and Electronics systems (ICCES)

作者： G. Uganya D. Rajalakshmi Ramarao Vangapandu M. Dinesh Jayant Giri Mahmoud Odeh Department of ECE Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai India Department of Data Science and Business Systems SRM Institute of Science and Technology Kattankulathur Chennai Department of Computer Science and Engineering Vignan's Institute of Engineering for Women Vishakhapatnam Department of VLSI Microelectronics Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences (SIMATS) Saveetha University Chennai Department of Mechanical Engineering Yeshwantrao Chavan College of Engineering Nagpur Division of Research and Development Lovely Professional University Phagwara India Department of Cyber Security Faculty of Information Technology Zarqa University Zarqa Jordan University of Business and Technology Jeddah Saudi Arabia

ISBN: (数字)9798350377972

ISBN: (纸本)9798350377989

The “Internet of things” is the developing technology to transfer the world into smart innovation. “IoT” security is the most problematic issue in recent applications due to its properties including ‘centralized architecture’, ‘limited capacity devices’, and ‘ambiguity’. So, blockchain with “IoT” applications provides secure data communication compared to traditional “IoT” applications. Blockchain is a recent growing technology that has features including ‘decentralized structure’, ‘transparency’, ‘immutable records’, ‘increased capacity’, and ‘quick backtracks’. The ‘cryptography hash algorithm’ is very important to provide secure data transmission. It converted the different size input to fixed-size unalterable output to enhance the security. But still, it needs efficient algorithm to secure data transmission with safeguard of private key. The objective of this paper is to propose a secure hash cryptography algorithm with double encryption (SHCA-DE) to protect the private key message. Then, this proposed algorithm has been analyzed with MD5, SHA-256, and SHA3-512. From this analysis, the SHA3-512 performs well with proposed algorithm.

关键词： Hash functions Technological innovation Accuracy Public key cryptography Blockchains Encryption Internet of Things data communication

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Stable Isotope Evidence Indicates Human Activities Dominate Riverine Nitrogen Sources in the Yellow River Headwater Region

SSRN

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SSRN 2025年

作者： Liu, Wei Li, Baolin Yuan, Yecheng Ma, Guangwen Li, Rui Zhu, Jie Jiang, Yuhao Xu, Jie Tan, Qiuyuan Sun, Qingling State Key Laboratory of Resources and Environmental Information Systems Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing100101 China University of Chinese Academy of Sciences Beijing100049 China Jiangsu Center of Collaborative Innovation in Geographical Information Resource Development and Application Nanjing210023 China State Environment Protection Key Laboratory of Environmental Monitoring Quality Control China National Environmental Monitoring Centre Beijing100012 China Academy of Forest Inventory and Planning National Forestry and Grassland Administration Beijing100013 China Guangdong Province Data Center of Terrestrial and Marine Ecosystems Carbon Cycle Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies School of Atmospheric Sciences Sun Yat-sen University Guangdong Zhuhai519082 China

The Qinghai-Tibetan Plateau, known as the "Asian Water Tower," is critical for providing drinking water, making the protection of its water quality essential. However, higher nitrogen concentrations and its rapid increase have been observed, with riverine nitrogen sources remaining controversial. To address it, this study integrated dual isotopes of - and - to assess the relative contributions of various nitrogen sources using the MixSIAR model. The values from different source samples showed significant variation (p © 2025, The Authors. All rights reserved.

关键词： Rivers

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Improved Fitness Dependent Optimizer for Solving Economic Load Dispatch Problem

arXiv

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arXiv 2022年

作者： Tahir, Barzan Hussein Rashid, Tarik A. Rauf, Hafiz Tayyab Bacanin, Nebojsa Chhabra, Amit Vimal, S. Yaseen, Zaher Mundher Department of Computer Science and Engineering University of Kurdistan Helwer Erbil Iraq Centre for Smart Systems AI and Cybersecurity Staffordshire University Stoke-on-Trent United Kingdom Singidunum University Danijelova 32 Belgrade11000 Serbia Department of Computer Engineering and Technology Guru Nanak Dev University Amritsar India Department of Artificial Intelligence and Data Science Ramco Institute of Technology North Venganallur Village Virudhunagar District Tamilnadu Rajapalayam626 117 India Department of Earth Sciences and Environment Faculty of Science and Technology Universiti Kebangsaan Malaysia Selangor Bangi43600 Malaysia USQ's Advanced Data Analytics Research Group School of Mathematics Physics and Computing University of Southern Queensland QLD4350 Australia New era and Development in Civil Engineering Research Group Scientific Research Center Al-Ayen University Thi-Qar64001 Iraq

Economic Load Dispatch depicts a fundamental role in the operation of power systems, as it decreases the environmental load, minimizes the operating cost, and preserves energy resources. The optimal solution to Economic Load Dispatch problems and various constraints can be obtained by evolving several evolutionary and swarm-based algorithms. The major drawback to swarm-based algorithms is premature convergence towards an optimal solution. Fitness Dependent Optimizer is a novel optimization algorithm stimulated by the decision-making and reproductive process of bee swarming. Fitness Dependent Optimizer (FDO) examines the search spaces based on the searching approach of Particle Swarm Optimization. To calculate the pace, the fitness function is utilized to generate weights that direct the search agents in the phases of exploitation and exploration. In this research, the authors have carried out Fitness Dependent Optimizer to solve the Economic Load Dispatch problem by reducing fuel cost, emission allocation, and transmission loss. Moreover, the authors have enhanced a novel variant of Fitness Dependent Optimizer, which incorporates novel population initialization techniques and dynamically employed sine maps to select the weight factor for Fitness Dependent Optimizer. The enhanced population initialization approach incorporates a quasi-random Sabol sequence to generate the initial solution in the multi-dimensional search space. A standard 24-unit system is employed for experimental evaluation with different power demands. Empirical results obtained using the enhanced variant of the Fitness Dependent Optimizer demonstrate superior performance in terms of low transmission loss, low fuel cost, and low emission allocation compared to the conventional Fitness Dependent Optimizer. The experimental study obtained 7.94E-12, the lowest transmission loss using the enhanced Fitness Dependent Optimizer. Correspondingly, various standard estimations are used to prove the stability

关键词： Decision making

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Multimodal wearable EEG, EMG and accelerometry measurements improve the accuracy of tonic-clonic seizure detection in-hospital

arXiv

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arXiv 2024年

作者： Zhang, Jingwei Swinnen, Lauren Chatzichristos, Christos Broux, Victoria Proost, Renee Jansen, Katrien Mahler, Benno Zabler, Nicolas Epitashvilli, Nino Dümpelmann, Matthias Schulze-Bonhage, Andreas Schriewer, Elisabeth Ermis, Ummahan Wolking, Stefan Linke, Florian Weber, Yvonne Symmonds, Mkael Sen, Arjune Biondi, Andrea Richardson, Mark P. Sulaiman, Abuhaiba I. Silva, Ana Isabel Sales, Francisco Vértes, Gergely Van Paesschen, Wim De Vos, Maarten STADIUS Center for Dynamical Systems Signal Processing and Data Analytics KU Leuven Leuven Belgium Laboratory for Epilepsy Research KU Leuven Leuven Belgium Reference Center for Refractory epilepsy Department of Neurology UZ Leuven Leuven Belgium Department of Pediatric Neurology UZ Leuven Leuven Belgium Department of Development and Regeneration KU Leuven Leuven Belgium Department of Neurology Karolinska University Hospital Stockholm Sweden Epilepsy Center Department of Neurosurgery Medical Center University of Freiburg Breisgau Freiburg Germany Department of Epileptology and Neurology University of Aachen Aachen Germany Oxford Epilepsy Research Group NIHR Biomedical Research Centre Nuffield Department of Clinical Neurosciences University of Oxford Oxford United Kingdom Department of Basic and Clinical Neuroscience Institute of Psychiatry Psychology and Neuroscience King's College London London United Kingdom Neurology Department Coimbra Hospital and University Centre Coimbra Portugal Epilepsy Seizure Detection Neurology UCB Pharma Brussels Belgium

Objective: Most current wearable tonic-clonic seizure (TCS) detection systems are based on extra-cerebral signals, such as electromyography (EMG) or accelerometry (ACC). Although many of these devices show good sensitivity in seizure detection, their false positive rates (FPR) are still relatively high. Wearable EEG may improve performance;however, studies investigating this remain scarce. This paper aims 1) to investigate the possibility of detecting TCSs with a behind-the-ear, two-channel wearable EEG, and 2) to evaluate the added value of wearable EEG to other non-EEG modalities in multimodal TCS detection. Method: We included 27 participants with a total of 44 TCSs from the European multicenter study SeizeIT2. The multimodal wearable detection system Sensor Dot (Byteflies) was used to measure two-channel, behind-the-ear EEG, EMG, electrocardiography (ECG), ACC and gyroscope (GYR). First, we evaluated automatic unimodal detection of TCSs, using performance metrics such as sensitivity, precision, FPR and F1-score. Secondly, we fused the different modalities and again assessed performance. Algorithm-labeled segments were then provided to a neurologist and a wearable data expert, who reviewed and annotated the true positive TCSs, and discarded false positives (FPs). Results: Wearable EEG outperformed the other modalities in unimodal TCS detection by achieving a sensitivity of 100.0% and a FPR of 10.3/24h (compared to 97.7% sensitivity and 30.9/24h FPR for EMG;95.5% sensitivity and 13.9 FPR for ACC). The combination of wearable EEG and EMG achieved overall the most clinically useful performance in offline TCS detection with a sensitivity of 97.7%, a FPR of 0.4/24 h, a precision of 43.0%, and a F1-score of 59.7%. Subsequent visual review of the automated detections resulted in maximal sensitivity and zero FPs. Significance: In TCS detection with a wearable device, the main advantage of combining EEG with ACC, EMG or both was a marked reduction in FPR, while retaining

关键词： Electrocardiography

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