Relevant bibliographies by topics / Clinical EEG data

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Clinical EEG data'

Author: Grafiati
Published: 1 June 2024
Last updated: 31 July 2025

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Journal articles on the topic "Clinical EEG data"

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Antony, Mary Judith, Baghavathi Priya Sankaralingam, Shakir Khan, Abrar Almjally, Nouf Abdullah Almujally, and Rakesh Kumar Mahendran. "Brain–Computer Interface: The HOL–SSA Decomposition and Two-Phase Classification on the HGD EEG Data." Diagnostics 13, no. 17 (2023): 2852. http://dx.doi.org/10.3390/diagnostics13172852.

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An efficient processing approach is essential for increasing identification accuracy since the electroencephalogram (EEG) signals produced by the Brain–Computer Interface (BCI) apparatus are nonlinear, nonstationary, and time-varying. The interpretation of scalp EEG recordings can be hampered by nonbrain contributions to electroencephalographic (EEG) signals, referred to as artifacts. Common disturbances in the capture of EEG signals include electrooculogram (EOG), electrocardiogram (ECG), electromyogram (EMG) and other artifacts, which have a significant impact on the extraction of meaningful
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Járdánházy, T., I. Somogyi, and T. Asztalos. "Compression methods for EEG spectral data." Electroencephalography and Clinical Neurophysiology 87, no. 2 (1993): S133. http://dx.doi.org/10.1016/0013-4694(93)91489-n.

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Banquet, J. P., W. Guenther, and D. Breitling. "Multidimensional factorial methods for EEG data." Electroencephalography and Clinical Neurophysiology 61, no. 3 (1985): S231. http://dx.doi.org/10.1016/0013-4694(85)90874-0.

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Gu, Yuqiao, Geir Halnes, Hans Liljenström, and Björn Wahlund. "A cortical network model for clinical EEG data analysis." Neurocomputing 58-60 (June 2004): 1187–96. http://dx.doi.org/10.1016/j.neucom.2004.01.184.

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Goldenholz, Daniel M., Joseph J. Tharayil, Rubin Kuzniecky, Philippa Karoly, William H. Theodore, and Mark J. Cook. "Simulating clinical trials with and without intracranial EEG data." Epilepsia Open 2, no. 2 (2017): 156–61. http://dx.doi.org/10.1002/epi4.12038.

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Ivanov, А. А. "Overview of mathematical EEG analysis. Quantitative EEG." Epilepsy and paroxysmal conditions 15, no. 2 (2023): 171–92. http://dx.doi.org/10.17749/2077-8333/epi.par.con.2023.154.

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The purpose of this article is to familiarize medical specialists involved in registration and analysis of electroencephalographic (EEG) studies using methods of mathematical processing and analysis for recorded EEG data. Understanding the principles of how quantitative EEG analysis tools work should help medical personnel to properly use their capabilities and ultimately improve quality of medical care. Here, we discuss basic and innovative mathematical tools for EEG processing and analysis.
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Salam, Abdus, Selina Husna Banu, Abu Nayeem, and Zobaida Sultana Susan. "Clinical Finding of Electroencephalographic (EEG) Data in Adults: A Retrospective study." Journal of Shaheed Suhrawardy Medical College 6, no. 1 (2017): 14–17. http://dx.doi.org/10.3329/jssmc.v6i1.31486.

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Background: Electroencephalography (EEG) is the first and only real-time monitor of epileptic seizures, and is a powerful measure of cerebral function in the seriously ill.Objective: The purpose of this study was to see the common conditions for doing EEG.Methods: This study was performed retrospectively by collecting and reviewing the electro-clinical information of the adult patients to whom EEGs were done at the 'Central Hospital' laboratory. Clinical problems were categorized into seizures, fainting attacks, headache, giddiness, vertigo, stroke, suicidal tendency, sudden aggressiveness and
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Cisotto, Giulia, and Davide Chicco. "Ten quick tips for clinical electroencephalographic (EEG) data acquisition and signal processing." PeerJ Computer Science 10 (September 3, 2024): e2256. http://dx.doi.org/10.7717/peerj-cs.2256.

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Electroencephalography (EEG) is a medical engineering technique aimed at recording the electric activity of the human brain. Brain signals derived from an EEG device can be processed and analyzed through computers by using digital signal processing, computational statistics, and machine learning techniques, that can lead to scientifically-relevant results and outcomes about how the brain works. In the last decades, the spread of EEG devices and the higher availability of EEG data, of computational resources, and of software packages for electroencephalography analysis has made EEG signal proce
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Cincotti, F., C. Babiloni, C. Miniussi, et al. "EEG Deblurring Techniques in a Clinical Context." Methods of Information in Medicine 43, no. 01 (2004): 114–17. http://dx.doi.org/10.1055/s-0038-1633846.

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Summary Objectives: EEG scalp potential distributions recorded in humans are affected by low spatial resolution and by the dependence on the electrical reference used. High resolution EEG technologies are available to drastically increase the spatial resolution of the raw EEG. Such technologies include the computation of surface Laplacian (SL) of the recorded potentials, as well as the use of realistic head models to estimate the cortical sources via linear inverse procedure (low resolution brain electromagnetic tomography, LORETA). However, these deblurring procedures are generally used in co
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Kutafina, Ekaterina, Alexander Brenner, Yannic Titgemeyer, Rainer Surges, and Stephan Jonas. "Comparison of mobile and clinical EEG sensors through resting state simultaneous data collection." PeerJ 8 (May 1, 2020): e8969. http://dx.doi.org/10.7717/peerj.8969.

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Development of mobile sensors brings new opportunities to medical research. In particular, mobile electroencephalography (EEG) devices can be potentially used in low cost screening for epilepsy and other neurological and psychiatric disorders. The necessary condition for such applications is thoughtful validation in the specific medical context. As part of validation and quality assurance, we developed a computer-based analysis pipeline, which aims to compare the EEG signal acquired by a mobile EEG device to the one collected by a medically approved clinical-grade EEG device. Both signals are
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Dissertations / Theses on the topic "Clinical EEG data"

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Abazid, Majd. "Topological study of the brain functional organization at the early stages of Alzheimer's disease using electroencephalography." Electronic Thesis or Diss., Institut polytechnique de Paris, 2022. http://www.theses.fr/2022IPPAS026.

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L'électroencéphalographie (EEG) est encore considérée de nos jours comme une technique de neuroimagerie très utile dans les applications cliniques, adaptée aux patients souffrant de troubles cognitifs et physiques, ainsi qu'aux tests à grande échelle. L'EEG est une technologie non invasive, peu coûteuse et facilement accessible. Elle se caractérise par une haute résolution temporelle, ce qui est crucial pour le suivi de la dynamique cérébrale.Plusieurs travaux dans la littérature ont exploité l'EEG pour étudier les altérations de l'activité cérébrale liées aux maladies neurodégénératives, nota
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Matlis, Sean Eben Hill. "Functional network and spectral analysis of clinical EEG data to identify quantitative biomarkers and classify brain disorders." Thesis, 2016. https://hdl.handle.net/2144/19059.

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Many cognitive and neurological disorders today, such as Autism Spectrum Disorders (ASD) and various forms of epilepsy such as infantile spasms (IS), manifest as changes in voltage activity recorded in scalp electroencephalograms (EEG). Diagnosis of brain disease often relies on the interpretation of complex EEG features through visual inspection by clinicians. Although clinically useful, such interpretation is subjective and suffers from poor inter-rater reliability, which affects clinical care through increased variability and uncertainty in diagnosis. In addition, such qualitative assessme
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Zeman, Philip Michael. "Feasibility of Multi-Component Spatio-Temporal Modeling of Cognitively Generated EEG Data and its Potential Application to Research in Functional Anatomy and Clinical Neuropathology." Thesis, 2009. http://hdl.handle.net/1828/5010.

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This dissertation is a compendium of multiple research papers that, together, address two main objectives. The first objective and primary research question is to determine whether or not, through a procedure of independent component analysis (ICA)-based data mining, volume-domain validation, and source volume estimation, it is possible to construct a meaningful, objective, and informative model of brain activity from scalpacquired EEG data. Given that a methodology to construct such a model can be created, the secondary objective and research question investigated is whether or not the
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Hiah, Pier Juhng, and 連培中. "Data Stream Mining Technology for ECG Signals of Chronic Pain: Real-Time Tracking and Clinical Correlation." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/67yzx2.

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碩士<br>國立交通大學<br>電機資訊國際學程<br>105<br>Evaluating and tracking the progress of treatment for chronic pain is challenging because pain is a subjective experience and can be measured only by self-report. Electrocardiography (ECG) has been proven to be a promising source of physiological biomarkers for chronic pain. Previous studies had demonstrated that heart rate variability (HRV) could be associated with different types of pain and also pain perception. This study aims to identify the relationship between HRV indices and chronic pain through collecting resting ECG data and subjective pain severity
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Books on the topic "Clinical EEG data"

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Lopes da Silva, F. H., 1935-, Storm van Leeuwen W, and Rémond Antoine, eds. Clinical applications of computer analysis of EEG and other neurophysiological signals. Elsevier, 1986.

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Vanhatalo, Sampsa, and J. Matias Palva. Infraslow EEG Activity. Edited by Donald L. Schomer and Fernando H. Lopes da Silva. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780190228484.003.0032.

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Infraslow electroencephalographic (EEG) activity refers to frequencies below the conventional clinical EEG range that starts at about 0.5 Hz. Evidence suggests that salient EEG signals in the infraslow range are essential parts of many physiological and pathological conditions. In addition, brain is known to exhibit multitude of infraslow processes, which may be observed directly as fluctuations in the EEG signal amplitude, as infraslow fluctuations or intermittency in other neurophysiological signals, or as fluctuations in behavioural performance. Both physiological and pathological EEG activ
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Sutter, Raoul, Peter W. Kaplan, and Donald L. Schomer. Historical Aspects of Electroencephalography. Edited by Donald L. Schomer and Fernando H. Lopes da Silva. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780190228484.003.0001.

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Electroencephalography (EEG), a dynamic real-time recording of electrical neocortical brain activity, began in the 1600s with the discovery of electrical phenomena and the concept of an “action current.” The galvanometer was introduced in the 1800s and the first bioelectrical observations of human brain signals were made in the 1900s. Certain EEG patterns were associated with brain disorders, increasing the clinical and scientific use of EEG. In the 1980s, technical advances allowed EEGs to be digitized and linked with videotape recording. In the 1990s, digital data storage increased and compu
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Herring, Christina. Neuromodulation in Psychiatric Disorders. Edited by Anthony J. Bazzan and Daniel A. Monti. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780190690557.003.0013.

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Quantitative electroencephalogram (qEEG) is the transformation of the EEG by spectral analysis in which the amount of electrical activity at a particular frequency is determined and compared against a normative data base. EEG findings are specific for different psychiatric problems and help reveal brain abnormalities associated with psychological symptoms. Repetitive transcranial magnetic stimulation (rTMS) is a system of delivering multiple pulses within a short time period that induce changes that outlast the stimulation period. Operant conditioning involves providing a reward to increase th
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Thomas, James, and Tanya Monaghan. Clinical data interpretation. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780199593972.003.0019.

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Katirji, Bashar. Electromyography in Clinical Practice. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780190603434.001.0001.

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Clinical Electromyography in Clinical Practice provides case-based learning of clinical Electromyography (EMG) with a main mission of reducing the gap between theory and practice in the field of electrodiagnostic medicine. The book format includes four introductory chapters that acquaint the discipline and scope of the EMG Examination to the beginners. This include chapters on nerve conduction studies, needle EMG, and specialized testing including late responses, repetitive nerve stimulation and single fiber EMG. Discussion on the electrodiagnostic and clinical EMG findings in the numerous neu
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Stanley, Barbara, and Antonia New, eds. Borderline Personality Disorder. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780199997510.001.0001.

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Until recently, borderline personality disorder (BPD) has been the stepchild of psychiatric disorders. Many researchers even questioned its existence. Clinicians have been reluctant to reveal the diagnosis to patients because of the stigma attached to it. But individuals with BPD suffer terribly and a significant proportion die by suicide and engage in nonsuicidal self-injury. The aim of this primer on BPD is to fill this void and provide clinicians with an accessible, easy-to-use, clinically oriented, evidenced-based guide for early-stage BPD. We present the most up to date data about BPD by
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Staedtke, Verena, and Eric H. Kossoff. Epilepsy Syndromes in Childhood. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780199937837.003.0074.

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Epilepsy syndromes of childhood are a heterogeneous group of disorders that occur at specific neurodevelopmental stages, with a variable prognosis ranging from benign to catastrophic. In clinical practice they are categorized based on seizure type, age of onset, clinical presentation, electroencephalographic (EEG) findings, as well as response to treatment. In addition, recent advancements in neuroimaging and genetic testing have become important diagnostic tools revealing underlying defects for some of these syndromes. This knowledge has consequences for clinical practice, as it opens new per
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Poddubnyy, Denis, and Hildrun Haibel. Treatment: DMARDs. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780198734444.003.0021.

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In axial spondyloarthritis (axSpA) there is little evidence to support use of classical synthetic disease-modifying antirheumatic drugs (DMARDs), with the majority of studies performed in advanced ankylosing spondylitis. Sulfasalazine is the best investigated DMARD in axSpA. Its positive clinical effect, if any, seems to be more prominent in the presence of peripheral arthritis, although a certain proportion of patients with axial disease might benefit from sulfasalazine therapy. Available data indicate that there is no evidence that methotrexate might be effective in axial disease, and only m
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Kirollos, Ramez, Adel Helmy, Simon Thomson, and Peter Hutchinson, eds. Oxford Textbook of Neurological Surgery. Oxford University Press, 2019. http://dx.doi.org/10.1093/med/9780198746706.001.0001.

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Neurosurgery is a rapidly developing and technically demanding branch of surgery that requires a detailed knowledge of the basic sciences and a thorough clinical approach. The Oxford Textbook of Neurological Surgery is an up-to-date, objective, and readable text that covers the full scope of neurosurgical practice. Each section takes a dual approach with ‘generic surgical management’ chapters that focus on specific clinical problems facing the neurosurgeon (e.g. sellar/suprasellar tumour, intradural spina tumours, and others) and ‘pathology-specific’ chapters (e.g. glioma, meningeal tumours, s
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Book chapters on the topic "Clinical EEG data"

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Gerlá, Vaclav, Lenka Lhotska, Matej Murgas, Vladana Djordjevic Radisavljevic, Vladimir Krajca, and Vaclav Kremen. "An Incremental Approach to Clinical EEG Data Classification." In IFMBE Proceedings. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-11128-5_122.

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Hammond, E. J., C. P. Barber, and B. J. Wilder. "Flash Visual Evoked Potential Topographic Mapping: Normative and Clinical Data." In Topographic Brain Mapping of EEG and Evoked Potentials. Springer Berlin Heidelberg, 1989. http://dx.doi.org/10.1007/978-3-642-72658-3_27.

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Hammond, E. J., C. P. Barber, and B. J. Wilder. "Scalp Topography of Red LED Flash-Evoked Potentials: Normal and Clinical Data." In Topographic Brain Mapping of EEG and Evoked Potentials. Springer Berlin Heidelberg, 1989. http://dx.doi.org/10.1007/978-3-642-72658-3_42.

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Chowdhury, Linkon, Bristy Roy Chowdhury, V. Rajinikanth, and Nilanjan Dey. "A Framework to Evaluate and Classify the Clinical-Level EEG Signals with Epilepsy." In Proceedings of International Conference on Data Science and Applications. Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-7561-7_8.

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Dasgupta, Abhijit, Losiana Nayak, Ritankar Das, Debasis Basu, Preetam Chandra, and Rajat K. De. "Feature Selection and Fuzzy Rule Mining for Epileptic Patients from Clinical EEG Data." In Lecture Notes in Computer Science. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-69900-4_11.

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Molina, Edward, Ricardo Salazar-Cabrera, and Diego M. López. "NeuroEHR: Open Source Telehealth System for the Management of Clinical Data, EEG and Remote Diagnosis of Epilepsy." In Communications in Computer and Information Science. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-00350-0_35.

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Mohammad, Khorshid, Linda S. de Vries, Gerda Meijler, and Frances M. Cowan. "Hypoxic-Ischemic Encephalopathy (HIE) in Term and Near-Term Infants." In Neonatal Brain Injury. Springer Nature Switzerland, 2024. https://doi.org/10.1007/978-3-031-55972-3_8.

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AbstractHypoxic-ischemic encephalopathy (HIE) remains a major burden for infants, their families, and society all over the world, while the incidence of HIE has fallen slightly in high-income countries (HICs) that is not the situation in many poorer economic environments. Still, in many cases, a clear cause for and the timing of the insult remains unclear. The introduction of therapeutic cooling in HICs for moderate and severe HIE has resulted in better early recognition of encephalopathy, better monitoring with EEG, and an emphasis on optimal early management with early seizure treatments and
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Herff, Christian, and Dean J. Krusienski. "Extracting Features from Time Series." In Fundamentals of Clinical Data Science. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-99713-1_7.

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AbstractClinical data is often collected and processed as time series: a sequence of data indexed by successive time points. Such time series can be from sources that are sampled over short time intervals to represent continuous biophysical wave-(one word waveforms) forms such as the voltage measurements representing the electrocardiogram, to measurements that are sampled daily, weekly, yearly, etc. such as patient weight, blood triglyceride levels, etc. When analyzing clinical data or designing biomedical systems for measurements, interventions, or diagnostic aids, it is important to represen
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Silva, Hugo, André Lourenço, Ana Fred, and Joaquim Filipe. "Clinical Data Privacy and Customization via Biometrics Based on ECG Signals." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-25364-5_12.

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Storås, Andrea M., Michael A. Riegler, Trine B. Haugen, et al. "Automatic Unsupervised Clustering of Videos of the Intracytoplasmic Sperm Injection (ICSI) Procedure." In Communications in Computer and Information Science. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-17030-0_9.

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AbstractThe in vitro fertilization procedure called intracytoplasmic sperm injection can be used to help fertilize an egg by injecting a single sperm cell directly into the cytoplasm of the egg. In order to evaluate, refine and improve the method in the fertility clinic, the procedure is usually observed at the clinic. Alternatively, a video of the procedure can be examined and labeled in a time-consuming process. To reduce the time required for the assessment, we propose an unsupervised method that automatically clusters video frames of the intracytoplasmic sperm injection procedure. Deep fea
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Conference papers on the topic "Clinical EEG data"

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Skoric, Tamara, Marija Djermanovic, Jovana Kljajic, Slobodan Spasojevic, and John M. O' Toole. "Early Prediction of Electrographic Seizures in Neonatal Hypoxic-ischemic Encephalopathy Based on Amplitude-integrated EEG and Clinical Data." In 2024 32nd European Signal Processing Conference (EUSIPCO). IEEE, 2024. http://dx.doi.org/10.23919/eusipco63174.2024.10715242.

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Lin, Jia Lun, Jin Yang Xia, and Xiao Ling Li. "Research on a CNN Based Clinical Electrocardiogram Classification Model." In 12th Annual International Conference on Material Science and Engineering. Trans Tech Publications Ltd, 2025. https://doi.org/10.4028/p-fj7a4x.

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Electrocardiogram (ECG) is the most commonly used diagnostic method for heart diseases such as arrhythmia. However, its inherent complexity, to some extent, reduces the accuracy of diagnosis. To quickly and automatically identify the type of arrhythmia, this paper constructs a clinical ECG classification model based on Convolutional Neural Network (CNN) to assist clinicians in analyzing ECG signals. The MIT-BIH ECG database is used as the research data source, and the heart beats are classified into 5 categories based on AAMI EC57 standard. 95% of the ECG data is randomly divided into training
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Dasgupta, Abhijit, Ritankar Das, Losiana Nayak, and Rajat K. De. "Analyzing epileptogenic brain connectivity networks using clinical EEG data." In 2015 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). IEEE, 2015. http://dx.doi.org/10.1109/bibm.2015.7359791.

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Huang, Zexin, Liyong Han, Zhihua Huang, Zhixiong Lin, and Chenghua Wang. "Automated data set construction system for clinical EEG research." In 2023 16th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI). IEEE, 2023. http://dx.doi.org/10.1109/cisp-bmei60920.2023.10373261.

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Binnie, C. D. "Long term EEG recording and its role in clinical practice." In IEE Colloquium on Data Logging of Physiological Signals. IEE, 1995. http://dx.doi.org/10.1049/ic:19951385.

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Yang, S., S. Lopez, M. Golmohammadi, I. Obeid, and J. Picone. "Semi-automated annotation of signal events in clinical EEG data." In 2016 IEEE Signal Processing in Medicine and Biology Symposium (SPMB). IEEE, 2016. http://dx.doi.org/10.1109/spmb.2016.7846855.

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Aghaeeaval, Mahsa, Nathaniel Bendahan, Zaitoon Shivji, et al. "Prediction of patient survival following postanoxic coma using EEG data and clinical features." In 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC). IEEE, 2021. http://dx.doi.org/10.1109/embc46164.2021.9629946.

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Doborjeh, Maryam Gholami, and Nikola Kasabov. "Personalised modelling on integrated clinical and EEG Spatio-Temporal Brain Data in the NeuCube Spiking Neural Network system." In 2016 International Joint Conference on Neural Networks (IJCNN). IEEE, 2016. http://dx.doi.org/10.1109/ijcnn.2016.7727358.

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Smid, Jerusa, Ricardo Nitrini, Vilma Martins, et al. "THE BRAZILIAN SURVEILLANCE FOR PRION DISEASE: CURRENT DATA." In XIII Meeting of Researchers on Alzheimer's Disease and Related Disorders. Zeppelini Editorial e Comunicação, 2021. http://dx.doi.org/10.5327/1980-5764.rpda014.

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Background: The Brazilian Surveillance for Prion Disease began in 2005 with compulsory notification of suspected cases. Objective: To determine the diagnosis of reported patients to the Brazilian Surveillance for Prion Disease and evaluate the clinical and genetic data. Methods: Data from the notification sheet were collected and patients were classified according to current clinical and pathological criteria. Results: 757 cases were notified from 2005 to 2019. 51 cases were defined DCJ, 295 probable DCJ, 172 possible DCJ and 38 genetic DCJ. 55 patients had other diagnosis and 146 were unclass
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Oliveira, Gustavo B. S., Paulo D. S. Souza, Tiago S. Silva, João B. D. Filho, and Murillo G. Carneiro. "Analyzing Shallow and Deep CNNs with Gold Standard and Random EEG Segment Selections for Coma Prognosis." In Simpósio Brasileiro de Computação Aplicada à Saúde. Sociedade Brasileira de Computação - SBC, 2025. https://doi.org/10.5753/sbcas.2025.7669.

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This study focuses on deep learning models for predicting coma outcomes using electroencephalogram (EEG) data, exploring convolutional neural networks (CNNs), particularly Shallow and Deep ConvNets, based on Filter Bank Common Spatial Patterns. A dataset of 121 EEG samples (42 favorable, 79 unfavorable) was analyzed. EEG segments were selected using two strategies and frequencies. Models were trained with 10-fold cross-validation and FTSurrogate for class balance. Shallow ConvNet showed stable performance across frequencies, while Deep ConvNet excelled at 200Hz. Simple segment selection and sa
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Reports on the topic "Clinical EEG data"

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Hamlin, Alexandra, Erik Kobylarz, James Lever, Susan Taylor, and Laura Ray. Assessing the feasibility of detecting epileptic seizures using non-cerebral sensor. Engineer Research and Development Center (U.S.), 2021. http://dx.doi.org/10.21079/11681/42562.

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This paper investigates the feasibility of using non-cerebral, time-series data to detect epileptic seizures. Data were recorded from fifteen patients (7 male, 5 female, 3 not noted, mean age 36.17 yrs), five of whom had a total of seven seizures. Patients were monitored in an inpatient setting using standard video electroencephalography (vEEG), while also wearing sensors monitoring electrocardiography, electrodermal activity, electromyography, accelerometry, and audio signals (vocalizations). A systematic and detailed study was conducted to identify the sensors and the features derived from t
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de Carvalho, Clístenes Crístian, Ioannis Kapsokalyvas, and Kariem El-Boghdadly. Second-generation supraglottic airways vs endotracheal tubes in adults undergoing abdominopelvic surgeries: a protocol for a systematic review with pairwise meta-analyses of randomised clinical trials. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, 2022. http://dx.doi.org/10.37766/inplasy2022.9.0041.

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Review question / Objective: We aim to compare second-generation supraglottic airways with endotracheal tubes for perioperative safety and quality of postoperative recovery as well as for ventilation performance and risk of pulmonary aspiration. Eligibility criteria: Inclusion criteria will be as follows: randomized clinical trials; human patients aged ≥ 16 years undergoing abdominopelvic procedures under general anaesthesia from any population (e.g., general population, pregnant women, obese patients); data available on any outcome related to insertion performance (e.g., failed first attempt,
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Meng, kairui, yulin You, lijuan Chen, and yicheng Liu. A meta analysis on the efficacy of Chengqi Decoction in the treatment of ARDS/ALI. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, 2022. http://dx.doi.org/10.37766/inplasy2022.8.0040.

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Review question / Objective: What is the clinical efficacy of combing Chengqi Decoction in the treatment of ARDS/ALI, compared with the conventional treatment of ARDA/ALI with western medicine? Condition being studied: Acute respiratory distress syndrome(ARDS), Acute lung injury(ALI). Eligibility criteria: (1) lacking literature data (e.g., nonpaired studies) (2) duplicate publications; (3) do not have access to the full text (4) conference reports, system reviews, protocols, or abstracts; (5) RCTs with small sample sizes; . (5)The treatment course is less than 6 days (6) Exclude articles with
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MR MSK Cartilage for Joint Disease, Consensus Profile. Chair Thomas Link and Xiaojuan Li. Radiological Society of North America (RSNA) / Quantitative Imaging Biomarkers Alliance (QIBA), 2021. http://dx.doi.org/10.1148/qiba/20210925.

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The goal of a QIBA Profile is to help achieve a useful level of performance for a given biomarker. The Claim (Section 2) describes the biomarker performance. The Activities (Section 3) contribute to generating the biomarker. Requirements are placed on the Actors that participate in those activities as necessary to achieve the Claim. Assessment Procedures (Section 4) for evaluating specific requirements are defined as needed. This QIBA Profile (MR-based cartilage compositional biomarkers (T1ρ, T2) ) addresses the application of T1ρ and T2 for the quantification of cartilage composition, which c
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Leavy, Michelle B., Danielle Cooke, Sarah Hajjar, et al. Outcome Measure Harmonization and Data Infrastructure for Patient-Centered Outcomes Research in Depression: Report on Registry Configuration. Agency for Healthcare Research and Quality (AHRQ), 2020. http://dx.doi.org/10.23970/ahrqepcregistryoutcome.

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Background: Major depressive disorder is a common mental disorder. Many pressing questions regarding depression treatment and outcomes exist, and new, efficient research approaches are necessary to address them. The primary objective of this project is to demonstrate the feasibility and value of capturing the harmonized depression outcome measures in the clinical workflow and submitting these data to different registries. Secondary objectives include demonstrating the feasibility of using these data for patient-centered outcomes research and developing a toolkit to support registries intereste
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Totten, Annette, Dana M. Womack, Marian S. McDonagh, et al. Improving Rural Health Through Telehealth-Guided Provider-to-Provider Communication. Agency for Healthcare Research and Quality, 2022. http://dx.doi.org/10.23970/ahrqepccer254.

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Objectives. To assess the use, effectiveness, and implementation of telehealth-supported provider-to-provider communication and collaboration for the provision of healthcare services to rural populations and to inform a scientific workshop convened by the National Institutes of Health Office of Disease Prevention on October 12–14, 2021. Data sources. We conducted a comprehensive literature search of Ovid MEDLINE®, CINAHL®, Embase®, and Cochrane CENTRAL. We searched for articles published from January 1, 2015, to October 12, 2021, to identify data on use of rural provider-to-provider telehealth
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McCausland, Rachel, Joann Fontanarosa, and Ravi Patel. Nonemergent Percutaneous Coronary Intervention Versus Optimal Medical Treatment for Stable Ischemic Heart Disease: A Rapid Response Literature Review. Agency for Healthcare Research and Quality (AHRQ), 2023. http://dx.doi.org/10.23970/ahrqepcrapidcoronary.

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Aims. There is uncertainty around the optimal role of percutaneous coronary intervention (PCI) for management of chronic coronary syndrome, specifically when patients have disease in multiple coronary vessels and disease in the proximal portion of the left anterior descending coronary artery. This uncertainty was reflected in 2021 guidance from the American College of Cardiology (ACC)/American Heart Association (AHA) on coronary artery revascularization. The Agency for Healthcare Research and Quality has commissioned this rapid response literature review to meet a Congressional request for a s
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Nguyen-Feng, Viann N., Marizen Ramirez, Kathryn L. Behrens, et al. Trauma Informed Care: A Systematic Review. Agency for Healthcare Research and Quality (AHRQ), 2025. https://doi.org/10.23970/ahrqepcsrtrauma.

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Objectives. To examine how Trauma Informed Care (TIC) and its components are defined and operationalized, and to examine the state of the evidence on effectiveness and potential harms of TIC approaches, frameworks, models, and components. Data sources. We searched Medline (Ovid)®, APA PsycInfo® (Ovid), CINAHL® (EBSCOHost), ERIC (EBSCOHost), and Scopus (Elsevier) for peer-reviewed articles published through July 19, 2024. Grey literature was also searched for Contextual Questions regarding TIC definitions and organizational and clinical components. Review methods. We used methods consistent wit
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Newman-Toker, David E., Susan M. Peterson, Shervin Badihian, et al. Diagnostic Errors in the Emergency Department: A Systematic Review. Agency for Healthcare Research and Quality (AHRQ), 2022. http://dx.doi.org/10.23970/ahrqepccer258.

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Objectives. Diagnostic errors are a known patient safety concern across all clinical settings, including the emergency department (ED). We conducted a systematic review to determine the most frequent diseases and clinical presentations associated with diagnostic errors (and resulting harms) in the ED, measure error and harm frequency, as well as assess causal factors. Methods. We searched PubMed®, Cumulative Index to Nursing and Allied Health Literature (CINAHL®), and Embase® from January 2000 through September 2021. We included research studies and targeted grey literature reporting diagnosti
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Rankin, Nicole, Deborah McGregor, Candice Donnelly, et al. Lung cancer screening using low-dose computed tomography for high risk populations: Investigating effectiveness and screening program implementation considerations: An Evidence Check rapid review brokered by the Sax Institute (www.saxinstitute.org.au) for the Cancer Institute NSW. The Sax Institute, 2019. http://dx.doi.org/10.57022/clzt5093.

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Background Lung cancer is the number one cause of cancer death worldwide.(1) It is the fifth most commonly diagnosed cancer in Australia (12,741 cases diagnosed in 2018) and the leading cause of cancer death.(2) The number of years of potential life lost to lung cancer in Australia is estimated to be 58,450, similar to that of colorectal and breast cancer combined.(3) While tobacco control strategies are most effective for disease prevention in the general population, early detection via low dose computed tomography (LDCT) screening in high-risk populations is a viable option for detecting asy
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