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Akademický článek

Advancing spinal cord injury care through non-invasive autonomic dysreflexia detection with AI

Autor: Sidharth Pancholi, Thomas H. Everett, Bradley S. Duerstock

Publikováno v: Scientific Reports, Vol 14, Iss 1, Pp 1-11 (2024)

Abstract This paper presents an AI-powered solution for detecting and monitoring Autonomic Dysreflexia (AD) in individuals with spinal cord injuries. Current AD detection methods are limited, lacking non-invasive monitoring systems. We propose a mode

Externí odkaz: https://doaj.org/article/11eac419b0b8438b8a3da0352b59a2e3

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Akademický článek

Automatic Detection and Characterization of Autonomic Dysreflexia Using Multi-Modal Non-Invasive Sensing and Neural Networks

Autor: Shruthi Suresh, Thomas H. Everett, Riyi Shi, Bradley S. Duerstock

Publikováno v: Neurotrauma Reports, Vol 3, Iss 1, Pp 501-510 (2022)

Autonomic dysreflexia (AD) frequently occurs in persons with spinal cord injuries (SCIs) above the T6 level triggered by different stimuli below the level of injury. If improperly managed, AD can have severe clinical consequences, even possibly leadi

Externí odkaz: https://doaj.org/article/457eec41059b4986aa2b0f90b3a6d89f

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Akademický článek

Time and frequency domain analysis of physiological features during autonomic dysreflexia after spinal cord injury

Autor: Ana Karina Kirby, Sidharth Pancholi, Zada Anderson, Caroline Chesler, Thomas H. Everett, Bradley S. Duerstock

Publikováno v: Frontiers in Neuroscience, Vol 17 (2023)

IntroductionAutonomic dysreflexia (AD) affects about 70% of individuals with spinal cord injury (SCI) and can have severe consequences, including death if not promptly detected and managed. The current gold standard for AD detection involves continuo

Externí odkaz: https://doaj.org/article/e7e477febc0c44e78161904b9dcd294c

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Akademický článek

Feature Selection Techniques for a Machine Learning Model to Detect Autonomic Dysreflexia

Autor: Shruthi Suresh, David T. Newton, Thomas H. Everett, Guang Lin, Bradley S. Duerstock

Publikováno v: Frontiers in Neuroinformatics, Vol 16 (2022)

Feature selection plays a crucial role in the development of machine learning algorithms. Understanding the impact of the features on a model, and their physiological relevance can improve the performance. This is particularly helpful in the healthca

Externí odkaz: https://doaj.org/article/bb70da19b95c455b81a725f69e2c625f

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Akademický článek

Skin Sympathetic Nerve Activity and the Short-Term QT Interval Variability in Patients With Electrical Storm

Autor: Songwen Chen, Guannan Meng, Anisiia Doytchinova, Johnson Wong, Susan Straka, Julie Lacy, Xiaochun Li, Peng-Sheng Chen, Thomas H. Everett IV

Publikováno v: Frontiers in Physiology, Vol 12 (2021)

Background: Skin sympathetic nerve activity (SKNA) and QT interval variability are known to be associated with ventricular arrhythmias. However, the relationship between the two remains unclear.Objective: The aim was to test the hypothesis that SKNA

Externí odkaz: https://doaj.org/article/02a2c60700f541e7ab9bcd6b01f1ab0b

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Akademický článek

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Akademický článek

Examining the development of memory for temporal context and its underlying neural processes using event-related potentials

Autor: Kathleen M. Bettencourt, Laurel H. Everett, Yixin Chen, Thanujeni Pathman

Publikováno v: Developmental Cognitive Neuroscience, Vol 48, Iss , Pp 100932- (2021)

Time is a critical feature of episodic memory—memory for events from a specific time and place (Tulving, 1972). Previous research indicates that temporal memory (memory for ‘when’) is slower to develop than memory for other details (e.g., ‘wh

Externí odkaz: https://doaj.org/article/812b40df4ef746cfac1894ae9c82bee0

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