AIMC Topic: Neurophysiological Monitoring
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Robotic Assisted Transcranial Doppler Monitoring in Acute Neurovascular Care: A Feasibility and Safety Study.
Neurocritical care
Sep 19, 2024
BACKGROUND: Transcranial color Doppler (TCD) is currently the only noninvasive bedside tool capable of providing real-time information on cerebral hemodynamics. However, being operator dependent, TCD monitoring is not feasible in many institutions. R...
Dynamic Detection of Delayed Cerebral Ischemia: A Study in 3 Centers.
Stroke
Feb 18, 2021
BACKGROUND AND PURPOSE: Delayed cerebral ischemia (DCI) after aneurysmal subarachnoid hemorrhage negatively impacts long-term recovery but is often detected too late to prevent damage. We aim to develop hourly risk scores using routinely collected cl...
Non-Invasive Estimation of Intracranial Pressure by Diffuse Optics: A Proof-of-Concept Study.
Journal of neurotrauma
Jul 7, 2020
Intracranial pressure (ICP) is an important parameter to monitor in several neuropathologies. However, because current clinically accepted methods are invasive, its monitoring is limited to patients in critical conditions. On the other hand, there ar...
Artificial Intelligence based facial recognition for Mood Charting among men on life style modification and it's correlation with cortisol.
Asian journal of psychiatry
May 11, 2019
UNLABELLED: Today, clinicians and researchers believe that mood disorders in children and adolescents remain one of the most under diagnosed mental health problems. Mood disorders in adolescents also put them at risk for other conditions that may per...
Robotic technology provides objective and quantifiable metrics of neurocognitive functioning in survivors of critical illness:A feasibility study.
Journal of critical care
Sep 12, 2018
PURPOSE: To assess the feasibility of using an integrated multimodal data collection strategy to characterize the post-intensive care syndrome (PICS).
A hierarchical multimodal system for motion analysis in patients with epilepsy.
Epilepsy & behavior : E&B
Aug 31, 2018
During seizures, a myriad of clinical manifestations may occur. The analysis of these signs, known as seizure semiology, gives clues to the underlying cerebral networks involved. When patients with drug-resistant epilepsy are monitored to assess thei...
Machine Learning for Outcome Prediction in Electroencephalograph (EEG)-Monitored Children in the Intensive Care Unit.
Journal of child neurology
May 13, 2018
The aim of this study was to evaluate the performance of models predicting in-hospital mortality in critically ill children undergoing continuous electroencephalography (cEEG) in the intensive care unit (ICU). We evaluated the performance of machine ...
Personal Sensing: Understanding Mental Health Using Ubiquitous Sensors and Machine Learning.
Annual review of clinical psychology
Mar 17, 2017
Sensors in everyday devices, such as our phones, wearables, and computers, leave a stream of digital traces. Personal sensing refers to collecting and analyzing data from sensors embedded in the context of daily life with the aim of identifying human...
A Neuromonitoring Approach to Facial Nerve Preservation During Image-guided Robotic Cochlear Implantation.
Otology & neurotology : official publication of the American Otological Society, American Neurotology Society [and] European Academy of Otology and Neurotology
Jan 1, 2016
HYPOTHESIS: A multielectrode probe in combination with an optimized stimulation protocol could provide sufficient sensitivity and specificity to act as an effective safety mechanism for preservation of the facial nerve in case of an unsafe drill dist...
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