Search Results - maxime+cannesson

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Deep Neural Networks for Real-Time Non-invasive Continuous Peripheral Oxygen Saturation Monitoring (Case No. 2024-227)

Summary: UCLA researchers in the Department of Anesthesiology have developed a novel pulse oximetry methodology utilizing deep neural networks for non-invasive monitoring. Background: In the US alone, over 5 million patients are admitted to the ICU for oxygen saturation monitoring. They, as well as the more than 15 million patients undergoing surgery,...

Published: 7/26/2024 | Inventor(s): Sungsoo (Danny) Kim, Sohee Kwon, Mia Markey, Alan Bovik, Akos Rudas, Ravi Pal, Maxime Cannesson

Keywords(s): Artifical Intelligence (Machine Learning, Data Mining), Blood Pressure, cardiovascular monitoring, central venous pressure (CVP), Continuous blood pressure monitoring, critical care, Deep learning-based sensing, deep-learning analysis algorithms, heart failure, hemodynamic monitoring, machine learning modeling, Monitoring (Medicine), neural network, non-invasive monitoring, Oxygen, Oxygen Saturation, pulmonary arterial pressure (PAP), Swan-Ganz catheter

Category(s): Medical Devices > Monitoring And Recording Systems, Software & Algorithms > Digital Health

Intraoperative Deep Learning Model for Imputation of the Continuous Central Venous Pressure (CVP) and Pulmonary Arterial Pressure (PAP) Waveforms From (Case No. 2024-224)

Summary: Researchers in the UCLA Department of Anesthesiology have developed a deep learning model to accurately represent and visualize hemodynamic waveforms, or blood flow patterns, with minimally invasive approaches. Background: Swan-Ganz (SG) catheters are used for precise cardiac hemodynamic evaluations. Indicated for patients with severe...

Published: 9/3/2024 | Inventor(s): Maxime Cannesson, Sungsoo (Danny) Kim, Akos Rudas, Jeffrey Chiang, Ravi Pal

Keywords(s): active learning, Algorithm, algorithm-based testing, arterial blood pressure (ABP), Artifical Intelligence (Machine Learning, Data Mining), artificial intelligence algorithms, blood cancers, blood flow management, Blood Pressure, Blood Proteins, cardiovascular monitoring, catheter, Catheterization, central venous pressure (CVP), Computer Aided Learning, Continuous blood pressure monitoring, critical care, curriculum learning, Deep Learning, Deep learning-based sensing, deep-learning analysis algorithms, heart failure, hemodynamic monitoring, Machine Learning, non-invasive monitoring, Perceptual Learning, pulmonary arterial pressure (PAP), Software & Algorithms, Swan-Ganz catheter

Category(s): Software & Algorithms, Software & Algorithms > Digital Health, Software & Algorithms > Artificial Intelligence & Machine Learning, Medical Devices, Medical Devices > Monitoring And Recording Systems

Detection of Dicrotic Notch in Arterial Pressure and Photoplethysmography Signals Using Iterative Envelope Mean Filter (Case No. 2024-034)

Summary: UCLA Researchers in the Department of Anesthesiology have developed an iterative envelope mean (IEM) method for the detection of specific features in arterial pressure monitoring applications. Background: The cardiac cycle consists of the distinct systolic and diastolic phases. The transition from the contracted, systolic phase to the...

Published: 10/24/2024 | Inventor(s): Maxime Cannesson, Ravi Pal, Akos Rudas, Jeffrey Chiang, Sungsoo (Danny) Kim

Keywords(s): arrhythmia, arterial blood pressure (ABP), cardiac cycle, Cardiac Electrophysiology, Cardiac failure, Cardiac Magnetic Resonance Imaging, cardiometabolic disease, cardiopulmonary illness, Cardiovascular, Cardiovascular Disease, Cardiovascular Disease Nephropathy, cardiovascular modeling, cardiovascular prediction, cardiovascular therapeutic solution, diastolic, diastolic phase peak, dicrotic notch, feature extraction tool, iterative envelope method (IEM), Medical Device, medical device cardiac monitoring, Medical Device Poly(Methyl Methacrylate), Medical Devices and Materials, non-invasive cardiac monitoring, photoplethysmography (PPG), Smart medical device, systolic, tachycardia, wearable medical device, wearable medical devices

Category(s): Medical Devices, Medical Devices > Monitoring And Recording Systems, Platforms, Platforms > Diagnostic Platform Technologies, Software & Algorithms, Diagnostic Markers > Targets And Assays, Diagnostic Markers

2021-283 MMHEALTH: MULTIMODAL HEALTH SENSING PLATFORM

SUMMARY: UCLA researchers in the Department of Electrical and Computer Engineering have developed a system that can remotely evaluate patient symptoms and diagnose medical conditions. BACKGROUND: Ensuring that patients are accurately and efficiently diagnosed is of high clinical significance. Current methods require contact-based diagnostic tests...

Published: 11/15/2024 | Inventor(s): Achuta Kadambi, Laleh Jalilian, Omid Abari, Maxime Cannesson, Ashley Kita, Pradyumna Chari, Adnan Armouti

Keywords(s): Diagnostic Markers & Platforms, Diagnostic Test, Infectious Diseases, Machine Learning, Remote Sensing, Sensors

Category(s): Life Science Research Tools > Research Methods, Life Science Research Tools, Diagnostic Markers, Medical Devices

2020-925 Methods and Apparatus for Extracting Vital Signs Using Smartphone Cameras

SUMMARYUCLA researchers in the Department of Electrical & Computer Engineering have developed a contactless apparatus to report broad vital sign measurements using face video acquisition and signal processing pipelines while ensuring patients’ privacy through visual encoding methods. BACKGROUNDPhotoplethysmography (PPG) is an inexpensive optical...

Published: 7/19/2023 | Inventor(s): Achuta Kadambi, Laleh Jalilian, Pradyumna Chari, Chinmay Talegaonkar, Doruk Karinca, Maxime Cannesson, Krish Kabra

Keywords(s):

Category(s): Software & Algorithms > Digital Health, Medical Devices > Medical Imaging, Medical Devices > Monitoring And Recording Systems, Optics & Photonics

2019-872 Methods and Apparatus to Impute Physiological Signals and Derivative Absolute Values in Real-Time Using Machine Learning Approaches from Independent Data Sources

SUMMARYResearchers led by Drs. Maxime Cannesson and Eran Halperin at UCLA have developed a way to predict arterial blood pressure waveforms using EKG and SpO2 waveforms.BACKGROUNDMonitoring and measuring vital physiological signals like arterial blood pressure (ABP) is critical for successful surgery. Ideally these types of signals should be measured...

Published: 7/19/2023 | Inventor(s): Maxime Cannesson, Brian Hill, Eran Halperin, Ira Hofer, Nadav Rakocz

Keywords(s): Advanced Computing / AI, Anesthesiology, Artifical Intelligence (Machine Learning, Data Mining), Bioinformatics, Digital Health, Hospital Systems And Devices, Monitoring And Recording Systems, Signal Processing, Simulation & Modeling, Software, Software & Algorithms

Category(s): Medical Devices > Monitoring And Recording Systems, Platforms > Diagnostic Platform Technologies, Software & Algorithms > Data Analytics, Software & Algorithms > Bioinformatics, Software & Algorithms > Programs