Please login to create your UC TechAlerts.
Request a new password for
Required
Find technologies available for licensing from all ten University of California (UC) campuses.
No technologies match these criteria. Schedule UC TechAlerts to receive an email when technologies are published that match this search. Click on the Save Search link above
Patient Pressure Injury Prevention Methods and Software
Pressure injuries (commonly called bedsores or pressure ulcers) represent one of the most persistent and costly challenges in healthcare, affecting over 2.5 million US patients and costing almost $27B in 2019. Hospital-acquired pressure injury events occur in about 3% in general populations and about 6% in intensive care units (ICUs). Current prevention strategies still rely on the Braden Scale risk assessment tool, which was developed in the 80s to stratify patients into risk categories based on factors like sensory perception, moisture, mobility, and friction. Staff adherence to turning protocols remains stubbornly low at just under 50% nationally, creating a gap between prescribed care and actual implementation. Technologies to sense pressure injuries suffer from several significant limitations: they often provide discontinuous monitoring requiring manual interpretation, lack objective mobility metrics, and fail to account for the complex interplay between pressure distribution, patient movement patterns, and individual risk factors. The existing Braden Scale approach is particularly problematic as it doesn't account for the presence of existing pressure injuries or patient-specific factors, and has been shown to have inadequate validity for ICU patients. Additionally, current pressure mapping systems are typically large, expensive, and require specialized training, limiting their practical deployment in routine clinical care.
Large Language Models For Verifiable Programming Of Plcs In Industrial Control Systems
A user-guided iterative pipeline that significantly improves the reliability and quality of code generated by Large Language Models (LLMs) for industrial control systems (ICS).
An Design Automation Methodology Based On Graph Neural Networks To Model The Integrated Circuits And Mitigate The Hardware Security Threats
An innovative design automation methodology leveraging graph neural networks to enhance integrated circuit security by mitigating hardware threats and protecting intellectual property.
Methods For Spatio-Temporal Scene-Graph Embedding For Autonomous Vehicle Applications
A revolutionary approach to enhancing the safety and efficiency of autonomous vehicles through advanced scene-graph embeddings.
Accurate, Non-Invasive Fetal Arterial Oxygen Saturation and Blood Ph Measurement via Diffuse Optics
Researchers at the University of California, Davis have developed non-invasive fetal monitoring that enables accurate, continuous measurement of fetal arterial blood oxygen saturation and blood pH.
Multiplexed Entangled Photon Generator Based On Integrated Photonic Microresonator Array
Brief description not available
Laser-Induced Confocal Microscope for Dielectrophoretic Fluorescence-Activated Droplet Sorting
A system that enhances and accelerates enzyme evolution process for synthetic biology applications using microfluidic technology and fluorescent sensors.
Enhancing iPSC Reprogramming Efficiency
A revolutionary method for improving the efficiency and quality of reprogramming adult cells into stem cells or other therapeutically relevant cell types via adhesome gene manipulation.