Noamko128/PPG-BP-Project
Develop a machine learning model using PPG signals to non-invasively estimate blood pressure changes in anesthetized patients during surgery. Exploring the potential of PPG-based devices for continuous patient monitoring. collaborate with:
This project helps anesthesiologists and surgical teams continuously monitor blood pressure changes in anesthetized patients during surgery without invasive catheters or intermittent cuffs. It takes photoplethysmogram (PPG) signals from a simple sensor and outputs an estimation of mean arterial pressure (MAP) changes. This tool is designed for medical professionals involved in patient care during surgical procedures.
Use this if you need a non-invasive, continuous method to track blood pressure trends in anesthetized patients, reducing risks and discomfort associated with current monitoring methods.
Not ideal if you require absolute blood pressure values that meet AAMI guidelines for diagnostic accuracy, as this model currently focuses on estimating changes and may require further development for full clinical validation.
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Mar 06, 2026
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