Our student Xu Han presents a breakthrough in neurocritical care AI
We’re pleased to share that our PhD student, Xu Han, recently presented his research in the Case Studies in Neurocritical Care AI Webinar Series, hosted by Moberg Analytics.
His presentation, titled “A Novel Methodology for Intracranial Pressure Subpeak Identification,” details an innovative approach for real-time analysis of intracranial pressure (ICP) waveforms. By extracting morphological features from the ICP signal and integrating data from arterial blood pressure (ABP) and electrocardiogram (ECG) signals, the proposed machine learning–based methodology achieved over 97% accuracy in identifying ICP subpeaks.
This work has significant applications in the automated monitoring of patients with traumatic brain injury (TBI), enabling early detection of critical physiological changes without the need for continuous physician oversight.
