CSEM technology supports breakthrough in EEG monitoring to reduce postoperative delirium

Neuchâtel’s CSEM is playing a central role in the QUESTIONED project, an initiative aiming to reduce postoperative delirium (POD) in elderly patients through real-time brain activity monitoring during anesthesia.

Postoperative delirium is a common complication in older surgical patients and has significant clinical and economic consequences. To address this, the QUESTIONED project, funded by the Bern MedTech Collaboration Call (BMCC), relies on CSEM’s EEG monitoring technology to improve anesthesia care and patient outcomes.

At the core of the solution is ULTEEMNite, a compact, wearable EEG device engineered by CSEM in collaboration with the Inselspital, Bern’s University Hospital. Originally developed for sleep studies, the technology has been adapted for surgical settings. Its dry electrode system enables accurate brain signal monitoring without the need for traditional gel-based or single-use electrodes, reducing waste and operational costs.

ULTEEMNite weighs less than 20 grams, uses Bluetooth Low Energy to transmit signals, and integrates seamlessly with portable displays and custom algorithms for real-time interpretation of EEG data. It provides anesthesiologists with a clearer view of a patient’s neurological state—supporting more precise drug dosing and potentially preventing both under- and over-sedation.

Bringing scalable, smart technology from lab to clinic

Unlike traditional depth-of-anesthesia systems that can be expensive, environmentally taxing, and limited in interpretive accuracy for older patients, ULTEEMNite is designed to be reusable, affordable, and clinically robust. Its introduction could broaden EEG-based monitoring to a wider range of surgeries and institutions, especially in aging healthcare systems like Switzerland’s.

CSEM’s involvement goes beyond hardware: the organization contributes its deep expertise in wearable biosignal acquisition, systems integration, and MedTech certification pathways. It is also supporting the customization of data visualization interfaces and machine learning models used to interpret brainwave patterns linked to POD.

By anchoring the technical component of the project, CSEM helps bridge the gap between research and real-world application—advancing Switzerland’s leadership in smart, patient-centric healthcare innovation.