Digital Health Zurich

From Wearables to Early Warning: Continuous Patient Monitoring and Transparent Risk Prediction in Acute Care

Wearable sensors offer a promising pathway toward continuous, automated patient monitoring — yet translating this potential into clinical practice requires both reliable data capture and trustworthy predictive models. In this talk, Dr. Samuel Wehrli (ZHAW) will present two complementary workstreams from the Innosuisse Flagship project SHIFT (Smart Hospital – Integrated Framework for Technology in Healthcare), conducted in collaboration with the University Hospital Basel and Leitwert AG.

The first part covers the feasibility of wearable-based vital sign monitoring on general wards, where a pilot study demonstrated that heart rate and respiratory rate captured by a wrist-worn device can approximate conventional NEWS2 scores with substantial agreement. The second part addresses Hospital in Motion, a sensor-based activity monitoring approach designed to combat hospital-associated disability in elderly patients by tracking and promoting mobility through clinically validated algorithms and user-centered dashboard interfaces. 

The talk will also introduce the Hybrid Naïve Bayes (HNB) framework — a modular approach that combines predictors from different data modalities (e.g., continuous wearable signals, binary clinical indicators, patient demographics) into a single, transparent risk score in a statistically principled way. The framework is inherently robust to missing inputs and produces interpretable, well-calibrated predictions that clinicians can inspect and trust. The presentation will highlight how continuous sensing, activity tracking, and transparent risk modelling can converge toward a seamless, data-driven care pathway from hospital admission through to home monitoring.

About Samuel Wehrli

Dr. Samuel Wehrli is a physicist and research group leader at the Institute of Computational Life Sciences at ZHAW (Zurich University of Applied Sciences). After completing his PhD at ETH Zurich, he spent over ten years in the sensor industry at Sensirion AG, leading several R&D teams and contributing to the development of IoT and sensor technologies. Today he conducts research and teaches at the intersection of biosignal analysis, artificial intelligence, and digital health. His projects — including SHIFT, ConCLAS, and Fokus-Uhr — combine engineering, data analytics, and health innovation to enable new forms of patient-centered care.