Wearable Stress Detection for Frontline Healthcare Workers
SENSE
Wearable sensor data and machine learning put to work on the emotional wellness of nurses and social workers.
Overview
Nurses and social workers carry a load that rarely shows up in any operational metric. SENSE pairs wearable sensors with machine learning to make that load visible, recording physiological signals across a shift and turning them into an estimate of stress for the person wearing the device.
Timing is what makes the estimate useful. A signal that arrives during the shift can prompt a break or a handoff, while a retrospective report can only describe what already happened. The work continues the lab’s interest in the working conditions of health and social care staff, alongside its research on emergency department workflows and clinical documentation.