The Intensive Care Unit (ICU) is a high-stress environment that often disrupts patients’ circadian rhythms and emotional well-being due to artificial lighting, unfamiliar routines, and the absence of natural day-night cues. This project explores how lighting interventions can improve the ICU experience from the perspective of critically ill patients. Conducted in collaboration with Critical Alarms Lab (TU Delft) and Leiden University Medical Center (LUMC), the study followed a human-centered design process to understand and address patient challenges related to light exposure.

Through observations, interviews with healthcare professionals, and environmental light assessments, key vulnerable moments in the patient journey particularly during waking and sleep preparation were identified. This led to the development of LumoGlaze, a wearable smart goggle, and LumoSync, a mobile app that uses physiological data (Heart rate and sleep phase from Fitbit) to adapt lighting. The system provides calming evening light and a morning bright light therapy to support circadian alignment.

Prototypes were refined through iterative testing and evaluated in a simulated ICU setting. Participants reported the system as comfortable, intuitive, and non-intrusive. While physiological data showed no significant variations across lighting modes, the intervention was perceived as supportive in creating a calmer environment.

This work highlights the potential of patient-centered, non-pharmacological lighting solutions in critical care. LumoGlaze serves as a blueprint for integrating adaptive, human-focused lighting technology into healthcare environments. Future recommendations include in-site ICU testing, extended physiological monitoring, and exploring more personalized lighting strategies.

Introduction: The Intensive Care Unit (ICU) is a highly monitored environment where alarm overload poses risks to patient safety and staff well-being. SpO2 alarms contribute significantly and are often clinically irrelevant. This contributes to alarm fatigue, delayed responses, and disrupted workflows while excessive noise adversely affects patient recovery and nurse mental health. The aim was to analyse the auditory alarm landscape in the ICU at Leiden University Medical Center (LUMC) with a focus on SpO2 alarms. Furthermore, SpO2 alarms were annotated for actionability through the integration of contextual data and SpO2 trends were evaluated.
Methods: A retrospective analysis was conducted on ICU patients admitted between December 2023 and October 2024. Alarm, oxygen saturation, and patient data were extracted from monitoring systems and patient data management systems. The alarm dataset was explored using descriptive statistics. Audible SpO2 alarms were annotated for actionability using predefined criteria based on clinical context, signal quality, and response to alarms, including respiratory support therapy escalation and ventilation or oxygen parameter adjustments. SpO2 trends surrounding alarms were analysed to find patterns between actionable and non-actionable events.
Results: Among 635,717 auditory alarms recorded over 2261 patient-days, 32% were SpO2 alarms, with 88.7% classified as non-actionable. The median response time for actionable alarms was 8.17 minutes, with most interventions involving FiO2 increases. Temporal analyses revealed alarm frequency peaks during morning and afternoon shifts. SpO2 trends at the time of actionable alarms correlated with significant desaturation events, while non-actionable alarms reflected minor, transient changes.
Conclusion: This study analysed the auditory alarmscape in the LUMC ICU, revealing that SpO2 alarms, while significant contributors to alarm burden, are mostly non-actionable, increasing the alarm load and its associated challenges unnecessarily. By annotating alarms based on clinical context, it has laid groundwork for developing robust predictive algorithms to suppress non-actionable alarms.