The map is not the territory: why sleep apnea needs a new way of seeing
Luca Cerina defended his PhD thesis at the Department of Electrical Engineering on April 1st.
Since sleep apnea was first described in the 1970s, research has shown that Sleep Disordered Breathing (SDB) is not one uniform condition but a broad spectrum of different patterns and patient types. People may experience full breathing pauses or partial reductions in breathing, sometimes mainly during dream sleep, sometimes mostly when lying on their back, sometimes with severe daytime sleepiness and sometimes with almost no obvious symptoms at all. These different patterns are not just technical details; they are linked to very different health risks, long-term outcomes, and responses to treatment. Two patients with the same diagnosis may therefore need very different therapeutic approaches.
The problem with a single number
Despite this complexity, the main measure used in diagnosis today is still the Apnea-Hypopnea Index (AHI), a number that simply counts how many breathing disruptions occur per hour of sleep. This number is useful, but it also reduces a complex night of sleep, breathing patterns, sleep stages, and body position into a single value. As a result, a large amount of valuable physiological information is collected but never fully used, and important differences between patients can remain hidden.
A better map of sleep apnea
This research of focused on developing new methods and metrics that create a more detailed picture of sleep disordered breathing. Special attention was given to home sleep apnea testing, which is becoming more common, and to people whose breathing problems occur mainly during REM sleep. By improving how respiratory signals are measured and how severity is described, the research shows that it is possible to capture meaningful differences between patients that are currently overlooked.
Towards personalized treatment
The most important implication of this work is clinical. Today, treatment decisions are largely based on a small set of severity metrics combined with medical history. But sleep apnea appears in many different forms and often exists alongside other conditions such as hypertension or increased risk of cognitive decline. This thesis moves toward a future where diagnosis is more precise, home measurements are simpler but still reliable, and treatment can be tailored to the individual patient rather than to an average score. In other words, better maps can lead to better treatment decisions, and ultimately, better patient outcomes.
The research was performed within Eindhoven MedTech Innovation Center (e/MTIC), incorporating 黑料福利网, Kempenhaeghe and Philips, as part of the MEDUSA TKI HTSM project.
Read more about the research of Sebastiaan Overeem, Merel van Gilst and their team on new ways to monitor sleep disorders. Besides that there were the PhD defenses 鈥�Measuring Sleep and Respiration with Chest-Wall Accelerometry鈥� of Fons Schipper in March 2026, 鈥楧eep generative modelling in sleep diagnostics鈥� of Hans van der Gorp in January 2026, and 鈥極ptimizing Automated Sleep Staging鈥� of Jaap van der Aar in December 2025.
Title of PhD thesis: . Supervisors: Prof. Sebastiaan Overeem (黑料福利网), Dr. Rik Vullings (黑料福利网), and Dr. Pedro Fonseca (Philips).