Comorbid insomnia and sleep apnea Diagnostics (CoDiac)

CoDiac (“Comorbid Insomnia and Sleep Apnea Diagnostics”) is a joint R&D project that focuses on a particularly challenging and clinically relevant constellation: insomnia (difficulties initiating and/or maintaining sleep) and sleep-related breathing disorders, especially sleep apnea, which often occur together as COMISA. This comorbidity is associated with high symptom burden and complex diagnostic and therapeutic pathways. At the same time, many healthcare systems face bottlenecks in sleep-laboratory capacity and in long-term therapy monitoring. CoDiac therefore targets a scalable, ambulatory solution that can extend the spectrum of care into the patient’s home while maintaining clinically meaningful signal quality and interpretability.

Project aim and core idea

The project’s central goal is the development of a portable and modular diagnostic and therapy-monitoring systemfor use in the patient’s natural home environment (“own bedroom”). The system is designed to provide markers of sleep structure and sleep quality of high medical value, while simultaneously meeting practical requirements such as wearing comfort, easy handling, and robustness against typical movement artefacts during sleep. Multi-night measurement capability is explicitly part of the design objective, because real-world sleep assessment often benefits from repeated recordings rather than single-night snapshots.

A key element is an interactive feedback concept that helps users apply and operate the system correctly at home. The intent is to reduce user errors (e.g., poor electrode contact or misplacement), improve data completeness, and enable reliable recordings without continuous professional supervision. This usability-driven approach is central for translating sleep-lab-grade methods into ambulatory practice.

Measurement concept: EEG-first, complemented by cardio-respiratory signals

CoDiac follows an “EEG-first” philosophy: electrophysiological measurement of brain activity via EEG (and—where relevant—sleep-related eye movements via EOG) remains a core component because it is fundamental for sleep staging and for clinically established interpretation of sleep architecture. However, the project also recognizes that COMISA assessment benefits from additional signals, especially for the detection and characterization of breathing-related events. CoDiac therefore integrates cardio-respiratory measures (e.g., oximetry/SpO₂, respiratory activity, heart-related parameters) in order to strengthen diagnostic power for sleep apnea while keeping the overall setup feasible for home use.

Importantly, CoDiac explicitly addresses the trade-off between “more signals” and “real-world feasibility”. Prior research demonstrates that combining many sensor channels can yield strong algorithmic performance, but such setups are often too complex for routine ambulatory use. CoDiac therefore aims for a pragmatic reduction of signal count—selecting a small, informative set that remains clinically meaningful and operationally robust in the home environment.

Digital workflow: secure portal, clinical review, and end-to-end traceability

A defining feature of CoDiac is the integration of the measurement system into a clinically oriented digital workflow: data are transmitted to an IT infrastructure and made available in a portal where medical professionals can review, edit, assess (befunden), and forward results. This provides a bridge between home-based acquisition and professional clinical interpretation, enabling the system to support both initial diagnostic decisions and longitudinal therapy monitoring.

From a system-engineering perspective, the project is organized into coordinated work packages that span: requirements and specification (medical and technical), hardware development, software platform development (database + portal), signal/vital-parameter processing, system integration and functional testing, testing in a sleep-medicine setting, and medical/technical evaluation plus documentation. This structure ensures that the demonstrator is not only technically functional, but also embedded in a realistic workflow with clearly defined interfaces between device, infrastructure, and clinical users.