In this study the feasibility of detecting sleep apnoeas with unobtrusive wearable sensors and sounds recorded with a smartphone is studied by making an overnight recording to patients with high probability of sleep apnoeas. The data acquired with the aforementioned devices is: ECG, acceleration, bioimpedance of thorax and processed and raw audio. In data analysis phase it will be studied which combinations of these signals would enable detecting sleep apnoeas with high enough sensitivity and specificity when compared to a night polygraphy reference (Nox T3 device using airflow, breathing movements, audio, position, movement, oxygen saturation, pulse and leg EMG).

Inclusion Criteria:

• High a priori probability for SA based on previous PG findings, BMI, and ESS and medical history
• Clinical reason i.e. potential benefit of repeating the PG due to e.g. technical challenges in the previous PG and/or unclear findings or diagnosis. Participation may be offered also in cases where first PG is diagnostic. In these cases accuracy of sleep apnoea grading will be improved.
• Adequate Finnish language skills to comprehend study-related instructions and questionnaires. The study materials are available only in Finnish.
• Signed written informed consent

Exclusion Criteria:

• Medical history of a major cardiovascular event (myocardial infarction, coronary artery bypass graft (CABG), percutaneous coronary intervention (PCI), stroke, or transient ischemic attack) within the previous 6 months
• Use of cardiac pacemaker or history of atrial fibrillation

The study group will be recruited from occupational health care patients who have been earlier admitted by Mehiläinen for a PG study at KNF-laboratoriot.