Difficulties recruiting participants

The aim of this trial is to assess the effect of two automated beds on severity of POSA as well as the feasibility of these beds as POSA treatment. These beds are equipped with sensors detecting apnoeas and hypopnoeas from physiological measurements - such as chest movement or breathing sound -, and coherently reacting by actively changing the user position whenever an apnoeic event occurs. Thereby we will investigate a possible treatment alternative to already established OSA therapies, either as a valuable add-on for patients eligible to the currently available therapies or as primary treatment option.

During the intervention nights (2 out of 3 experiment nights), positional therapy by means of the automated bed will be applied in order to induce a change in the sleeping position. Two approaches to influence the position will be investigated:

1. Lifting the upper body up, which has been suggested as a method for reducing habitual snoring. This intervention will be provided by an adjustable bed (AmbianceE-Motion, manufactured by Elite SA, Aubonne, Switzerland) referred to as ISABel Bed 1. This bed contains four motors for changing the inclination angle of the head, trunk, leg, and foot support. Only the position of the trunk and head support is changed during the study. The inclination angle is set to the maximum inclination angle the bed allows: this is 50° at the slatted frame which results in approximately 40° inclination of the hip of the user. The reference angle (0°) is represented by the supine position.
2. Inclination of one side of the bed. This intervention will be provided with a custom-made, adjustable bed base prototype, referred to as ISABel Bed 2 (produced by Sensory-Motor Systems Lab, ETH Zurich, Zurich, Switzerland). The bed is equipped with two motors which allow sideward inclination of up to 40 °. The inclination to be applied in this study is set to 30 ° based on a pre-study with healthy human subjects. Both beds are equipped with non-invasive, cable-free sensors (cardio-ballistography, microphone, and force sensor). A closed-loop control algorithm, which has been developed using machine learning techniques, continuously monitors these signals and triggers the positional intervention, when it detects that the participant is experiencing an apnoea event.

Inclusion Criteria:

• Documented supine positional OSA (AHIsupine/AHInonsupine ≥2) with a total AHI of ≥10 events/hour
• Age ≥18 years and <80 years
• Written informed consent documented by signature

Exclusion Criteria:

• Previous or current use of positional therapy
• Use of home oxygen therapy
• Documented hypoventilation syndrome
• Documented Cheyne-Stokes breathing
• Documented moderate-to-severe or severe obstructive lung diseases
• Chronic heart failure
• Documented active drug or alcohol abuse
• Known or suspected non-compliance
• Inability to follow the procedures of the study, e.g. due to language problems, documented psychological disorders, documented dementia, etc. of the participant
• Current professional driver or any either documented or reported previous sleep-related driving accidents
• People working with or operating heavy machinery
• Child-bearing age: female participants who are neither surgically sterilised / hysterectomised nor post-menopausal for longer than 2 years are considered as being of child bearing potential
• Documented unstable, untreated coronary or peripheral artery disease, severe hypertension or hypotension (≥180/110 or ≤90/60 mmHg)
• BMI >40 kg/m2 or body weight >130 kg
• Being the investigator, his/her family members, employees, or other dependent persons