Somnofy has been thoroughly tested and evaluated by leading sleep researchers from the University of Bergen.
Somnofy has been validated against polysomnography (PSG)
Polysomnography is a clinical neurophysiological method used to study sleep and the changes that occur during sleep. Electrodes continuously record various bodily functions, including brainwaves (EEG), eye movements (EOG), muscle tone (EMG), heart rate (EKG), and breathing patterns. This method is considered the most reliable way to measure sleep today but requires advanced equipment.
Somnofy was validated against PSG by researchers from the University of Bergen and the Norwegian University of Science and Technology in 2020. The validation study was published in the prestigious journal Sleep Medicine.
About the Study
A total of 71 nights were measured from 71 different participants. Of these, 43 were women, and the average age was 28.9 years (ranging from 19 to 61 years).
Based on this dataset, machine learning has trained Somnofy algorithms to interpret sleep data with very high accuracy. Somnofy measures breathing rate and movement with over 99% accuracy. Whether a person is asleep or awake is correctly identified in 95% of cases. The sleep phase a person is in is accurately determined with 89% accuracy.
Conclusion: Somnofy showed high accuracy compared to medical sleep measurement (polysomnography).
These results apply to healthy individuals aged 19-61 years. For older or younger individuals, we cannot definitively say whether the accuracy is the same, higher, or lower. Various medical conditions can also affect accuracy.
What About Older Individuals?
For individuals over 61 years old, we do not have data to specify the accuracy of sleep analyses. What we do know is that Somnofy can accurately assess breathing rate and movement. Therefore, it can indicate whether the individual is calm or restless and track their breathing rate over time. This provides valuable data that can offer insights into well-being, general health, existing pains, or infections.
What About Individuals with Physical Disabilities?
If a service user has a "normal" pattern of movement during the night (no spasms, paralysis, etc.), the accuracy is assumed to be similar to what was described above. Significant deviations from normal nighttime movement can lead to inaccuracies in measuring wakefulness and sleep phases.
References: