Do you sleep well?
Problem being addressed
While Obstructed Sleep Apnoea is a debilitating condition that can lead to mortality and other serious complications, it is reported that up to 20% of the general population suffer with OSA and over 80% of patients remain incorrectly diagnosed.
A novel method to automatically detect OSA by acquiring trusted OSA signal data, evaluated and selected through its extensive use in previous high-quality studies. The architecture of the model was designed to mathematically calculate and produce maximum results in minimum time by using specific mathematical mechanisms.
Advantages of this solution
The robustness and effectiveness of the proposed model was confirmed with an experiment designed to test and train the model. At this stage, the model is demonstrating excellent ability in identifying the presence and absence of apnoea for both new and unseen data. Besides, this method dramatically reduces the amount of required equipment, time and costs.
Solution originally applied in these industries
Possible New Application of the Work
Electronics and Sensors Industry
The created model is based on time series and can be successfully used with different types of sensors and wearables to analyze the user’s state over time and predict possible changes. It will allow to achieve more accurate results using minimal sensors and equipment.
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