Neural networks are one type of machine learning. They form the basis for creating autonomous programmes. We have applied artificial intelligence to analyse non-contact sensor signals for the early diagnosis of pulmonary diseases such as COAD.
The aim of the project is to develop and test an innovative solution in the form of a mattress with non-invasive measurement functions of respiratory action parameters (frequency and amplitude) and human temperature, together with remote monitoring of the measured parameters. The results from the electronic devices implemented in the mattress will be sent to neural networks. These algorithms will make diagnostic decisions based on a large amount of data.
The Sorest system monitors the respiratory system in sick, impaired or infirm people. Neural networks analyse the collected signals for early oncological diagnosis.
Range of Application
- palliative and geriatric care;
- home care;
- COAD diagnosis;