Neurometers develop machine learning algorithms and cognitive protocols to analyze clinical situations, qualitatively and quantitatively. 

Thanks to the 20+ years academic work, dedicated features were implemented to the machine learning algorithms, to allow the extraction of a set of neural signatures of consciousness and cognitive processing from EEG signals. Supervised learning has then  been performed on the worldwide largest proprietary data base of patients with disorder of consciousness. 

As a result, the algorithm is able to estimate the patient's current cognitive state, and predict the consciousness state.