An automatic, continuous and probabilistic sleep stager based on a hidden markov model

We report about an automatic continuous sleep stager which is based on probabilistic principles employing Hidden Markov Models (HMM). Our sleep stager offers the advantage of being objective by not relying on human scorers, having much finer temporal resolution (one second instead of 30 seconds),and being based on solid probabilistic principles rather than a predefined set of rules (Rechtschaffen and Kales). Results obtained for nine whole night sleep recordings are reported.