Ensemble hidden Markov models for biosignal analysis

Variational learning theory allows the estimation of posterior probability distributions of model parameters, rather than the parameters themselves. We demonstrate the use of variational learning methods on hidden Markov models with different observation models and apply the HMM to a range of biomedical signals, such as EEG, periodic breathing and RR-interval series.