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An algorithm is presented in this paper to estimate the activity of a person at each time index through a Bayesian approach. It does not require any pre-processing to identify single activity parts in the signal but can generate some instability in the estimated sequences of activities due to its nature. To circumvent this issue, the decision is enforced with a graph setting constraints between the...
In this paper, an algorithm able to detect epilepsy seizure based on 3D accelerometers and with patient adaptation is presented. This algorithm is based on a Bayesian approach using hidden Markov models for statistical modelling of moves signals. A particular focus is set on the learning procedure and in particular on its initialisation to ensure a good learning and to avoid numerical instability...
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