A method for configuring a device for detecting a situation from a set of situations where a physical system comprises the following steps: reception of a learning sequence corresponding to a given situation of the physical system; determination of parameters of a hidden-state Markov statistical model recorded in the detection device and relating to the given situation, on the basis of a prior initialization of these parameters. The prior initialization comprises the following steps: determination of a plurality of probability distributions from the learning sequence; distribution of the probability distributions between the various hidden states of the statistical model in question by global optimization of a function of adaptation of these probability distributions to the various hidden states and to impossible transition constraints; and initialization of the parameters of the statistical model in question using given representative probability distributions for each hidden state of the statistical model in question.