  This paper presents a method of choosing number of states of a HMM based on
number of critical points of the motion capture data. The choice of Hidden
Markov Models(HMM) parameters is crucial for recognizer's performance as it is
the first step of the training and cannot be corrected automatically within
HMM. In this article we define predictor of number of states based on number of
critical points of the sequence and test its effectiveness against sample data.
