General implementation of HMM in Matlab toolbox

I am not that familier with HMM, but I want to implement in Matlab. I want to use this toolbox HMM Toolbox http://www.mathworks.de/de/help/stats/hidden-markov-models-hmm.html#f10382. I am not sure if I have understood the way I have to implement it. If have many training sequences of states for different classes. So this is the way I would do it:

1. I calculate for every sequence the transition and emisison matrix by [TRANS,EMIS] = hmmestimate(seq,states) which represents a HMM
2. I save these matrix with the information which class belongsI do this for every training sequence
3. If I get an observation sequence for classification I use the hmmviterbi(seq,TRANS,EMIS) function for calculating the "likelyness" with every HMM I have saved.
4. The most "likelyness" one (highest percent) was the HMM I looked for --> I know the class

Is this the way I can implement HMM?

I hope you can give me some hints

Btw. I know that my English is not that good, but I hope it is understandable.

[Namra Akram]

Hey, I am having same issue. No one replied but I hope you figured it out .... can you please tell me the anwer too?? Or direct me to some useful source?? I'll be grateful.