Facial paralysis is a common clinical condition with the rate from 20 to 25 patients per 100,000 people per year. An objectively quantitative tool to support for medical diagnostics is very necessary and important. This paper proposes a very robust method that overcomes the drawbacks of other techniques to develop this tool. In our research, we use a combination of local binary patterns (LBP) and Gabor filters to calculate the features that are used for training and testing. Experiments show that our results outperform other techniques testing on a dynamic facial expression database.