This paper presents a complex application for rehabilitation of patients with first and second stage rheumatoid arthritis (RA). The application contains a module for the doctor, for the kinetotherapist, and a module as a game matching the symptoms for each stage of RA. The purpose of this application is to achieve the rehabilitation of the RA hand with support of digital technology and multimodal interaction: leap motion, serious gaming, and neuronal networks. The neural network offers support for patients to perform the exercises at home classifying the correct movement with accuracy of 95%. During the development of the application, various challenges were encountered in terms of populating the database, raising the cubes within the game related to second stage of RA, and the implementation of the neural network. The application was tested by a group of students, resulting in the fact that the degree of mental stress, fatigue in the fingers, wrists and physical exertion were insignificant in most cases.