Natural language plays a crucial role in many different and very specific scientific issues. It is also the main aspect of studying specific learning disabilities like dyslexia and helps to design adequate technologies aiming at the specific dyslexia needs. Although dyslexia affects up to 20 % of the worldwide population, no apparatus has been designed to build a user model or user categorization. Such individual categorization, describing individual reading problems and changes over time, may, however, be crucial for further psychological and neurological studies of this disorder.

Fuzzy principles are applicable in a wide range of areas, from economics, business, medical methods to natural science. In natural language, the fuzzy approach deals with linguistic variables, which are transformed from numbers to expressions on predefined scales. Given the complexity of dyslexia needs, it is very challenging to design a new and original fuzzy apparatus tailored specifically to individual needs.

This article introduces the idea and process of using the fuzzy approach for classifying dyslexia symptoms and their progression by obtaining information about individual problems that people with dyslexia deal with. A correct classification is important for the new emerging assistive technologies accommodating text for people with dyslexia and for further clinical and psychological studies of dyslexia and linguistic based problems. As reading problems are diverse, the clinical and psychological studies based on our approach may also be useful in studies of, for example, problems after a stroke, brain tumours, epilepsy, etc.