Automatic Linguistic Report on the Quality of the Gait of a Person

Gait analysis has been explored thoroughly during the last decade as a behavioral biometric measurement. Some areas of application include: access control, surveillance, activity monitoring and clinical analysis. Our work aims to contribute to the field of human gait modeling by providing a solution based on the computational theory of perceptions. Our model differs significantly from others, e.g., based on machine learning techniques, because we use a linguistic model to represent the subjective designer’s perceptions of the human gait process. This model is easily understood and provides good results. Using accelerometers included in a smart phone, we propose a method for producing a linguistic report about the quality of the gait in terms of homogeneity and symmetry. This type of reports could be used to analyze the evolution of the human gait after a recovery treatment and also for preventing falls in elderly people.