An indoor localization system to detect areas causing the freezing of gait in Parkinsonians
Florenc Demrozi1,a, Vladislav Bragoi1,b, Federico Tramarin2 and Graziano Pravadelli1,c
1Univ. of Verona, Italy
aflorenc.Demrozi@univr.it
bvladislav.Bragoi@univr.it
cgraziano.Pravadelli@univr.it
2Univ. of Padua, Italy
federico.tramarin@unipd.it
ABSTRACT
People affected by the Parkinson’s disease are often subject to episodes of Freezing of Gait (FoG) near specific areas within their environment. In order to prevent such episodes, this paper presents a low–cost indoor localization system specifically designed to identify these critical areas. The final aim is to exploit the output of this system within a wearable device, to generate a rhythmic stimuli able to prevent the FoG when the person enters a risky area. The proposed localization system is based on a classification engine, which uses a fingerprinting phase for the initial training. It is then dynamically adjusted by exploiting a probabilistic graph model of the environment.
Keywords: Fingerprinting, Indoor localization, Machine learning, Probabilistic graph, Parkinson’s disease.
