An unobtrusive expert system to detect freezing of gait during daily living in people with Parkinson's disease

Parkinson's disease is a common neurodegenerative disorder causing several motor symptoms. Gait disorders such as festination and freezing of gait are important clinical problems, since, despite their high impact on patients' quality of life, they are poorly understood and counteracted phenomena due to their episodic nature, heterogeneous manifestation, and drug resistance. Automatic and objective monitoring of gait during daily living may help to increase clinical knowledge about these motor symptoms and to assess the effectiveness of pharmacological and rehabilitation therapies. Despite the effort of researchers in wearable systems for gait monitoring, their effective developing in clinical practice is still absent. An important obstacle to this goal is the aggregation of big data into meaningful information for clinicians. In this paper, an acceptable and usable architecture for 24h gait monitoring is resumed and a solution to obtain aggregate and clinical useful information from collected data is proposed.