JoWUA

Abstract

The article presents the results of research on the problem of using the capabilities of Mobile Touch Phones on the Android Platform for monitoring the status of patients with Parkinson’s disease. The purpose of the study is to create a system for user authentication to exclude the collection of incorrect data and data not related to the patient, and for classifying the patient’s state to automate the monitoring process of his state. The article describes the software and hardware architecture of the solution, which includes mobile phone modules, a system for sending data to a server, and separate modules for doctors. An apparatus of fuzzy logic was used to send data to the server; neural networks are used to process the data in the task of classifying the state of patients. Data is collected from the phone in two modes: interactive and background. In the interactive mode, the patients during the day can mark the level of their activity, the presence of dyskinesia, their medications taking and other data that cannot be collected without the participation of the patient himself. In the background monitoring, data are collected from mobile phone sensors. Further, the knowledge that will be extracted from this data using data mining techniques will minimize the interactive part of the monitoring. This will make the monitoring process easy for patients and informative for neurologists.