MATEC Web Conf.
Volume 125, 201721st International Conference on Circuits, Systems, Communications and Computers (CSCC 2017)
|Number of page(s)||11|
|Published online||04 October 2017|
Sensor-based supporting mobile system Parkinson disease clinical tests utilising biomedical and RFID technologies
Military University of Technology, Cybernetics Faculty, gen. S. Kaliski Street, Warsaw, Poland
This paper discusses method and tool for assisting clinical tests of pharmaceutical drugs utilising sensors and mobile technologies. Emerging sensor and mobile technologies deliver new opportunities to gather and process medical data. Presented analytical approach implements such observations and delivers new, convenient means for remote patient monitoring. Clinical tests are highly specialised process requiring methodology and tools to support such research. Currently available methods rely mostly on analogue approach (booklets), requiring the clinical test participant to fill in health state daily. Such approach often can be biased by unpunctual, not precise reporting. The mobile device can support this process by automatic scheduling and recording an actual time of reports and most of all it can record the inertial and biometric sensor data during the survey process. Presented analytical method (tremors recognition) and mobile tool offers consistent approach to clinical test assistance transforming and Android smartphone into remote reporting and notification tool. The tool offers additionally features for sensor based diagnostics support for PD tremor recognition as well as specific clonic and tonic symptoms (dedicated for further system extensions towards epilepsy). Capabilities of the system delivers also RFID mechanisms for efficient on-site clinical test authorisation and configuration. This feature simplifies application installation and automatic set-up considering the participant, clinical test configuration, schedule, smartphone and sensor data. Such a composition delivers convenient and reliable tool which can assist patients and medical staff during the process objectifying the clinical tests results and helping to ensure good quality of the data, quickly available and easily accessible.
© The Authors, published by EDP Sciences, 2017
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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