MATEC Web Conf.
Volume 210, 201822nd International Conference on Circuits, Systems, Communications and Computers (CSCC 2018)
|Number of page(s)
|05 October 2018
Wearable sensor-based data analysis for neurological disease symptoms evaluation utilising quantitative approach.
Military University of Technology, Cybernetics Faculty, gen. W. Urbanowicz Street 2, Warsaw, Poland
The paper describes implementation of an analytical method and conclusions of novel approach to clinical trials monitoring and evaluation. Based on clinical trials observations a set of requirements for validating symptoms of neurological diseases have been formulated, concentrating on the ones which can be registered using wearable sensors. The constructed tool utilizes conventional surveying methods supplemented with biomedical sensor for neurological symptoms recognition and intensity evaluation. Developed mobile system is aimed at clinical trials assistance utilising sensor-based state evaluation. Such quantitative approach is a supplement for patient’s subjective evaluation of health state. This work is a discussion on pros and cons of such process composition and its supplementation with technology. Existing methodology relies on health state evaluation based on iteratively answered questionnaires, which in our understanding cannot be fully controlled and reliable. Utilisation of actigraphy and electromyography provides efficient means of some gestures recognition but most of all PD tremor identification and evaluation of their intensity, therefore can be used for ON/OFF state and dyskinesia identification and evaluation. In order to recognise specific states for PD patients (tremors, bradykinesias, rigidity, mental slowness, etc.) a set of additional techniques have been designed and implemented.
© The Authors, published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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