English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

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.

Wearable sensor-based data analysis for neurological disease symptoms evaluation utilising quantitative approach.