Implementation of a Smartwatch with Machine Learning for Ascertaining Efficacy of Deep Brain Stimulation for Parkinson's Disease Treatment
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21460%2F24%3A00381883" target="_blank" >RIV/68407700:21460/24:00381883 - isvavai.cz</a>
Výsledek na webu
<a href="https://ieeexplore.ieee.org/document/10805665" target="_blank" >https://ieeexplore.ieee.org/document/10805665</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/EHB64556.2024.10805665" target="_blank" >10.1109/EHB64556.2024.10805665</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Implementation of a Smartwatch with Machine Learning for Ascertaining Efficacy of Deep Brain Stimulation for Parkinson's Disease Treatment
Popis výsledku v původním jazyce
The amalgamation of the smartwatch in conjunction with machine learning enables the opportunity to distinguish the efficacy of deep brain stimulation for treating Parkinson's disease. The smartwatch is comprised of an inertial sensor package inclusive of a gyroscope for quantifying the response of deep brain stimulation for a person with Parkinson's disease. The acquired gyroscope signal from the smartwatch can quantify the Parkinson's disease tremor response to prescribed 'On' and 'Off' settings for deep brain stimulation. Through wireless transmission to an email account serving as a provisional Cloud computing resource, the gyroscope signal data can be synthesized to a feature set for machine learning classification. Using a multilayer perceptron neural network, the research successfully demonstrates the ability to attain considerable classification distinction between 'On' and 'Off' settings prescribed to deep brain stimulation for a person with Parkinson's disease using the quantified gyroscope signal data obtained through a smartwatch.
Název v anglickém jazyce
Implementation of a Smartwatch with Machine Learning for Ascertaining Efficacy of Deep Brain Stimulation for Parkinson's Disease Treatment
Popis výsledku anglicky
The amalgamation of the smartwatch in conjunction with machine learning enables the opportunity to distinguish the efficacy of deep brain stimulation for treating Parkinson's disease. The smartwatch is comprised of an inertial sensor package inclusive of a gyroscope for quantifying the response of deep brain stimulation for a person with Parkinson's disease. The acquired gyroscope signal from the smartwatch can quantify the Parkinson's disease tremor response to prescribed 'On' and 'Off' settings for deep brain stimulation. Through wireless transmission to an email account serving as a provisional Cloud computing resource, the gyroscope signal data can be synthesized to a feature set for machine learning classification. Using a multilayer perceptron neural network, the research successfully demonstrates the ability to attain considerable classification distinction between 'On' and 'Off' settings prescribed to deep brain stimulation for a person with Parkinson's disease using the quantified gyroscope signal data obtained through a smartwatch.
Klasifikace
Druh
D - Stať ve sborníku
CEP obor
—
OECD FORD obor
20601 - Medical engineering
Návaznosti výsledku
Projekt
—
Návaznosti
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Ostatní
Rok uplatnění
2024
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název statě ve sborníku
2024 E-Health and Bioengineering Conference (EHB)
ISBN
979-8-3315-3214-7
ISSN
2575-5145
e-ISSN
2575-5145
Počet stran výsledku
4
Strana od-do
319-322
Název nakladatele
IEEE Industrial Electronic Society
Místo vydání
Vienna
Místo konání akce
Iasi
Datum konání akce
14. 11. 2024
Typ akce podle státní příslušnosti
WRD - Celosvětová akce
Kód UT WoS článku
001413708800078