Expert System for Neurocognitive Rehabilitation Based on the Transfer of the ACE-R to CHC Model Factors
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61988987%3A17310%2F23%3AA2402HXX" target="_blank" >RIV/61988987:17310/23:A2402HXX - isvavai.cz</a>
Nalezeny alternativní kódy
RIV/00843989:_____/23:E0110095
Výsledek na webu
<a href="https://www.mdpi.com/2227-7390/11/1/7" target="_blank" >https://www.mdpi.com/2227-7390/11/1/7</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.3390/math11010007" target="_blank" >10.3390/math11010007</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Expert System for Neurocognitive Rehabilitation Based on the Transfer of the ACE-R to CHC Model Factors
Popis výsledku v původním jazyce
This article focuses on developing an expert system applicable to the area of neurocognitive rehabilitation. The benefit of this interdisciplinary research is to propose an expert system that has been adapted based on real patients’ results from the Addenbrooke’s cognitive examination (ACE-R). One of this research’s main results is a unique proposal to transfer the ACE-R result to the CHC (Cattell–Horn–Carroll) intelligence model. This unique approach enables transforming the CHC model domains according to the modified ACE-R factor analysis, which has never been used before. The expert system inference results allow the automated optimized design of a neurorehabilitation plan to train patients’ cognitive functions according to the CHC model. A set of tasks in 6 difficulty levels (Level 1–Level 6) was proposed for each of the nine CHC model domains. For each patient, the ACE-R results helped determine specific CHC domains to be rehabilitated as well as the starting game level for the rehabilitation within each domain. The proposed expert system has been verified on real data of 705 patients and achieved an average error of 5.94% for all CHC model domains. The proposed system is to be included in the outcomes of the research project of the Technology Agency of the Czech Republic as a verified procedure for healthcare providers.
Název v anglickém jazyce
Expert System for Neurocognitive Rehabilitation Based on the Transfer of the ACE-R to CHC Model Factors
Popis výsledku anglicky
This article focuses on developing an expert system applicable to the area of neurocognitive rehabilitation. The benefit of this interdisciplinary research is to propose an expert system that has been adapted based on real patients’ results from the Addenbrooke’s cognitive examination (ACE-R). One of this research’s main results is a unique proposal to transfer the ACE-R result to the CHC (Cattell–Horn–Carroll) intelligence model. This unique approach enables transforming the CHC model domains according to the modified ACE-R factor analysis, which has never been used before. The expert system inference results allow the automated optimized design of a neurorehabilitation plan to train patients’ cognitive functions according to the CHC model. A set of tasks in 6 difficulty levels (Level 1–Level 6) was proposed for each of the nine CHC model domains. For each patient, the ACE-R results helped determine specific CHC domains to be rehabilitated as well as the starting game level for the rehabilitation within each domain. The proposed expert system has been verified on real data of 705 patients and achieved an average error of 5.94% for all CHC model domains. The proposed system is to be included in the outcomes of the research project of the Technology Agency of the Czech Republic as a verified procedure for healthcare providers.
Klasifikace
Druh
J<sub>imp</sub> - Článek v periodiku v databázi Web of Science
CEP obor
—
OECD FORD obor
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Návaznosti výsledku
Projekt
<a href="/cs/project/TL02000313" target="_blank" >TL02000313: Chytrý neuro-rehabilitační systém pro pacienty se získaným poškozením mozku v časných stádiích léčby</a><br>
Návaznosti
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach
Ostatní
Rok uplatnění
2023
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název periodika
Mathematics
ISSN
2227-7390
e-ISSN
—
Svazek periodika
—
Číslo periodika v rámci svazku
1
Stát vydavatele periodika
CH - Švýcarská konfederace
Počet stran výsledku
19
Strana od-do
—
Kód UT WoS článku
000909438700001
EID výsledku v databázi Scopus
2-s2.0-85145887833