2020
Dias, Sofia Balula; Grammatikopoulou, Athina; Diniz, José Alves; Dimitropoulos, Kosmas; Grammalidis, Nikos; Zilidou, Vicky; Savvidis, Theodore; Konstantinidis, Evdokimos; Bamidis, Panagiotis D; Jaeger, Hagen; Stadtschnitzer, Michael; Silva, Hugo; Telo, Gonçalo; Ioakeimidis, Ioannis; Ntakakis, George; Karayiannis, Fotis; Huchet, Estelle; Hoermann, Vera; Filis, Konstantinos; Theodoropoulou, Elina; Lyberopoulos, George; Kyritsis, Konstantinos; Papadopoulos, Alexandros; Delopoulos, Anastasios; Trivedi, Dhaval; Chaudhuri, Ray K; Klingelhoefer, Lisa; Reichmann, Heinz; Bostantzopoulou, Sevasti; Katsarou, Zoe; Iakovakis, Dimitrios; Hadjidimitriou, Stelios; Charisis, Vasileios; Apostolidis, George; Hadjileontiadis, Leontios J
Innovative Parkinson's Disease Patients' Motor Skills Assessment: The i-PROGNOSIS Paradigm Journal Article
In: Frontiers in Computer Science, 2 , pp. 20, 2020, ISSN: 2624-9898.
Abstract | Links | BibTeX | Tags: i-PROGNOSIS, motor assessment tests, motor skills decline, parkinson's disease (PD), unified parkinson disease rating scale (UPDRS) part III
@article{10.3389/fcomp.2020.00020,
title = {Innovative Parkinson's Disease Patients' Motor Skills Assessment: The i-PROGNOSIS Paradigm},
author = {Sofia Balula Dias and Athina Grammatikopoulou and José Alves Diniz and Kosmas Dimitropoulos and Nikos Grammalidis and Vicky Zilidou and Theodore Savvidis and Evdokimos Konstantinidis and Panagiotis D Bamidis and Hagen Jaeger and Michael Stadtschnitzer and Hugo Silva and Gonçalo Telo and Ioannis Ioakeimidis and George Ntakakis and Fotis Karayiannis and Estelle Huchet and Vera Hoermann and Konstantinos Filis and Elina Theodoropoulou and George Lyberopoulos and Konstantinos Kyritsis and Alexandros Papadopoulos and Anastasios Delopoulos and Dhaval Trivedi and Ray K Chaudhuri and Lisa Klingelhoefer and Heinz Reichmann and Sevasti Bostantzopoulou and Zoe Katsarou and Dimitrios Iakovakis and Stelios Hadjidimitriou and Vasileios Charisis and George Apostolidis and Leontios J Hadjileontiadis},
url = {https://www.frontiersin.org/article/10.3389/fcomp.2020.00020},
doi = {10.3389/fcomp.2020.00020},
issn = {2624-9898},
year = {2020},
date = {2020-01-01},
journal = {Frontiers in Computer Science},
volume = {2},
pages = {20},
abstract = {Being the second most common neurodegenerative disease, Parkinson's disease (PD) can be symptomatically treated, although, unfortunately, it cannot be cured yet. Moreover, diagnosing and assessing PD patients is a complex process, requiring continuous monitoring. In this vein, the design, development, and validation of innovative assessment tools may be helpful in the management of patients with PD, in particular. Based on intelligent ICT interventions, the i-PROGNOSIS project intends to mitigate PD's specific symptoms, such as neurological movement disorders of gait, balance, coordination, and posture, already characterized in the early phase of the disease. From this perspective, an innovative iPrognosis motor assessment tool is presented here, taking into consideration the Unified Parkinson Disease Rating Scale (UPDRS) Part III motor skills testing items, for evaluating the motor skills status. The efficiency of the proposed Assessment Tests to reflect the motor skills status, similarly to the UPDRS Part III items, was validated via 27 participants (18 males; mean age = 62 years},
keywords = {i-PROGNOSIS, motor assessment tests, motor skills decline, parkinson's disease (PD), unified parkinson disease rating scale (UPDRS) part III},
pubstate = {published},
tppubtype = {article}
}