المؤلفون: Sofia Balula Dias, José Alves Diniz, Evdokimos Konstantinidis, Theodore Savvidis, Vicky Zilidou, Panagiotis D. Bamidis, Athina Grammatikopoulou, Kosmas Dimitropoulos, Nikos Grammalidis, Hagen Jaeger, Michael Stadtschnitzer, Hugo Silva, Gonçalo Telo, Ioannis Ioakeimidis, George Ntakakis, Fotis Karayiannis, Estelle Huchet, Vera Hoermann, Konstantinos Filis, Elina Theodoropoulou, George Lyberopoulos, Konstantinos Kyritsis, Alexandros Papadopoulos, Anastasios Depoulos, Dhaval Trivedi, Ray K. Chaudhuri, Lisa Klingelhoefer, Heinz Reichmann, Sevasti Bostantzopoulou, Zoe Katsarou, Dimitrios Iakovakis, Stelios Hadjidimitriou, Vasileios Charisis, George Apostolidis, Leontios J. Hadjileontiadis

المصدر: Frontiers in Psychology, Vol 11 (2021)

مصطلحات موضوعية: human-computer interaction-serious games, co-creation, game-based learning, i-PROGNOSIS, Parkinson’s disease, Psychology, BF1-990

الوصف: Human-Computer Interaction (HCI) and games set a new domain in understanding people’s motivations in gaming, behavioral implications of game play, game adaptation to player preferences and needs for increased engaging experiences in the context of HCI serious games (HCI-SGs). When the latter relate with people’s health status, they can become a part of their daily life as assistive health status monitoring/enhancement systems. Co-designing HCI-SGs can be seen as a combination of art and science that involves a meticulous collaborative process. The design elements in assistive HCI-SGs for Parkinson’s Disease (PD) patients, in particular, are explored in the present work. Within this context, the Game-Based Learning (GBL) design framework is adopted here and its main game-design parameters are explored for the Exergames, Dietarygames, Emotional games, Handwriting games, and Voice games design, drawn from the PD-related i-PROGNOSIS Personalized Game Suite (PGS) (www.i-prognosis.eu) holistic approach. Two main data sources were involved in the study. In particular, the first one includes qualitative data from semi-structured interviews, involving 10 PD patients and four clinicians in the co-creation process of the game design, whereas the second one relates with data from an online questionnaire addressed by 104 participants spanning the whole related spectrum, i.e., PD patients, physicians, software/game developers. Linear regression analysis was employed to identify an adapted GBL framework with the most significant game-design parameters, which efficiently predict the transferability of the PGS beneficial effect to real-life, addressing functional PD symptoms. The findings of this work can assist HCI-SG designers for designing PD-related HCI-SGs, as the most significant game-design factors were identified, in terms of adding value to the role of HCI-SGs in increasing PD patients’ quality of life, optimizing the interaction with personalized HCI-SGs and, hence, fostering a collaborative human-computer symbiosis.

وصف الملف: electronic resource

العلاقة: https://www.frontiersin.org/articles/10.3389/fpsyg.2020.612835/fullTest; https://doaj.org/toc/1664-1078Test

الوصول الحر: https://doaj.org/article/fe38070f027a4084b8423163b62256e2Test

المؤلفون: Sofia Balula Dias, Athina Grammatikopoulou, José Alves Diniz, Kosmas Dimitropoulos, Nikos Grammalidis, Vicky Zilidou, Theodore Savvidis, Evdokimos Konstantinidis, Panagiotis D. Bamidis, Hagen Jaeger, Michael Stadtschnitzer, Hugo Silva, Gonçalo Telo, Ioannis Ioakeimidis, George Ntakakis, Fotis Karayiannis, Estelle Huchet, Vera Hoermann, Konstantinos Filis, Elina Theodoropoulou, George Lyberopoulos, Konstantinos Kyritsis, Alexandros Papadopoulos, Anastasios Delopoulos, Dhaval Trivedi, K. Ray Chaudhuri, Lisa Klingelhoefer, Heinz Reichmann, Sevasti Bostantzopoulou, Zoe Katsarou, Dimitrios Iakovakis, Stelios Hadjidimitriou, Vasileios Charisis, George Apostolidis, Leontios J. Hadjileontiadis

المصدر: Frontiers in Computer Science, Vol 2 (2020)

مصطلحات موضوعية: i-PROGNOSIS, parkinson's disease (PD), motor assessment tests, unified parkinson disease rating scale (UPDRS) part III, motor skills decline, Electronic computers. Computer science, QA75.5-76.95

الوصف: 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, SD = 10.36 years; range, 43–79 years) with early (n = 10) and moderate (n = 17) PD who performed the Assessment Tests. Features from the latter were then correlated with the corresponding clinically assessed UPDRS Part III items, and statistically significant negative correlations (range, −0.364 to −0.802) were identified between the median values of the Assessment Tests and the UPDRS Part III items. In this vein, the iPrognosis Assessment Tests were integrated within the personalized interventions of the i-PROGNOSIS project, providing alternative means of assessing their effect on the PD patient's motor skills enhancement. The promising results presented here elaborate on the concept of using ICT-based assessment means to achieve comparable outcomes with the clinical standards in motor skills assessment.

وصف الملف: electronic resource

العلاقة: https://www.frontiersin.org/article/10.3389/fcomp.2020.00020/fullTest; https://doaj.org/toc/2624-9898Test

الوصول الحر: https://doaj.org/article/4181dc3fe4eb4dbaa33b05c07f23e31cTest

المؤلفون: Vasileios Charisis, Stelios Hadjidimitriou, Dimitrios Iakovakis, Hugo Placido da Silva, Sevasti Bostantzopoulou, Zoe Katsarou, Leontios Hadjileontiadis

الوصف: Bowel sounds (BS), the noises produced by the movement of fluids and gas during the peristaltic movement of intestines, are useful in clinical practice as their auscultation constitutes a traditional technique for identifying gastrointestinal (GI) health status. Assessing patients with GI disturbances presents many challenges for a health professional. In this direction, there are research efforts that focus on computerized BS analysis systems in order to detect GI motility problems.

العلاقة: info:eu-repo/grantAgreement/EC/H2020/690494/; https://zenodo.org/record/3686980Test; https://doi.org/10.5281/zenodo.3686980Test; oai:zenodo.org:3686980

الإتاحة: https://doi.org/10.5281/zenodo.3686980Test
https://doi.org/10.5281/zenodo.3686979Test
https://zenodo.org/record/3686980Test

المؤلفون: Iakovakis Dimitrios, Stelios Hadjidimitriou, Vasileios Charisis, Sevasti Bostantzopoulou, Zoe Katsarou, Leontios J. Hadjileontiadis

المصدر: Scientific Reports

مصطلحات موضوعية: Parkinson's disease (PD), machine learning, keystroke dynamics

الوصف: Parkinson’s disease (PD) is a degenerative movement disorder causing progressive disability that severely affects patients’ quality of life. While early treatment can produce significant benefits for patients, the mildness of many early signs combined with the lack of accessible high-frequency monitoring tools may delay clinical diagnosis. To meet this need, user interaction data from consumer technologies have recently been exploited towards unsupervised screening for PD symptoms in daily life. Similarly, this work proposes a method for detecting fine motor skills decline in early PD patients via analysis of patterns emerging from finger interaction with touchscreen smartphones during natural typing. Our approach relies on low-/higher-order statistical features of keystrokes timing and pressure variables, computed from short typing sessions. Features are fed into a two-stage multi-model classification pipeline that reaches a decision on the subject’s status (PD patient/control) by gradually fusing prediction probabilities obtained for individual typing sessions and keystroke variables. This method achieved an AUC=0.92 and 0.82/0.81 sensitivity/specificity (matched groups of 18 early PD patients/15 controls) with discriminant features plausibly correlating with clinical scores of relevant PD motor symptoms. These findings suggest an improvement over similar approaches, thereby constituting a further step towards unobtrusive early PD detection from routine activities.

العلاقة: info:eu-repo/grantAgreement/EC/H2020/690494/; https://www.nature.com/articles/s41598-018-25999-0.pdfTest; https://zenodo.org/record/1297479Test; https://doi.org/10.1038/s41598-018-25999-0Test; oai:zenodo.org:1297479

الإتاحة: https://doi.org/10.1038/s41598-018-25999-0Test
https://zenodo.org/record/1297479Test

المؤلفون: Dimitrios Iakovakis, Kosmas Dimitropoulos, Sevasti Bostantzopoulou, Sofia B. Dias, Michael Stadtschnitzer, Hagen Jaeger, Evdokimos I. Konstantinidis, Konstantinos Kyritsis, Dhaval Trivedi, Vasileios Charisis, Leontios J. Hadjileontiadis, Vera Hoermann, Zoe Katsarou, Konstantinos Filis, Gonçalo Telo, Athina Grammatikopoulou, José Alves Diniz, Hugo Silva, Nikos Grammalidis, Lisa Klingelhoefer, Stelios Hadjidimitriou, Estelle Huchet, Fotis Karayiannis, George Ntakakis, George Apostolidis, Alexandros Papadopoulos, Vicky Zilidou, Panagiotis D. Bamidis, Ray K. Chaudhuri, Ioannis Ioakeimidis, Theodore Savvidis, Anastasios Depoulos, G. Lyberopoulos, Heinz Reichmann, Elina Theodoropoulou

المساهمون: Publica

المصدر: Frontiers in Psychology
Frontiers in Psychology, Vol 11 (2021)

مصطلحات موضوعية: lcsh:BF1-990, Context (language use), Qualitative property, 02 engineering and technology, Computer-assisted web interviewing, human-computer interaction-serious games, Game design, Quality of life (healthcare), Human–computer interaction, 0202 electrical engineering, electronic engineering, information engineering, Psychology, Adaptation (computer science), Game Developer, Set (psychology), General Psychology, Original Research, i-PROGNOSIS, 05 social sciences, ComputingMilieux_PERSONALCOMPUTING, 050301 education, 020206 networking & telecommunications, game-based learning, lcsh:Psychology, Parkinson’s disease, 0503 education, co-creation

الوصف: Human-Computer Interaction (HCI) and games set a new domain in understanding people’s motivations in gaming, behavioral implications of game play, game adaptation to player preferences and needs for increased engaging experiences in the context of HCI serious games (HCI-SGs). When the latter relate with people’s health status, they can become a part of their daily life as assistive health status monitoring/enhancement systems. Co-designing HCI-SGs can be seen as a combination of art and science that involves a meticulous collaborative process. The design elements in assistive HCI-SGs for Parkinson’s Disease (PD) patients, in particular, are explored in the present work. Within this context, the Game-Based Learning (GBL) design framework is adopted here and its main game-design parameters are explored for the Exergames, Dietarygames, Emotional games, Handwriting games, and Voice games design, drawn from the PD-related i-PROGNOSIS Personalized Game Suite (PGS) (www.i-prognosis.eu) holistic approach. Two main data sources were involved in the study. In particular, the first one includes qualitative data from semi-structured interviews, involving 10 PD patients and four clinicians in the co-creation process of the game design, whereas the second one relates with data from an online questionnaire addressed by 104 participants spanning the whole related spectrum, i.e., PD patients, physicians, software/game developers. Linear regression analysis was employed to identify an adapted GBL framework with the most significant game-design parameters, which efficiently predict the transferability of the PGS beneficial effect to real-life, addressing functional PD symptoms. The findings of this work can assist HCI-SG designers for designing PD-related HCI-SGs, as the most significant game-design factors were identified, in terms of adding value to the role of HCI-SGs in increasing PD patients’ quality of life, optimizing the interaction with personalized HCI-SGs and, hence, fostering a collaborative human-computer symbiosis.

الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::acbe2e20f1b98f3a23f2ceee34dafea0Test
https://doi.org/10.3389/fpsyg.2020.612835Test

المؤلفون: Dhaval Trivedi, Evdokimos I. Konstantinidis, Kosmas Dimitropoulos, Lisa Klingelhoefer, Panagiotis D. Bamidis, Sofia B. Dias, Theodore Savvidis, Sevasti Bostantzopoulou, Leontios J. Hadjileontiadis, Nikos Grammalidis, Zoe Katsarou, José Alves Diniz, Michael Stadtschnitzer, Athina Grammatikopoulou

المصدر: ICIP

مصطلحات موضوعية: medicine.medical_specialty, Motion analysis, Parkinson's disease, Rehabilitation, business.industry, Deep learning, medicine.medical_treatment, Disease, medicine.disease, Field (computer science), Motion (physics), Physical medicine and rehabilitation, medicine, Artificial intelligence, business, Motor skill

الوصف: The primary manifestations of Parkinson Disease (PD) concern abnormalities of movement associated with the constant deterioration of motor skills. Such motor impairment affects patients’ movement accuracy and coordination, disrupting their daily life. Taking into account recent studies stating that computer-based physical therapy games can be used as a PD rehabilitation option, we propose a novel Exergame, the iPrognosis Warming up Game (http://www.i-prognosis.euTest/), as a user-friendly tool that could both serve as a computer-based physical therapy game, as well as a means of accurately and automatically identifying the severity of PD motor symptoms. To this regard, we propose a novel deep learning methodology for motor impairment stage prediction that relies solely on human body motion data extracted from the recorded game sessions. Experimental results using a dataset of both early and advanced PD patients reveal a good classification performance of the proposed methodology, predicting the motor impairment stage of PD patients and paving the way for additional research in the field.

الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_________::bd234e3c415327ee96107427933cb3f1Test
https://doi.org/10.1109/icip40778.2020.9191017Test

المؤلفون: Sofia Balula Dias (9988631), José Alves Diniz (9988634), Evdokimos Konstantinidis (9988637), Theodore Savvidis (9988640), Vicky Zilidou (9988643), Panagiotis D. Bamidis (9988646), Athina Grammatikopoulou (9988649), Kosmas Dimitropoulos (4452610), Nikos Grammalidis (4452619), Hagen Jaeger (6809762), Michael Stadtschnitzer (4968112), Hugo Silva (7361843), Gonçalo Telo (9988652), Ioannis Ioakeimidis (9988655), George Ntakakis (4968109), Fotis Karayiannis (4968091), Estelle Huchet (9988658), Vera Hoermann (9988661), Konstantinos Filis (9988664), Elina Theodoropoulou (9988667), George Lyberopoulos (9988670), Konstantinos Kyritsis (8188227), Alexandros Papadopoulos (8188224), Anastasios Depoulos (9988673), Dhaval Trivedi (6809765), Ray K. Chaudhuri (9988676), Lisa Klingelhoefer (403293), Heinz Reichmann (254641), Sevasti Bostantzopoulou (8493963), Zoe Katsarou (6894134), Dimitrios Iakovakis (4968043), Stelios Hadjidimitriou (4968040), Vasileios Charisis (4968049), George Apostolidis (9988679), Leontios J. Hadjileontiadis (4968052)

مصطلحات موضوعية: Applied Psychology, Clinical Psychology, Developmental and Educational Psychology, Neuroscience and Physiological Psychology, Organizational Behavioral Psychology, Personality, Social and Criminal Psychology, Gender Psychology, Health, Clinical and Counselling Psychology, Industrial and Organisational Psychology, Psychology not elsewhere classified, Psychology and Cognitive Sciences not elsewhere classified, human-computer interaction-serious games, co-creation, game-based learning, i-PROGNOSIS, Parkinson’s disease

الوصف: Human-Computer Interaction (HCI) and games set a new domain in understanding people’s motivations in gaming, behavioral implications of game play, game adaptation to player preferences and needs for increased engaging experiences in the context of HCI serious games (HCI-SGs). When the latter relate with people’s health status, they can become a part of their daily life as assistive health status monitoring/enhancement systems. Co-designing HCI-SGs can be seen as a combination of art and science that involves a meticulous collaborative process. The design elements in assistive HCI-SGs for Parkinson’s Disease (PD) patients, in particular, are explored in the present work. Within this context, the Game-Based Learning (GBL) design framework is adopted here and its main game-design parameters are explored for the Exergames, Dietarygames, Emotional games, Handwriting games, and Voice games design, drawn from the PD-related i-PROGNOSIS Personalized Game Suite (PGS) (www.i-prognosis.eu) holistic approach. Two main data sources were involved in the study. In particular, the first one includes qualitative data from semi-structured interviews, involving 10 PD patients and four clinicians in the co-creation process of the game design, whereas the second one relates with data from an online questionnaire addressed by 104 participants spanning the whole related spectrum, i.e., PD patients, physicians, software/game developers. Linear regression analysis was employed to identify an adapted GBL framework with the most significant game-design parameters, which efficiently predict the transferability of the PGS beneficial effect to real-life, addressing functional PD symptoms. The findings of this work can assist HCI-SG designers for designing PD-related HCI-SGs, as the most significant game-design factors were identified, in terms of adding value to the role of HCI-SGs in increasing PD patients’ quality of life, optimizing the interaction with personalized HCI-SGs and, hence, fostering a collaborative human-computer symbiosis.

العلاقة: https://figshare.com/articles/figure/Image_4_Assistive_HCI-Serious_Games_Co-design_Insights_The_Case_Study_of_i-PROGNOSIS_Personalized_Game_Suite_for_Parkinson_s_Disease_JPEG/13578482Test

الإتاحة: https://doi.org/10.3389/fpsyg.2020.612835.s004Test

المؤلفون: Sofia Balula Dias, José Alves Diniz, Evdokimos Konstantinidis, Theodore Savvidis, Vicky Zilidou, Panagiotis D. Bamidis, Athina Grammatikopoulou, Kosmas Dimitropoulos, Nikos Grammalidis, Hagen Jaeger, Michael Stadtschnitzer, Hugo Silva, Gonçalo Telo, Ioannis Ioakeimidis, George Ntakakis, Fotis Karayiannis, Estelle Huchet, Vera Hoermann, Konstantinos Filis, Elina Theodoropoulou, George Lyberopoulos, Konstantinos Kyritsis, Alexandros Papadopoulos, Anastasios Depoulos, Dhaval Trivedi, Ray K. Chaudhuri, Lisa Klingelhoefer, Heinz Reichmann, Sevasti Bostantzopoulou, Zoe Katsarou, Dimitrios Iakovakis, Stelios Hadjidimitriou, Vasileios Charisis, George Apostolidis, Leontios J. Hadjileontiadis

مصطلحات موضوعية: Applied Psychology, Clinical Psychology, Developmental and Educational Psychology, Neuroscience and Physiological Psychology, Organizational Behavioral Psychology, Personality, Social and Criminal Psychology, Gender Psychology, Health, Clinical and Counselling Psychology, Industrial and Organisational Psychology, Psychology not elsewhere classified, Psychology and Cognitive Sciences not elsewhere classified, human-computer interaction-serious games, co-creation, game-based learning, i-PROGNOSIS, Parkinson’s disease

الوصف: Human-Computer Interaction (HCI) and games set a new domain in understanding people’s motivations in gaming, behavioral implications of game play, game adaptation to player preferences and needs for increased engaging experiences in the context of HCI serious games (HCI-SGs). When the latter relate with people’s health status, they can become a part of their daily life as assistive health status monitoring/enhancement systems. Co-designing HCI-SGs can be seen as a combination of art and science that involves a meticulous collaborative process. The design elements in assistive HCI-SGs for Parkinson’s Disease (PD) patients, in particular, are explored in the present work. Within this context, the Game-Based Learning (GBL) design framework is adopted here and its main game-design parameters are explored for the Exergames, Dietarygames, Emotional games, Handwriting games, and Voice games design, drawn from the PD-related i-PROGNOSIS Personalized Game Suite (PGS) (www.i-prognosis.eu) holistic approach. Two main data sources were involved in the study. In particular, the first one includes qualitative data from semi-structured interviews, involving 10 PD patients and four clinicians in the co-creation process of the game design, whereas the second one relates with data from an online questionnaire addressed by 104 participants spanning the whole related spectrum, i.e., PD patients, physicians, software/game developers. Linear regression analysis was employed to identify an adapted GBL framework with the most significant game-design parameters, which efficiently predict the transferability of the PGS beneficial effect to real-life, addressing functional PD symptoms. The findings of this work can assist HCI-SG designers for designing PD-related HCI-SGs, as the most significant game-design factors were identified, in terms of adding value to the role of HCI-SGs in increasing PD patients’ quality of life, optimizing the interaction with personalized HCI-SGs and, hence, fostering a collaborative human-computer symbiosis.

العلاقة: https://figshare.com/articles/figure/Image_3_Assistive_HCI-Serious_Games_Co-design_Insights_The_Case_Study_of_i-PROGNOSIS_Personalized_Game_Suite_for_Parkinson_s_Disease_JPEG/13578479Test

الإتاحة: https://doi.org/10.3389/fpsyg.2020.612835.s003Test
https://figshare.com/articles/figure/Image_3_Assistive_HCI-Serious_Games_Co-design_Insights_The_Case_Study_of_i-PROGNOSIS_Personalized_Game_Suite_for_Parkinson_s_Disease_JPEG/13578479Test

المؤلفون: Estelle Huchet, Dhaval Trivedi, K. Ray Chaudhuri, Nikos Grammalidis, Sevasti Bostantzopoulou, Vasileios Charisis, Anastasios Delopoulos, Kosmas Dimitropoulos, Zoe Katsarou, Hagen Jaeger, Hugo Silva, Elina Theodoropoulou, Theodore Savvidis, Michael Stadtschnitzer, Sofia B. Dias, Alexandros Papadopoulos, G. Lyberopoulos, Fotis Karayiannis, Konstantinos Filis, Gonçalo Telo, Konstantinos Kyritsis, José Alves Diniz, George Apostolidis, Vicky Zilidou, Vera Hoermann, George Ntakakis, Panagiotis D. Bamidis, Ioannis Ioakeimidis, Dimitrios Iakovakis, Stelios Hadjidimitriou, Heinz Reichmann, Athina Grammatikopoulou, Leontios J. Hadjileontiadis, Evdokimos I. Konstantinidis, Lisa Klingelhoefer

المصدر: Frontiers in Computer Science, Vol 2 (2020)

مصطلحات موضوعية: medicine.medical_specialty, Movement disorders, Parkinson's disease, Computer science, Psychological intervention, 02 engineering and technology, Disease, unified parkinson disease rating scale (UPDRS) part III, lcsh:QA75.5-76.95, parkinson's disease (PD), Physical medicine and rehabilitation, Rating scale, 0202 electrical engineering, electronic engineering, information engineering, medicine, Motor skill, Balance (ability), General Environmental Science, i-PROGNOSIS, General Engineering, 020207 software engineering, medicine.disease, Gait, motor assessment tests, General Earth and Planetary Sciences, 020201 artificial intelligence & image processing, lcsh:Electronic computers. Computer science, medicine.symptom, motor skills decline

الوصف: 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, SD = 10.36 years; range, 43–79 years) with early (n = 10) and moderate (n = 17) PD who performed the Assessment Tests. Features from the latter were then correlated with the corresponding clinically assessed UPDRS Part III items, and statistically significant negative correlations (range, −0.364 to −0.802) were identified between the median values of the Assessment Tests and the UPDRS Part III items. In this vein, the iPrognosis Assessment Tests were integrated within the personalized interventions of the i-PROGNOSIS project, providing alternative means of assessing their effect on the PD patient's motor skills enhancement. The promising results presented here elaborate on the concept of using ICT-based assessment means to achieve comparable outcomes with the clinical standards in motor skills assessment.

الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a7ce85bb215d988c4cfdd8ba3e98cfb3Test

المؤلفون: Evdokimos I. Konstantinidis, Vasileios Charisis, Leontios J. Hadjileontiadis, Theodore Savvidis, Sofia B. Dias, Sevasti Bostantzopoulou, Vicky Zilidou, José Alves Diniz, Panagiotis D. Bamidis, Kosmas Dimitropoulos, Ioannis Ioakeimidis, Athina Grammatikopoulou, Dhaval Trivedi, Nikos Grammalidis, Lisa Klingelhoefer, Stelios Hadjidimitriou, Zoe Katsarou, Michael Stadtschnitzer

المصدر: PETRA

مصطلحات موضوعية: medicine.medical_specialty, Parkinson's disease, 020205 medical informatics, Computer science, Psychological intervention, 02 engineering and technology, Disease, medicine.disease, 3. Good health, Objective assessment, 03 medical and health sciences, 0302 clinical medicine, Quality of life (healthcare), Intervention (counseling), 0202 electrical engineering, electronic engineering, information engineering, medicine, Physical therapy, 030212 general & internal medicine

الوصف: Parkinson's disease (PD) is a chronic and progressive neurodegenerative disease that affects ~7 million people worldwide, without any cure to date; however, it can be symptomatically treated. In this vein, innovative technologies can be used for the objective assessment of clinical symptoms and to provide supportive therapies at home. The present work explores the processes and the outcomes of the i-PROGNOSIS (www.i-prognosis.eu) intervention deployment in three PD clinical centres (Greece, UK, and Germany). For that purpose, 36 PD patients were recruited to voluntarily participate in the i-PROGNOSIS feasibility study, spread across the three different countries. The PD patients interacted with the i-PROGNOSIS system for up-to-three months, mainly within the clinical environment, using the provided iPrognosis Games in dedicated gaming stations that were setup in the corresponding clinical centres. Overall, the results show that the iPrognosis Games were positively evaluated by medical experts. Moreover, based on the collected feedback, the iPrognosis Games have achieved their main goals of providing an innovative, objective and usable system for the monitoring of early PD (motor and non-motor) symptomatology, by providing tools for complementing existing clinical interventions for the improvement of PD patients' quality of life.

الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_________::62003145173e04efc5cebba8ae13f6e5Test
https://doi.org/10.1145/3389189.3397974Test