Multimodal Interaction and AI in Rehabilitation of Rheumatoid Arthritis
Currently, there are several devices used in kinetotherapy for rehabilitation and evaluation of movements, but fewer applications that support rehabilitation for people diagnosed with rheumatoid arthritis. In the past several ones were using Microsoft Kinect, other are using Leap Motion and artifici...
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| Format: | Article |
| Language: | English |
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Iuliu Hatieganu University of Medicine and Pharmacy, Cluj-Napoca
2021-09-01
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| Series: | Applied Medical Informatics |
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| Online Access: | https://ami.info.umfcluj.ro/index.php/AMI/article/view/855 |
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| author | Gabriela VARGA Lăcrămioară STOICU-TIVADAR Stelian NICOLA Elena AMARICĂI Oana SUCIU Corina DOBRESCU Elena SÎRBU |
| author_facet | Gabriela VARGA Lăcrămioară STOICU-TIVADAR Stelian NICOLA Elena AMARICĂI Oana SUCIU Corina DOBRESCU Elena SÎRBU |
| author_sort | Gabriela VARGA |
| collection | DOAJ |
| description | Currently, there are several devices used in kinetotherapy for rehabilitation and evaluation of movements, but fewer applications that support rehabilitation for people diagnosed with rheumatoid arthritis. In the past several ones were using Microsoft Kinect, other are using Leap Motion and artificial intelligence, and present gamification features. The paper presents a system for at-home rehabilitation of patients with first and second stages of rheumatoid arthritis (RA) based on multimodal interaction using leap motion, serious gaming and neuronal networks support. The system consists of an application for the doctor - who will give the diagnostic, who can view the actual patients and the deleted ones - and one for the kinetotherapist with two games matching the symptoms for first and second stage of RA. The aim of the game for RA first stage is to increase overall hand mobility through the swipe movement. The purpose of the second game is to recover the grip movement of the hand, placing some 3D models in a box. Through the neuronal network the patients can have feedback from the comfort of their home for the realized exercises. The correct movements are classified with an accuracy of 95%. The technologies used were: Visual Studio 2019, Unity 2018, C# and Python 3.7. In this moment, the application was tested by a group of 10 patients from Medical Centre Sf. Mary of Timişoara from May to June 2021. The fatigue of the fingers and wrist were, in most of the cases small, respectively, too small. Most of the users given positive feedback and confirmed that they would use the application with the aim of rehabilitation. In the current pandemic context such a system would be very useful for both: patients and healthcare workers. In this way, results would be more visible in terms of rehabilitation. |
| first_indexed | 2024-12-13T11:17:43Z |
| format | Article |
| id | doaj.art-9e2fd62822634dfaa6efe08952bd2dfe |
| institution | Directory Open Access Journal |
| issn | 2067-7855 |
| language | English |
| last_indexed | 2024-12-13T11:17:43Z |
| publishDate | 2021-09-01 |
| publisher | Iuliu Hatieganu University of Medicine and Pharmacy, Cluj-Napoca |
| record_format | Article |
| series | Applied Medical Informatics |
| spelling | doaj.art-9e2fd62822634dfaa6efe08952bd2dfe2022-12-21T23:48:35ZengIuliu Hatieganu University of Medicine and Pharmacy, Cluj-NapocaApplied Medical Informatics2067-78552021-09-0143Suppl. S14040855Multimodal Interaction and AI in Rehabilitation of Rheumatoid ArthritisGabriela VARGA0Lăcrămioară STOICU-TIVADAR1Stelian NICOLA2Elena AMARICĂI3Oana SUCIU4Corina DOBRESCU5Elena SÎRBU6Department of Automation and Applied Informatics, Politehnica University of Timisoara, România , P-ta Victoriei no. 2, Timisoara, 300006, RomaniaDepartment of Automation and Applied Informatics, Politehnica University of Timisoara, România , P-ta Victoriei no. 2, Timisoara, 300006, RomaniaDepartment of Automation and Applied Informatics, Politehnica University of Timisoara, România , P-ta Victoriei no. 2, Timisoara, 300006, RomaniaDepartment of Rehabilitation, Physical Medicine and Rheumatology, Victor Babes University of Medicine and Pharmacy, Eftimie Murgu no. 2, Timisoara, 300041, RomaniaDepartment of Rehabilitation, Physical Medicine and Rheumatology, Victor Babes University of Medicine and Pharmacy, Eftimie Murgu no. 2, Timisoara, 300041, RomaniaPrivate practice, Romulus no 62, Timisoara, 300238, RomaniaDepartment of Physical Therapy and Special Motricity, West University of Timisoara, Vasile Parvan Boulevard no 4, Timisoara, 300233, RomaniaCurrently, there are several devices used in kinetotherapy for rehabilitation and evaluation of movements, but fewer applications that support rehabilitation for people diagnosed with rheumatoid arthritis. In the past several ones were using Microsoft Kinect, other are using Leap Motion and artificial intelligence, and present gamification features. The paper presents a system for at-home rehabilitation of patients with first and second stages of rheumatoid arthritis (RA) based on multimodal interaction using leap motion, serious gaming and neuronal networks support. The system consists of an application for the doctor - who will give the diagnostic, who can view the actual patients and the deleted ones - and one for the kinetotherapist with two games matching the symptoms for first and second stage of RA. The aim of the game for RA first stage is to increase overall hand mobility through the swipe movement. The purpose of the second game is to recover the grip movement of the hand, placing some 3D models in a box. Through the neuronal network the patients can have feedback from the comfort of their home for the realized exercises. The correct movements are classified with an accuracy of 95%. The technologies used were: Visual Studio 2019, Unity 2018, C# and Python 3.7. In this moment, the application was tested by a group of 10 patients from Medical Centre Sf. Mary of Timişoara from May to June 2021. The fatigue of the fingers and wrist were, in most of the cases small, respectively, too small. Most of the users given positive feedback and confirmed that they would use the application with the aim of rehabilitation. In the current pandemic context such a system would be very useful for both: patients and healthcare workers. In this way, results would be more visible in terms of rehabilitation.https://ami.info.umfcluj.ro/index.php/AMI/article/view/855virtual realityhand rehabilitationleap motionneuronal networkmultimodal interaction |
| spellingShingle | Gabriela VARGA Lăcrămioară STOICU-TIVADAR Stelian NICOLA Elena AMARICĂI Oana SUCIU Corina DOBRESCU Elena SÎRBU Multimodal Interaction and AI in Rehabilitation of Rheumatoid Arthritis Applied Medical Informatics virtual reality hand rehabilitation leap motion neuronal network multimodal interaction |
| title | Multimodal Interaction and AI in Rehabilitation of Rheumatoid Arthritis |
| title_full | Multimodal Interaction and AI in Rehabilitation of Rheumatoid Arthritis |
| title_fullStr | Multimodal Interaction and AI in Rehabilitation of Rheumatoid Arthritis |
| title_full_unstemmed | Multimodal Interaction and AI in Rehabilitation of Rheumatoid Arthritis |
| title_short | Multimodal Interaction and AI in Rehabilitation of Rheumatoid Arthritis |
| title_sort | multimodal interaction and ai in rehabilitation of rheumatoid arthritis |
| topic | virtual reality hand rehabilitation leap motion neuronal network multimodal interaction |
| url | https://ami.info.umfcluj.ro/index.php/AMI/article/view/855 |
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