Collaborative design of a telerehabilitation system enabling virtual second opinion based on fuzzy logic
Here, the authors present a low cost telerehabilitation system made up of a commercial red–green–blue depth (RGB‐D) camera and a web‐based platform. The authors goal is to monitor and assess subject movement providing acceptable and usable at‐home remote rehabilitation services without the presence...
Main Authors: | , , , , , |
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Format: | Article |
Language: | English |
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Wiley
2018-06-01
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Series: | IET Computer Vision |
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Online Access: | https://doi.org/10.1049/iet-cvi.2017.0114 |
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author | Marianna Capecci Lucio Ciabattoni Francesco Ferracuti Andrea Monteriù Luca Romeo Federica Verdini |
author_facet | Marianna Capecci Lucio Ciabattoni Francesco Ferracuti Andrea Monteriù Luca Romeo Federica Verdini |
author_sort | Marianna Capecci |
collection | DOAJ |
description | Here, the authors present a low cost telerehabilitation system made up of a commercial red–green–blue depth (RGB‐D) camera and a web‐based platform. The authors goal is to monitor and assess subject movement providing acceptable and usable at‐home remote rehabilitation services without the presence of a clinician. Clinical goals, defined by physiotherapists, are firstly translated into motion analysis features. A Takagi Sugeno fuzzy inference system (FIS) is then proposed to evaluate and combine these features into scores. In this stage, the ‘collaborative design’ paradigm is used in depth and complete manner: the contribution of the clinician is not limited only to the rules definition but enters in the core of the evaluation algorithm through the definition of the fuzzy rules. A case study on low back pain rehabilitation involving 40 subjects, 5 exercises, and 4 physiotherapists is then presented to the effectiveness of the proposed system. Results of the validation of the system aimed at the assessment of the reliability of the proposed approach show high correlations between clinician evaluation and FIS scores. In this scenario, due to the high correlation, each FIS could represent a virtual alter‐ego of the physiotherapist which enable a real time and free second opinion. |
first_indexed | 2024-03-12T00:35:48Z |
format | Article |
id | doaj.art-219a990dada047b8b7d041268954976f |
institution | Directory Open Access Journal |
issn | 1751-9632 1751-9640 |
language | English |
last_indexed | 2024-03-12T00:35:48Z |
publishDate | 2018-06-01 |
publisher | Wiley |
record_format | Article |
series | IET Computer Vision |
spelling | doaj.art-219a990dada047b8b7d041268954976f2023-09-15T09:36:27ZengWileyIET Computer Vision1751-96321751-96402018-06-0112450251210.1049/iet-cvi.2017.0114Collaborative design of a telerehabilitation system enabling virtual second opinion based on fuzzy logicMarianna Capecci0Lucio Ciabattoni1Francesco Ferracuti2Andrea Monteriù3Luca Romeo4Federica Verdini5Neurorehabilitation ClinicDepartment of Experimental and Clinical MedicinePolytechnic University of Marche60126AnconaItalyDepartment of Information EngineeringPolytechnic University of Marche60131AnconaItalyDepartment of Information EngineeringPolytechnic University of Marche60131AnconaItalyDepartment of Information EngineeringPolytechnic University of Marche60131AnconaItalyDepartment of Information EngineeringPolytechnic University of Marche60131AnconaItalyDepartment of Information EngineeringPolytechnic University of Marche60131AnconaItalyHere, the authors present a low cost telerehabilitation system made up of a commercial red–green–blue depth (RGB‐D) camera and a web‐based platform. The authors goal is to monitor and assess subject movement providing acceptable and usable at‐home remote rehabilitation services without the presence of a clinician. Clinical goals, defined by physiotherapists, are firstly translated into motion analysis features. A Takagi Sugeno fuzzy inference system (FIS) is then proposed to evaluate and combine these features into scores. In this stage, the ‘collaborative design’ paradigm is used in depth and complete manner: the contribution of the clinician is not limited only to the rules definition but enters in the core of the evaluation algorithm through the definition of the fuzzy rules. A case study on low back pain rehabilitation involving 40 subjects, 5 exercises, and 4 physiotherapists is then presented to the effectiveness of the proposed system. Results of the validation of the system aimed at the assessment of the reliability of the proposed approach show high correlations between clinician evaluation and FIS scores. In this scenario, due to the high correlation, each FIS could represent a virtual alter‐ego of the physiotherapist which enable a real time and free second opinion.https://doi.org/10.1049/iet-cvi.2017.0114collaborative designvirtual second opinionfuzzy logiclow cost telerehabilitation systemcommercial red-green-blue depth cameraweb-based platform |
spellingShingle | Marianna Capecci Lucio Ciabattoni Francesco Ferracuti Andrea Monteriù Luca Romeo Federica Verdini Collaborative design of a telerehabilitation system enabling virtual second opinion based on fuzzy logic IET Computer Vision collaborative design virtual second opinion fuzzy logic low cost telerehabilitation system commercial red-green-blue depth camera web-based platform |
title | Collaborative design of a telerehabilitation system enabling virtual second opinion based on fuzzy logic |
title_full | Collaborative design of a telerehabilitation system enabling virtual second opinion based on fuzzy logic |
title_fullStr | Collaborative design of a telerehabilitation system enabling virtual second opinion based on fuzzy logic |
title_full_unstemmed | Collaborative design of a telerehabilitation system enabling virtual second opinion based on fuzzy logic |
title_short | Collaborative design of a telerehabilitation system enabling virtual second opinion based on fuzzy logic |
title_sort | collaborative design of a telerehabilitation system enabling virtual second opinion based on fuzzy logic |
topic | collaborative design virtual second opinion fuzzy logic low cost telerehabilitation system commercial red-green-blue depth camera web-based platform |
url | https://doi.org/10.1049/iet-cvi.2017.0114 |
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