Smart Web-Based Platform to Support Physical Rehabilitation
The enhancement of ubiquitous and pervasive computing brings new perspectives in medical rehabilitation. In that sense, the present study proposes a smart, web-based platform to promote the reeducation of patients after hip replacement surgery. This project focuses on two fundamental aspects in the...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2018-04-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | http://www.mdpi.com/1424-8220/18/5/1344 |
| _version_ | 1828351522695544832 |
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| author | Yves Rybarczyk Jan Kleine Deters Clément Cointe Danilo Esparza |
| author_facet | Yves Rybarczyk Jan Kleine Deters Clément Cointe Danilo Esparza |
| author_sort | Yves Rybarczyk |
| collection | DOAJ |
| description | The enhancement of ubiquitous and pervasive computing brings new perspectives in medical rehabilitation. In that sense, the present study proposes a smart, web-based platform to promote the reeducation of patients after hip replacement surgery. This project focuses on two fundamental aspects in the development of a suitable tele-rehabilitation application, which are: (i) being based on an affordable technology, and (ii) providing the patients with a real-time assessment of the correctness of their movements. A probabilistic approach based on the development and training of ten Hidden Markov Models (HMMs) is used to discriminate in real time the main faults in the execution of the therapeutic exercises. Two experiments are designed to evaluate the precision of the algorithm for classifying movements performed in the laboratory and clinical settings, respectively. A comparative analysis of the data shows that the models are as reliable as the physiotherapists to discriminate and identify the motion errors. The results are discussed in terms of the required setup for a successful application in the field and further implementations to improve the accuracy and usability of the system. |
| first_indexed | 2024-04-14T01:40:19Z |
| format | Article |
| id | doaj.art-4e94c6c9ad4242c9b0f419fcf5badc39 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-14T01:40:19Z |
| publishDate | 2018-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-4e94c6c9ad4242c9b0f419fcf5badc392022-12-22T02:19:47ZengMDPI AGSensors1424-82202018-04-01185134410.3390/s18051344s18051344Smart Web-Based Platform to Support Physical RehabilitationYves Rybarczyk0Jan Kleine Deters1Clément Cointe2Danilo Esparza3Intelligent & Interactive Lab (SI<sup>2</sup> Lab), Universidad de Las Américas, Quito 170124, EcuadorFaculty of Electrical Engineering, University of Twente, 217 7500 Enschede, The NetherlandsEcole Normale Supérieure de Paris-Saclay, 94235 Cachan, FranceIntelligent & Interactive Lab (SI<sup>2</sup> Lab), Universidad de Las Américas, Quito 170124, EcuadorThe enhancement of ubiquitous and pervasive computing brings new perspectives in medical rehabilitation. In that sense, the present study proposes a smart, web-based platform to promote the reeducation of patients after hip replacement surgery. This project focuses on two fundamental aspects in the development of a suitable tele-rehabilitation application, which are: (i) being based on an affordable technology, and (ii) providing the patients with a real-time assessment of the correctness of their movements. A probabilistic approach based on the development and training of ten Hidden Markov Models (HMMs) is used to discriminate in real time the main faults in the execution of the therapeutic exercises. Two experiments are designed to evaluate the precision of the algorithm for classifying movements performed in the laboratory and clinical settings, respectively. A comparative analysis of the data shows that the models are as reliable as the physiotherapists to discriminate and identify the motion errors. The results are discussed in terms of the required setup for a successful application in the field and further implementations to improve the accuracy and usability of the system.http://www.mdpi.com/1424-8220/18/5/1344telemedicinemotor rehabilitationmotion assessmentnatural user interfaceHidden Markov Model |
| spellingShingle | Yves Rybarczyk Jan Kleine Deters Clément Cointe Danilo Esparza Smart Web-Based Platform to Support Physical Rehabilitation Sensors telemedicine motor rehabilitation motion assessment natural user interface Hidden Markov Model |
| title | Smart Web-Based Platform to Support Physical Rehabilitation |
| title_full | Smart Web-Based Platform to Support Physical Rehabilitation |
| title_fullStr | Smart Web-Based Platform to Support Physical Rehabilitation |
| title_full_unstemmed | Smart Web-Based Platform to Support Physical Rehabilitation |
| title_short | Smart Web-Based Platform to Support Physical Rehabilitation |
| title_sort | smart web based platform to support physical rehabilitation |
| topic | telemedicine motor rehabilitation motion assessment natural user interface Hidden Markov Model |
| url | http://www.mdpi.com/1424-8220/18/5/1344 |
| work_keys_str_mv | AT yvesrybarczyk smartwebbasedplatformtosupportphysicalrehabilitation AT jankleinedeters smartwebbasedplatformtosupportphysicalrehabilitation AT clementcointe smartwebbasedplatformtosupportphysicalrehabilitation AT daniloesparza smartwebbasedplatformtosupportphysicalrehabilitation |