Supervised Classification of Motor-Rehabilitation Body Movements with RGB Cameras and Pose Tracking Data
The technological evolution allowed the use of a single camera for precise and effective body tracking, reducing the cost and increasing the accessibility of applications in places where depth cameras and wearable sensors are not available. This paper describes and implements a supervised machine le...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Brazilian Computer Society
2022-09-01
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| Series: | Journal on Interactive Systems |
| Subjects: | |
| Online Access: | https://sol.sbc.org.br/journals/index.php/jis/article/view/2409 |
| _version_ | 1811167769978208256 |
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| author | Luis Guilherme Silva Rodrigues Diego Roberto Colombo Dias Marcelo de Paiva Guimarães Alexandre Fonseca Brandão Leonardo C. Rocha Rogério Luiz Iope José Remo Ferreira Brega |
| author_facet | Luis Guilherme Silva Rodrigues Diego Roberto Colombo Dias Marcelo de Paiva Guimarães Alexandre Fonseca Brandão Leonardo C. Rocha Rogério Luiz Iope José Remo Ferreira Brega |
| author_sort | Luis Guilherme Silva Rodrigues |
| collection | DOAJ |
| description | The technological evolution allowed the use of a single camera for precise and effective body tracking, reducing the cost and increasing the accessibility of applications in places where depth cameras and wearable sensors are not available. This paper describes and implements a supervised machine learning process consisting of a mobile application used as a motion capture device which also transforms the data into an input for a machine learning model that classifies upper and lower limbs movements (24 types of human movements). The user performs movements in front of the camera, and the trained model classifies them. We designed the system to work in a motor-rehabilitation context to assist the professional while the patient does physical exercises. The implementation can summarize the movements made during the rehabilitation sessions by counting the repetitions and classifying them when done completely or reached a specific range of motion. |
| first_indexed | 2024-04-10T16:14:35Z |
| format | Article |
| id | doaj.art-2694492f4a00434e83c3d14fc569b183 |
| institution | Directory Open Access Journal |
| issn | 2763-7719 |
| language | English |
| last_indexed | 2024-04-10T16:14:35Z |
| publishDate | 2022-09-01 |
| publisher | Brazilian Computer Society |
| record_format | Article |
| series | Journal on Interactive Systems |
| spelling | doaj.art-2694492f4a00434e83c3d14fc569b1832023-02-09T18:01:17ZengBrazilian Computer SocietyJournal on Interactive Systems2763-77192022-09-0113122123110.5753/jis.2022.24092006Supervised Classification of Motor-Rehabilitation Body Movements with RGB Cameras and Pose Tracking DataLuis Guilherme Silva Rodrigues0https://orcid.org/0000-0001-8729-116XDiego Roberto Colombo Dias1https://orcid.org/0000-0001-9619-2171Marcelo de Paiva Guimarães2https://orcid.org/0000-0001-5026-1581Alexandre Fonseca Brandão3https://orcid.org/0000-0003-3978-8862Leonardo C. Rocha4https://orcid.org/0000-0002-4913-4902Rogério Luiz Iope5https://orcid.org/0000-0002-9462-3350José Remo Ferreira Brega6https://orcid.org/0000-0002-2275-4722Universidade Estadual PaulistaUniversidade Federal de São João del-ReiUniversidade Federal de São PauloUniversidade Estadual de CampinasUniversidade Federal de São João del-ReiUniversidade Estadual PaulistaUniversidade Estadual PaulistaThe technological evolution allowed the use of a single camera for precise and effective body tracking, reducing the cost and increasing the accessibility of applications in places where depth cameras and wearable sensors are not available. This paper describes and implements a supervised machine learning process consisting of a mobile application used as a motion capture device which also transforms the data into an input for a machine learning model that classifies upper and lower limbs movements (24 types of human movements). The user performs movements in front of the camera, and the trained model classifies them. We designed the system to work in a motor-rehabilitation context to assist the professional while the patient does physical exercises. The implementation can summarize the movements made during the rehabilitation sessions by counting the repetitions and classifying them when done completely or reached a specific range of motion.https://sol.sbc.org.br/journals/index.php/jis/article/view/2409classificationcomputer visionmachine learningpose trackingsupervised learningmotor-rehabilitation |
| spellingShingle | Luis Guilherme Silva Rodrigues Diego Roberto Colombo Dias Marcelo de Paiva Guimarães Alexandre Fonseca Brandão Leonardo C. Rocha Rogério Luiz Iope José Remo Ferreira Brega Supervised Classification of Motor-Rehabilitation Body Movements with RGB Cameras and Pose Tracking Data Journal on Interactive Systems classification computer vision machine learning pose tracking supervised learning motor-rehabilitation |
| title | Supervised Classification of Motor-Rehabilitation Body Movements with RGB Cameras and Pose Tracking Data |
| title_full | Supervised Classification of Motor-Rehabilitation Body Movements with RGB Cameras and Pose Tracking Data |
| title_fullStr | Supervised Classification of Motor-Rehabilitation Body Movements with RGB Cameras and Pose Tracking Data |
| title_full_unstemmed | Supervised Classification of Motor-Rehabilitation Body Movements with RGB Cameras and Pose Tracking Data |
| title_short | Supervised Classification of Motor-Rehabilitation Body Movements with RGB Cameras and Pose Tracking Data |
| title_sort | supervised classification of motor rehabilitation body movements with rgb cameras and pose tracking data |
| topic | classification computer vision machine learning pose tracking supervised learning motor-rehabilitation |
| url | https://sol.sbc.org.br/journals/index.php/jis/article/view/2409 |
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