STPT: Spatio-Temporal Polychromatic Trajectory Based Elderly Exercise Evaluation System
This paper introduces an elderly exercise evaluation system. To determine the quality of a performed exercise, the authors propose a novel system to generate and use Spatio-Temporal Polychromatic Trajectory (STPT) images. Usually, the elder people need to perform some exercises or take physiotherapy...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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IEEE
2023-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10098793/ |
| _version_ | 1797782167619633152 |
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| author | Riad Ahmed Raiyaan Abdullah Lafifa Jamal |
| author_facet | Riad Ahmed Raiyaan Abdullah Lafifa Jamal |
| author_sort | Riad Ahmed |
| collection | DOAJ |
| description | This paper introduces an elderly exercise evaluation system. To determine the quality of a performed exercise, the authors propose a novel system to generate and use Spatio-Temporal Polychromatic Trajectory (STPT) images. Usually, the elder people need to perform some exercises or take physiotherapy in order to stay healthy both physically and mentally. It becomes difficult to evaluate the quality of their exercise routine without the aid of a trained physiotherapist. The system aims to overcome this problem by allowing elders to record their exercise videos using an easy-to-use Graphical User Interface and evaluate the results. A dataset of 109 subjects performing four types of shoulder exercises several times was created. The videos are labelled as correct or incorrect and an STPT image is generated from each video. Using our newly introduced method, the movement of the elder person is projected into an image which can be input to a Convolutional Neural Network (CNN). The dataset is further augmented to increase accuracy. Using our proposed method, the best model achieved an F1 Score over 90% in three of the four exercises. The CNN is trained based on these clips and the models are added to the backend of the interface. The proposed system requires only an ordinary camera and a computer with an entry level GPU allowing it to be deployed at a large scale. |
| first_indexed | 2024-03-13T00:07:11Z |
| format | Article |
| id | doaj.art-d22c5922d50a4f699b99b9b42af3de76 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-03-13T00:07:11Z |
| publishDate | 2023-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-d22c5922d50a4f699b99b9b42af3de762023-07-12T23:00:08ZengIEEEIEEE Access2169-35362023-01-0111379583797510.1109/ACCESS.2023.326624510098793STPT: Spatio-Temporal Polychromatic Trajectory Based Elderly Exercise Evaluation SystemRiad Ahmed0Raiyaan Abdullah1https://orcid.org/0000-0002-7950-816XLafifa Jamal2https://orcid.org/0000-0002-3314-7514Department of Robotics and Mechatronics Engineering, University of Dhaka, Dhaka, BangladeshDepartment of Robotics and Mechatronics Engineering, University of Dhaka, Dhaka, BangladeshDepartment of Robotics and Mechatronics Engineering, University of Dhaka, Dhaka, BangladeshThis paper introduces an elderly exercise evaluation system. To determine the quality of a performed exercise, the authors propose a novel system to generate and use Spatio-Temporal Polychromatic Trajectory (STPT) images. Usually, the elder people need to perform some exercises or take physiotherapy in order to stay healthy both physically and mentally. It becomes difficult to evaluate the quality of their exercise routine without the aid of a trained physiotherapist. The system aims to overcome this problem by allowing elders to record their exercise videos using an easy-to-use Graphical User Interface and evaluate the results. A dataset of 109 subjects performing four types of shoulder exercises several times was created. The videos are labelled as correct or incorrect and an STPT image is generated from each video. Using our newly introduced method, the movement of the elder person is projected into an image which can be input to a Convolutional Neural Network (CNN). The dataset is further augmented to increase accuracy. Using our proposed method, the best model achieved an F1 Score over 90% in three of the four exercises. The CNN is trained based on these clips and the models are added to the backend of the interface. The proposed system requires only an ordinary camera and a computer with an entry level GPU allowing it to be deployed at a large scale.https://ieeexplore.ieee.org/document/10098793/Elderly assistanceexercise quality evaluationdeep learningspatio-temporal polychromatic trajectory |
| spellingShingle | Riad Ahmed Raiyaan Abdullah Lafifa Jamal STPT: Spatio-Temporal Polychromatic Trajectory Based Elderly Exercise Evaluation System IEEE Access Elderly assistance exercise quality evaluation deep learning spatio-temporal polychromatic trajectory |
| title | STPT: Spatio-Temporal Polychromatic Trajectory Based Elderly Exercise Evaluation System |
| title_full | STPT: Spatio-Temporal Polychromatic Trajectory Based Elderly Exercise Evaluation System |
| title_fullStr | STPT: Spatio-Temporal Polychromatic Trajectory Based Elderly Exercise Evaluation System |
| title_full_unstemmed | STPT: Spatio-Temporal Polychromatic Trajectory Based Elderly Exercise Evaluation System |
| title_short | STPT: Spatio-Temporal Polychromatic Trajectory Based Elderly Exercise Evaluation System |
| title_sort | stpt spatio temporal polychromatic trajectory based elderly exercise evaluation system |
| topic | Elderly assistance exercise quality evaluation deep learning spatio-temporal polychromatic trajectory |
| url | https://ieeexplore.ieee.org/document/10098793/ |
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