Research on upper limb rehabilitation assessment model based on belief rule base
Rehabilitation assessments hold an irreplaceable role in the field of rehabilitative therapy. However, due to the subjectivity of traditional physicians and the variability of patient conditions, this leads to a lack of detailed grading and inaccurate assessment results. To address this issue, we de...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2025-01-01
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| Series: | Frontiers in Bioengineering and Biotechnology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fbioe.2024.1469598/full |
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| _version_ | 1841558697448308736 |
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| author | Dawei Jiang Zixu Zhao Lijun Wang Chao Zhang Meixuan He Tiejun Ji |
| author_facet | Dawei Jiang Zixu Zhao Lijun Wang Chao Zhang Meixuan He Tiejun Ji |
| author_sort | Dawei Jiang |
| collection | DOAJ |
| description | Rehabilitation assessments hold an irreplaceable role in the field of rehabilitative therapy. However, due to the subjectivity of traditional physicians and the variability of patient conditions, this leads to a lack of detailed grading and inaccurate assessment results. To address this issue, we developed an upper limb rehabilitation evaluation model. This model integrates muscle strength assessment methods and the Belief Rule Base (BRB), along with qualitative knowledge such as clinical rehabilitation theories and expert experiences. It also utilizes training data from actual patients, collected by an upper limb rehabilitation robot. We then optimized the BRB model’s evaluation accuracy using the Fmincon algorithm and compared its result with commonly used methods such as the Back Propagation (BP) neural network and Support Vector Machine (SVM). This comparison validated the effectiveness and advancement of our BRB approach. This work has laid both a theoretical and practical groundwork for developing a clinical decision support system based on the BRB for upper limb rehabilitation evaluations. |
| format | Article |
| id | doaj-art-6c6f24c65b9843188efd6d6d9e5be784 |
| institution | Kabale University |
| issn | 2296-4185 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Bioengineering and Biotechnology |
| spelling | doaj-art-6c6f24c65b9843188efd6d6d9e5be7842025-01-06T06:59:35ZengFrontiers Media S.A.Frontiers in Bioengineering and Biotechnology2296-41852025-01-011210.3389/fbioe.2024.14695981469598Research on upper limb rehabilitation assessment model based on belief rule baseDawei Jiang0Zixu Zhao1Lijun Wang2Chao Zhang3Meixuan He4Tiejun Ji5Institute of Technology, Changchun University of Technology, Changchun, ChinaComputer Science and Engineering, Changchun University of Technology, Changchun, ChinaInstitute of Technology, Changchun University of Technology, Changchun, ChinaInstitute of Applied Technology, Changchun University of Technology, Changchun, ChinaSchool of Mechanical and Vehicular Engineering, Beijing Institute of Technology, Beijing, ChinaRehabilitation Department, Jilin Electric Power Hospital, Changchun, ChinaRehabilitation assessments hold an irreplaceable role in the field of rehabilitative therapy. However, due to the subjectivity of traditional physicians and the variability of patient conditions, this leads to a lack of detailed grading and inaccurate assessment results. To address this issue, we developed an upper limb rehabilitation evaluation model. This model integrates muscle strength assessment methods and the Belief Rule Base (BRB), along with qualitative knowledge such as clinical rehabilitation theories and expert experiences. It also utilizes training data from actual patients, collected by an upper limb rehabilitation robot. We then optimized the BRB model’s evaluation accuracy using the Fmincon algorithm and compared its result with commonly used methods such as the Back Propagation (BP) neural network and Support Vector Machine (SVM). This comparison validated the effectiveness and advancement of our BRB approach. This work has laid both a theoretical and practical groundwork for developing a clinical decision support system based on the BRB for upper limb rehabilitation evaluations.https://www.frontiersin.org/articles/10.3389/fbioe.2024.1469598/fullupper limb rehabilitationrehabilitation assessmentbelief rule baseexpert knowledgeevidential reasoning |
| spellingShingle | Dawei Jiang Zixu Zhao Lijun Wang Chao Zhang Meixuan He Tiejun Ji Research on upper limb rehabilitation assessment model based on belief rule base Frontiers in Bioengineering and Biotechnology upper limb rehabilitation rehabilitation assessment belief rule base expert knowledge evidential reasoning |
| title | Research on upper limb rehabilitation assessment model based on belief rule base |
| title_full | Research on upper limb rehabilitation assessment model based on belief rule base |
| title_fullStr | Research on upper limb rehabilitation assessment model based on belief rule base |
| title_full_unstemmed | Research on upper limb rehabilitation assessment model based on belief rule base |
| title_short | Research on upper limb rehabilitation assessment model based on belief rule base |
| title_sort | research on upper limb rehabilitation assessment model based on belief rule base |
| topic | upper limb rehabilitation rehabilitation assessment belief rule base expert knowledge evidential reasoning |
| url | https://www.frontiersin.org/articles/10.3389/fbioe.2024.1469598/full |
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