Regression-Based Machine Learning for Predicting Lifting Movement Pattern Change in People with Low Back Pain Article Swipe
Trung C. Phan
,
Adrian Pranata
,
Joshua Farragher
,
Adam L. Bryant
,
Hung T. Nguyen
,
Rifai Chai
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.3390/s24041337
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.3390/s24041337
Machine learning (ML) algorithms are crucial within the realm of healthcare applications. However, a comprehensive assessment of the effectiveness of regression algorithms in predicting alterations in lifting movement patterns has not been conducted. This research represents a pilot investigation using regression-based machine learning techniques to forecast alterations in trunk, hip, and knee movements subsequent to a 12-week strength training for people who have low back pain (LBP). The system uses a feature extraction algorithm to calculate the range of motion in the sagittal plane for the knee, trunk, and hip and 12 different regression machine learning algorithms. The results show that Ensemble Tree with LSBoost demonstrated the utmost accuracy in prognosticating trunk movement. Meanwhile, the Ensemble Tree approach, specifically LSBoost, exhibited the highest predictive precision for hip movement. The Gaussian regression with the kernel chosen as exponential returned the highest prediction accuracy for knee movement. These regression models hold the potential to significantly enhance the precision of visualisation of the treatment output for individuals afflicted with LBP.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/s24041337
- https://www.mdpi.com/1424-8220/24/4/1337/pdf?version=1708338590
- OA Status
- gold
- Cited By
- 9
- References
- 43
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4391944120
All OpenAlex metadata
Raw OpenAlex JSON
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https://openalex.org/W4391944120Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.3390/s24041337Digital Object Identifier
- Title
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Regression-Based Machine Learning for Predicting Lifting Movement Pattern Change in People with Low Back PainWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2024Year of publication
- Publication date
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2024-02-19Full publication date if available
- Authors
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Trung C. Phan, Adrian Pranata, Joshua Farragher, Adam L. Bryant, Hung T. Nguyen, Rifai ChaiList of authors in order
- Landing page
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https://doi.org/10.3390/s24041337Publisher landing page
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https://www.mdpi.com/1424-8220/24/4/1337/pdf?version=1708338590Direct link to full text PDF
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://www.mdpi.com/1424-8220/24/4/1337/pdf?version=1708338590Direct OA link when available
- Concepts
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Artificial intelligence, Machine learning, Random forest, Regression, Computer science, Sagittal plane, Trunk, Regression analysis, Support vector machine, Mathematics, Statistics, Medicine, Radiology, Ecology, BiologyTop concepts (fields/topics) attached by OpenAlex
- Cited by
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9Total citation count in OpenAlex
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2025: 4, 2024: 5Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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