Spine Posture Detection for Office Workers With Hybrid Machine Learning
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Green Open Access
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Abstract
This study aims to detect bad spine posture using an al-ternative approach that doesn't rely on deep learning or excessive energy. The goal is to improve accuracy and effectiveness without disrupting workflow. A custom dataset was created, numerical inferences were made from posture values, and a hybrid approach using Light Gradient Boosting achieved a 96 % success rate.
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Keywords
Office workers, Sitting posture, Machine learning, Spine posture, Light gradient boosting machine
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Citation
Yildiz, A., Mise, P., Cakar, T., Terzibasioglu, A. M., & Oke, D. (2023, September). Spine posture detection for office workers with hybrid machine learning. In 2023 8th International Conference on Computer Science and Engineering (UBMK). (pp. 486-491).
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486
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491
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Scopus : 0
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48
checked on Jun 11, 2026
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