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Updated: May 27, 2025

Lower Limb Biomechanical Analysis of Healthy Participants

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机器学习增强的背部肌肉强度预测,考虑起重条件和个体特征

Kyung-Sun Lee¹, Jaejin Hwang², Jiyeon Ha³

¹Division of Energy Resources Engineering and Industrial Engineering, Kangwon National University, Republic of Korea.

International journal of occupational safety and ergonomics : JOSE

|February 19, 2025

概括

这项研究发现,性别,前臂姿势和举起高度显著影响背部肌肉力量. 这些发现可以为人体工程设计和康复提供信息,以减少与工作有关的伤害.

科学领域:

生物力学生物力学
职业健康职业健康职业健康
人体工程学就是人体工程学.

背景情况:

腰部疼痛是手工物料处理行业的一个常见问题.
背部肌肉力量是防止这种伤害的关键因素.

研究的目的:

为了研究性,前臂姿势和抬起高度对背部肌肉力量的影响.
使用机器学习识别背部肌肉力量的预测因素.

主要方法:

分析了98名参与者的数据.
机器学习模型的应用,包括线性回归,随机森林和多层感知子 (MLP).

主要成果:

确定了性,前臂姿势和抬起高度对背部力量的显著影响.
男人表现出比女性更大的背部肌肉力量.
与俯卧姿势相比,俯卧前臂姿势增加了10%的力量.
在MLP模型中,预测准确度最高 (r=0.896).

结论:

结果为设计人体工程学工作站和个性化康复计划提供了洞察力.
优化职业安全和医疗保健策略可以减少与工作相关的肌肉骨疾病.

关键词:

背部力量背部力量背部力量前臂姿势前臂姿势多层感知器多层感知器肌肉骨系统疾病肌肉骨疾病预测模型的预测模型.随机的森林随机的森林

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