多平面宫运动数据集:IMU测量和气球计
Lee Keidan1,2, Rawan Ibrahim2,3,4, Evyatar Ohayon2
1Department of Anatomy and Anthropology, Faculty of Medical & Health Sciences, Tel- Aviv University, Tel-Aviv, 699780, Israel.
Scientific data
|January 3, 2025
概括
这项研究引入了一种使用Delsys惯性测量单元 (IMU) 传感器计算宫运动范围 (CROM) 的可靠方法. 经过验证的方法为评估和监测椎脊柱状况提供了有价值的工具.
科学领域:
- 生物力学 生物力学
- 医疗技术 医疗技术 医学技术
- 数据科学数据科学数据科学
背景情况:
- 精确测量宫运动范围 (CROM) 对于诊断和管理脊柱疾病至关重要.
- 传统方法在精度和可重复性方面可能存在局限性.
- 惯性测量单元 (IMU) 传感器为客观和可穿戴的运动跟踪提供了潜力.
研究的目的:
- 呈现可复制的数据集和使用Delsys IMU传感器的四基方位分析计算CROM的方法.
- 为了对开发的方法与通用气球计进行验证.
- 评估CROM测量技术的可靠性和可重复性.
主要方法:
- 使用Delsys IMU传感器进行数据采集.
- 应用基于四子的方向分析来计算CROM.
- 招募了14名参与者,分析了504个宫运动跨 sagittal,正面和水平平面.
- 与通用气球计相对应的验证测量.
主要成果:
- 在斜面平面 (R = 0.828 ± 0.051) 显示出强烈的有效性,在正面平面 (R = 0.573 ± 0.138) 显示出中度的有效性.
- 在水平平面的有效性观察到的限制 (R = 0.353 ± 0.122).
- 在所有平面上实现了高可靠性 (Sagittal ICC = 0.855 ± 0.065,正面ICC = 0.855 ± 0.015,水平ICC = 0.945 ± 0.005).
结论:
- 开发的CROM测量模型是帮助诊断,治疗计划和监测椎脊柱状况的宝贵工具.
- 这项研究为宫和脊柱领域的生物力学评估提供了可访问的分析过程.
- 该数据集作为机器学习模型在头部/部位置预测和运动分析中的基准.
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