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多平面颈椎运动数据集:惯性测量单元测量与角度计

Multi-Planar Cervical Motion Dataset: IMU Measurements and Goniometer.

作者信息

Keidan Lee, Ibrahim Rawan, Ohayon Evyatar, Pick Chaim G, Been Ella

机构信息

Department of Anatomy and Anthropology, Faculty of Medical & Health Sciences, Tel- Aviv University, Tel-Aviv, 699780, Israel.

Sylvan Adams Sports Institute, Tel Aviv University, Tel Aviv, 699780, Israel.

出版信息

Sci Data. 2025 Jan 3;12(1):13. doi: 10.1038/s41597-024-04351-4.

Abstract

This data descriptor presents a comprehensive and replicable dataset and method for calculating the cervical range of motion (CROM) utilizing quaternion-based orientation analysis from Delsys inertial measurement unit (IMU) sensors. This study was conducted with 14 participants and analyzed 504 cervical movements in the Sagittal, Frontal and Horizontal planes. Validated against a Universal Goniometer and tested for reliability and reproducibility. Analysis showed strong validity in the sagittal plane (R = 0.828 ± 0.051) and moderate in the frontal (R = 0.573 ± 0.138), with limitations in the horizontal plane (R = 0.353 ± 0.122). Reliability was high across all planes (Sagittal: ICC = 0.855 ± 0.065, Frontal: ICC = 0.855 ± 0.015, Horizontal: ICC = 0.945 ± 0.005). Our model for CROM measurements is a valuable tool aiding diagnosis, treatment planning, and monitoring of cervical spine conditions. This study presents an accessible analysis process for biomechanical assessments in cervical and spinal fields. The dataset herein serves as a benchmark for state-of-the-art machine learning models predicting head/neck position, analyzing smoothness of movements, measuring standard motion patterns, and calibrating drift based on movement comparisons.

摘要

本数据描述提供了一个全面且可重复的数据集及方法,用于利用来自Delsys惯性测量单元(IMU)传感器的基于四元数的方向分析来计算颈椎活动范围(CROM)。本研究招募了14名参与者,分析了矢状面、额状面和水平面内的504次颈椎运动。该方法经通用测角仪验证,并测试了其可靠性和可重复性。分析表明,该方法在矢状面具有较强的有效性(R = 0.828 ± 0.051),在额状面为中等有效性(R = 0.573 ± 0.138),在水平面存在局限性(R = 0.353 ± 0.122)。所有平面的可靠性都很高(矢状面:ICC = 0.855 ± 0.065,额状面:ICC = 0.855 ± 0.015,水平面:ICC = 0.945 ± 0.005)。我们的CROM测量模型是辅助颈椎疾病诊断、治疗计划制定和监测的宝贵工具。本研究为颈椎和脊柱领域的生物力学评估提供了一个易于理解的分析过程。本文中的数据集可作为预测头部/颈部位置、分析运动平滑度、测量标准运动模式以及基于运动比较校准漂移的先进机器学习模型的基准。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9263/11698851/8116abffb7cd/41597_2024_4351_Fig1_HTML.jpg

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