Kulkarni Rutuja A, Banerjee Rajit, Wang Vicki Z, Oliart Marcel, Rampulla Verity, Das Prithvi, Koontz Alicia M
Human Engineering Research Laboratories, VA Pittsburgh Healthcare System, Pittsburgh, PA 15206, USA.
Department of Bioengineering, Swanson School of Engineering, University of Pittsburgh, Pittsburgh, PA 15261, USA.
Sensors (Basel). 2025 Sep 11;25(18):5673. doi: 10.3390/s25185673.
Optokinetic motion capture (OMC) is the gold standard for measuring the kinematics associated with lifting posture. Unfortunately, limitations exist, including cost, portability, and marker occlusion. The purpose of this study is to evaluate the agreement between OMC and inertial measurement units (IMUs) for quantifying joint kinematics during squat-pivot and stoop-twist lifting tasks. Ten unimpaired adults wearing both IMUs and OMC markers performed 24 lifting trials. Correlation coefficients and Root Mean Square Error (RMSE) between IMU and OMC time-series signals were computed for trunk and lower-extremity joints. Peak values obtained from each system during each trial were analyzed via Bland-Altman plots. Results show high correlations for trunk, knee, and ankle flexion angles (>0.9) and ankle rotation angles (>0.7). Moderate correlation was found for trunk axial rotation and lateral flexion angles (0.5-0.7). RMSE was under 9° for each angle. Biases between systems ranged from 0.3° to 16°. Both systems were able to detect statistically significant differences in peak angles between the two postures ( < 0.05). IMUs show promise for recording field data on complex lifting tasks.
视动运动捕捉(OMC)是测量与举升姿势相关运动学的金标准。不幸的是,它存在一些局限性,包括成本、便携性和标记遮挡。本研究的目的是评估OMC与惯性测量单元(IMU)在深蹲 - pivot和弯腰 - 扭转举升任务期间量化关节运动学时的一致性。十名未受损的成年人同时佩戴IMU和OMC标记进行了24次举升试验。计算了IMU和OMC时间序列信号在躯干和下肢关节之间的相关系数和均方根误差(RMSE)。通过Bland - Altman图分析每次试验中每个系统获得的峰值。结果显示,躯干、膝盖和脚踝的屈曲角度(> 0.9)以及脚踝旋转角度(> 0.7)具有高度相关性。躯干轴向旋转和侧屈角度的相关性中等(0.5 - 0.7)。每个角度的RMSE均低于9°。系统之间的偏差范围为0.3°至16°。两个系统都能够检测到两种姿势之间峰值角度的统计学显著差异(< 0.05)。IMU在记录复杂举升任务的现场数据方面显示出前景。