手密集型工作与不同职业的手/手腕和其他上半身区域的工作相关的肌肉骨骼疾病(WMSDs)密切相关。包括办公室工作,制造,服务,和医疗保健。解决WMSDs的流行需要可靠和实用的暴露测量。传统的方法,如电测角和光学运动捕捉,虽然可靠,是昂贵和不切实际的现场使用。相比之下,小型惯性测量单元(IMU)可以提供具有成本效益的省时,和用户友好的替代测量手/手腕的姿势在实际工作中。这项研究比较了六种用于估计腕部角度的定向算法,现场设置中的当前黄金标准。六名参与者执行了五项模拟的手部密集型工作任务(涉及相当大的手腕速度和/或手部力量)和一项标准化的手部运动。具有不同平滑度和约束的三种乘法卡尔曼滤波算法与测角仪的一致性最高。这些算法在六个受试者和五个任务中,屈曲/伸展的中值相关系数为0.75-0.78,桡骨/尺骨偏离的中值相关系数为0.64。他们还以与测角器的最低平均绝对差异排名前三名,排名第十,50岁,和手腕屈曲/伸展的第90百分位数(9.3°,2.9°,7.4°,分别)。尽管这项研究的结果对于实际现场使用并不完全可以接受,特别是一些工作任务,这些研究表明,在进一步改进后,基于IMU的腕部角度估计在职业风险评估中可能有用.
Hand-intensive work is strongly associated with work-related musculoskeletal disorders (WMSDs) of the hand/wrist and other upper body regions across diverse occupations, including office work, manufacturing, services, and healthcare. Addressing the prevalence of WMSDs requires reliable and practical exposure measurements. Traditional methods like electrogoniometry and optical motion capture, while reliable, are expensive and impractical for field use. In contrast, small inertial measurement units (IMUs) may provide a cost-effective, time-efficient, and user-friendly alternative for measuring hand/wrist posture during real work. This study compared six orientation algorithms for estimating wrist angles with an electrogoniometer, the current gold standard in field settings. Six participants performed five simulated hand-intensive work tasks (involving considerable wrist velocity and/or hand force) and one standardised hand movement. Three multiplicative Kalman filter algorithms with different smoothers and constraints showed the highest agreement with the goniometer. These algorithms exhibited median correlation coefficients of 0.75-0.78 for flexion/extension and 0.64 for radial/ulnar deviation across the six subjects and five tasks. They also ranked in the top three for the lowest mean absolute differences from the goniometer at the 10th, 50th, and 90th percentiles of wrist flexion/extension (9.3°, 2.9°, and 7.4°, respectively). Although the results of this study are not fully acceptable for practical field use, especially for some work tasks, they indicate that IMU-based wrist angle estimation may be useful in occupational risk assessments after further improvements.