Lifting during manual material handling is a major cause of low-back pain (LBP). As an important risk factor that directly influences the risk of LBP, the Load vertical location (LVL) during lifting needs to be measured and controlled. However, existing solutions for LVL measurement are inefficient, inaccurate, and impractical for real-world workplace environments. To address these problems, an unobtrusive wearable system, including smart insoles and smart wristbands, was proposed to measure LVL accurately in workplace environments. Different from traditional methods which rely on Inertial Measurement Unit (IMU) and suffer from integral drifting errors over time, a novel barometer-based LVL measurement method was proposed in this study. To correct the environment-induced LVL measurement errors in the barometer-based method, a novel Known Vertical Location Update (KVLU) method was proposed. This method calibrates the measured LVL using a known wrist vertical location at known postures during frequently used daily activities such as standing and walking. The proposed wearable system achieved a mean absolute error (MAE) of 5.71 cm in LVL measurement. This result indicates that the proposed system has the potential to reliably measure LVL and assess the risk of LBP in manual lifting tasks.

翻译：手动物料搬运过程中的举重动作是导致下背部疼痛（LBP）的主要原因。作为直接影响LBP风险的重要风险因素，举重过程中的负载垂直位置（LVL）需要被测量与控制。然而，现有的LVL测量方案效率低下、精度不足，且在实际工作场所环境中缺乏实用性。为解决这些问题，本研究提出了一种包含智能鞋垫与智能腕带的非侵入式可穿戴系统，用于在工作场所环境中精确测量LVL。不同于依赖惯性测量单元（IMU）且会随时间产生积分漂移误差的传统方法，本研究提出了一种基于气压计的新型LVL测量方法。为校正基于气压计的方法中由环境因素引起的LVL测量误差，本研究进一步提出了一种新型已知垂直位置更新（KVLU）方法。该方法利用人体在站立、行走等日常高频活动中处于特定姿态时手腕的已知垂直位置，对测量的LVL进行校准。所提出的可穿戴系统在LVL测量中实现了5.71厘米的平均绝对误差（MAE）。该结果表明，本系统具备可靠测量LVL并评估手动举重任务中LBP风险的潜力。