Department of Electronic Systems, Aalborg University, 9220 Aalborg, Denmark.
Department of Mechanical, Mechatronics, and Manufacturing Engineering, University of Engineering & Technology Lahore, Faisalabad Campus, Faisalabad 38000, Pakistan.
Sensors (Basel). 2023 May 18;23(10):4863. doi: 10.3390/s23104863.
Continuous ergonomic risk assessment of the human body is critical to avoid various musculoskeletal disorders (MSDs) for people involved in physical jobs. This paper presents a digital upper limb assessment (DULA) system that automatically performs rapid upper limb assessment (RULA) in real-time for the timely intervention and prevention of MSDs. While existing approaches require human resources for computing the RULA score, which is highly subjective and untimely, the proposed DULA achieves automatic and objective assessment of musculoskeletal risks using a wireless sensor band embedded with multi-modal sensors. The system continuously tracks and records upper limb movements and muscle activation levels and automatically generates musculoskeletal risk levels. Moreover, it stores the data in a cloud database for in-depth analysis by a healthcare expert. Limb movements and muscle fatigue levels can also be visually seen using any tablet/computer in real-time. In the paper, algorithms of robust limb motion detection are developed, and an explanation of the system is provided along with the presentation of preliminary results, which validate the effectiveness of the new technology.
持续的人体工程学风险评估对于从事体力劳动的人避免各种肌肉骨骼疾病（MSD）至关重要。本文提出了一种数字上肢评估（DULA）系统，可实时自动进行快速上肢评估（RULA），以便及时进行干预和预防 MSD。虽然现有方法需要人力资源来计算 RULA 评分，但这是高度主观和不及时的，而所提出的 DULA 使用嵌入多模式传感器的无线传感器带实现了对肌肉骨骼风险的自动和客观评估。该系统可连续跟踪和记录上肢运动和肌肉激活水平，并自动生成肌肉骨骼风险水平。此外，它将数据存储在云数据库中，以便医疗保健专家进行深入分析。还可以使用任何平板电脑/计算机实时直观地查看肢体运动和肌肉疲劳水平。本文开发了稳健的肢体运动检测算法，并介绍了系统的工作原理和初步结果，验证了新技术的有效性。
