Impact of workstation and wearable technologies on musculoskeletal disorder risk in computer-intensive sedentary environments

虽然大多数现代工作场所使用计算机，但计算机并不是为人类福祉而设计的。随着计算机使用的增加，工作的静坐性质也随之增加。办公室中的计算机和其他当前通信工具消除了各种物理任务要求。相比之下，人体工程学研究表明，为了保持良好的身心健康和幸福感，至少每30分钟就需要有规律的大动作。这种运动是“低效的”，但“必要的”。一些现有的工具可能会鼓励这种可取的移动。家具设计师正在创造椅子和工作表面选项，以支持更健康的姿势。可调节的办公椅可以适应使用者的座椅和靠背高度和倾斜度，扶手位置，以及灵活的支撑部件，特别是对下背部。摇摆-支撑或悬臂系统进一步鼓励坐着时的移动。工作台的高度可能是可调的，包括坐姿和站立高度的变化；此外，这允许每个人在推荐的略低于放松的肘部高度下工作。不幸的是，当工人可以在不太理想的条件下工作时，雇主却不愿提供这种功能齐全的要素。办公室工作人员普遍存在的严重不适被忽视，尽管这表明肌肉骨骼疾病(MSD)的风险增加。值得注意的是，MSD的缺勤时间超过了平均水平，工人的补偿成本也高于平均水平。在一项有3个工作站的对照环境研究中，姿势姿势(包括不同的运动程度和平面)与背部和颈部疼痛和疲劳的变化有关。这种姿势变化的频率和类型如何影响真实工作环境中的健康指标(生理、知觉和姿势)，目前还只有部分了解。这个项目将使用模式识别和大数据分析技术来研究这个复杂的问题，以确定健康的姿势模式如何随工作或设备干预而变化。该程序将使用非侵入性记录技术并应用模式识别和机器学习方法来分析身体各区域的姿势变化类别。无线可穿戴传感器已经测量了物理参数的变化，这些参数是肌肉骨骼疾病的前兆。该项目将探索这些传感器的能力，以及大多数员工经常使用的智能手机支持的新系统。一旦定义了可靠的模型，我们将衡量1)变化的动态工作站元素，2)定期使用可穿戴消费技术，以及3)结合使用两者的效果。拟议的研究计划将加强我们对这些要素如何在常规工作环境中使用的理解，包括姿势、生理和知觉。

While most modern workplaces use computers, computers were not designed for human well-being. With increasing computer use, the sedentary nature of work rises. Computers and other current communication tools in offices eliminate various physical task requirements. In contrast, ergonomics research shows that regular, large movements are required at least every 30 minutes to maintain good physical and psychological health and well-being. Such movements are `inefficient' but `necessary'. Some existing tools may encourage such desirable movements. Furniture designers are creating chairs and work surface options to support healthier postures. Adjustable office chairs can fit users with seat and backrest height and slope, arm rest location, and flexible supportive components, particularly for the lower back. Rocking-supports or cantilevered systems further encourage movement while seated. Work surfaces may be height-adjustable including variations between sitting and standing heights; furthermore, these allow each person to work at the recommended slightly-below-relaxed-elbow height. Unfortunately, employers are reticent to provide such fully functional elements when workers can work in less-than-optimal conditions. Prevalent significant discomfort amongst office workers is ignored, although it indicates increased Musculoskeletal Disorder (MSD) risk. Notably, MSDs account for longer than average work absences and higher than average workers compensation costs. During a controlled setting study with 3 workstations, postural gestures (including differing degrees and planes of movement) have been associated with changes in back and neck pain and fatigue. How such frequency and type of postural changes affect health indicators (physiology, perception and posture) in real working environments is only partially understood. This program will study this complex question using pattern recognition and big-data analysis techniques, to determine how healthy postural patterns vary with work or equipment interventions. This program will analyse postural variation categories across body regions using non-invasive recording techniques and applying pattern recognition and machine learning methods. Wireless wearable sensors already measure variations in physical parameters which are precursors to Musculoskeletal disorders. This project will explore the ability of these sensors, and new systems supported by intelligent phones that most workers use regularly. Once reliable models are defined, we will measure the effect of 1) varying dynamic workstation elements, 2) regularly using wearable consumer technologies, and 3) using both in combination. The proposed research program will enhance our understanding of how these elements are used in regular work environments accounting for posture, physiology and perception.