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，久坐不动的工作性质增加了。办公室中的计算机和其他现有通信工具消除了各种物理任务的要求。 相反，人体工程学研究表明，至少每30分钟需要进行一次有规律的大幅度运动，以保持良好的身心健康和福祉。这种流动"效率低“，但”必要“。 一些现有的工具可能会鼓励这种理想的运动。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。可调节办公椅可以适合用户的座位和靠背的高度和坡度，扶手位置，以及灵活的支撑组件，特别是下背部。摇摆支撑或悬臂系统进一步鼓励运动，而坐着。工作表面可以是高度可调的，包括坐姿和站立高度之间的变化;此外，这些允许每个人在建议的略低于放松肘部的高度下工作。不幸的是，当工人可以在不太理想的条件下工作时，雇主不愿提供这种功能齐全的元件。办公室工作人员普遍存在的显著不适被忽略，尽管它表明肌肉骨骼疾病（MSD）的风险增加。值得注意的是，MSD的缺勤时间比平均值长，而且比平均工人的补偿成本高。 在3个工作站的受控环境研究中，姿势姿势（包括不同程度和平面的运动）与背部和颈部疼痛和疲劳的变化相关。在真实的工作环境中，这种姿势变化的频率和类型如何影响健康指标（生理、感知和姿势）仅被部分理解。该计划将使用模式识别和大数据分析技术研究这个复杂的问题，以确定健康的姿势模式如何随着工作或设备干预而变化。 该计划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可以测量身体参数的变化，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，以及大多数工人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，我们将测量1）不同的动态工作站元素，2）定期使用可穿戴消费者技术，以及3）两者结合使用的效果。拟议的研究计划将提高我们对这些元素如何在常规工作环境中使用姿势，生理和感知的理解。

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.