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

Impact of workstation and wearable technologies on musculoskeletal disorder risk in computer-intensive sedentary environments
工作站和可穿戴技术对计算机密集型久坐环境中肌肉骨骼疾病风险的影响
批准号:
RGPIN-2020-05591
负责人:
Black, Nancy
金额:
$1.89万
依托单位:
依托单位国家:
加拿大
项目类别:
Discovery Grants Program - Individual
财政年份:
2022
资助国家:
加拿大
项目状态:
已结题
起止时间:
2022-01-01 至 2023-12-31

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中文摘要
翻译
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。随着电脑使用的增加,久坐不动的工作性质也在增加。办公室里的电脑和其他通讯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,要保持良好的身心健康和幸福,至少每30分钟需要有规律的大运动量。这种运动“效率低下”,但却是“必要的”。一些现有的工具可能会鼓励这种理想的运动。家具设计师正在设计椅子和工作台面,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,扶手的位置,和灵活的支持组件,特别是下背部。摇摆支撑或悬臂式系统进一步鼓励运动,而坐。工作台面的高度可以调节,包括坐姿和站立高度的变化;此外,这些允许每个人在推荐的稍微低于放松肘部的高度工作。不幸的是,当工人可以在不太理想的条件下工作时,雇主不愿提供这些功能齐全的元素。办公室职员普遍存在的严重不适被忽视了,尽管它表明肌肉骨骼疾病(MSD)的风险增加。值得注意的是,msd造成的缺勤时间长于平均水平,员工补偿成本也高于平均水平。在3个工作站的受控环境研究中,姿势姿势(包括不同程度和运动平面)与背部和颈部疼痛和疲劳的变化有关。在实际工作环境中,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),目前还只是部分了解。该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。该计划将使用非侵入性记录技术和应用模式识别和机器学习方法分析身体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,这些变化是肌肉骨骼疾病的前兆。这个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。一旦确定了可靠的模型,我们将测量1)不同动态工作站元素的影响,2)定期使用可穿戴消费技术,以及3)将两者结合使用。拟议的研究计划将加强我们对这些元素如何在常规工作环境中使用的理解,包括姿势、生理和感知。
英文摘要
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.
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A Quantitative Evaluation of User Benefits When Using a Sit-and-Stand Desk With a Gamified Auto-Elevate Feature
  • 批准号:
    561353-2020
  • 项目类别:
    Alliance Grants
  • 资助金额:
    $3.12万
  • 财政年份:
    2021
  • 负责人:
    Black, Nancy
  • 依托单位:
Impact of workstation and wearable technologies on musculoskeletal disorder risk in computer-intensive sedentary environments
  • 批准号:
    RGPIN-2020-05591
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $1.89万
  • 财政年份:
    2021
  • 负责人:
    Black, Nancy
  • 依托单位:
Impact of workstation and wearable technologies on musculoskeletal disorder risk in computer-intensive sedentary environments
  • 批准号:
    RGPIN-2020-05591
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $1.89万
  • 财政年份:
    2020
  • 负责人:
    Black, Nancy
  • 依托单位:
Determining workstation design characteristics which improve posture and reduce musculoskeletal disorder risk in sedentary environments
  • 批准号:
    DDG-2017-00014
  • 项目类别:
    Discovery Development Grant
  • 资助金额:
    $0.73万
  • 财政年份:
    2018
  • 负责人:
    Black, Nancy
  • 依托单位:
海外基金