Development and Use of Devices for Ergonomic Assessment and Comfort Enhancement in Industrial Environments

工业环境中人体工程学评估和舒适度增强设备的开发和使用

• 批准号: RGPIN-2019-05240
• 负责人: Oliver, Michele
• 金额: $ 2.62万
• 依托单位: University of Guelph
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2021
• 资助国家: 加拿大
• 起止时间: 2021-01-01 至 2022-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=738140
• 关键词: Development; Use; Devices; Ergonomic; Assessment

The first objective of this proposal is to understand the effects of muscle fatigue on posture, muscle activation, muscle latency and vibration transmissibility, and then to use the information to further develop active whole-body vibration (WBV) attenuation devices for seats in large mobile equipment. It is well known that large mobile machines expose operators to WBV exposure which results in seated operators experiencing muscle fatigue. However, what is not well understood are the effects of muscle fatigue on posture, muscle activation, muscle latency and vibration transmissibility during WBV exposure. Over the course of this proposal, a series of studies will systematically quantify this for individual sinusoidal vibration axes and combined axis exposures at a number of discrete frequencies before and after participants complete a low back fatiguing protocol. Studies will be conducted on a lab located hexapod robot simulator where participants will sit on a seat attached to the robot platform.  Similar investigations will be conducted using simulations that use vibration recordings obtained from a working machine but implemented on the laboratory located robot where participants will use a VR headset along with joystick controls and gas and brake pedals. Over the course of this proposal a newly designed and built active vibration control device will also be further developed and tested using the same protocols noted above. The second objective of the proposal will be to further develop and use a recently designed wearable wrist device for the assessment of kinematics and kinetics and the prediction of muscles forces during the performance of simulated workplace tasks. Data obtained from the wrist wearable device and fingertip force sensors during simulated workplace tasks performed in the laboratory will be used to create a model of the hand and forearm which will be able to predict muscle forces. The long term objective of this research program is to develop a suite of reasonably priced active vibration control devices which can be used on any seat for a variety of large mobile equipment over a variety of terrains in order to improve ISO 2631-1[10] predicted operator comfort. The second long term objective is to develop and use devices for ergonomic assessment which will provide input data for validated models that predict muscle forces. The ability to accurately predict muscle forces could allow us as engineers to virtually prototype hand tools and tasks with an aim to design them in a way that minimizes muscle force requirements while maintaining neutral wrist postures. Another long term objective is the implementation of machine learning techniques to detect subtle kinematic changes that might occur as a worker is beginning to fatigue so that the device alerts them that they need to take a break and/or change what they're doing.

该建议的第一个目的是了解肌肉疲劳对姿势，肌肉激活，肌肉潜伏期和振动传播的影响，然后使用信息进一步开发主动的全身振动（WBV）衰减设备，以便在大型移动设备中座位。众所周知，大型移动机器将操作员暴露于WBV暴露中，这导致坐着的操作员遇到肌肉疲劳。但是，尚不清楚的是肌肉疲劳对WBV暴露期间肌肉疲劳，肌肉激活，肌肉潜伏期和振动的影响。在本提案的整个过程中，一系列研究将系统地量化单个正弦振动轴和组合轴的组合暴露，并在参与者完成低背部疲劳方案之前和之后的许多离散频率。研究将在位于Hexapod机器人模拟器的实验室进行，参与者将坐在机器人平台上的座位上。将使用使用从工作机器获得的振动记录但在实验室的机器人上实施的振动记录的模拟进行类似的调查，参与者将使用VR耳机以及操纵杆控制，气体和制动踏板。在本提案的整个过程中，新设计和构建的主动振动控制设备也将通过上述相同的协议进行进一步开发和测试。该提案的第二个目标是进一步开发和使用最近设计的可穿戴手腕设备，以评估运动学和动力学，并在执行模拟工作场所任务的过程中对肌肉力量的预测。在实验室执行的模拟工作场所任务中，从腕部可穿戴设备和指尖传感器获得的数据将用于创建手和前臂模型，该模型能够预测肌肉力。该研究计划的长期目标是开发一套价格合理的主动振动控制设备，这些设备可在任何座位上用于各种地形上的各种大型移动设备，以改善ISO 2631-1 [10]预测的操作员舒适性。第二个长期目标是开发和使用设备进行人体工程学评估，该评估将为预测肌肉力量的验证模型提供输入数据。准确预测肌肉力量的能力可以使我们作为工程师几乎原型手动工具和任务，以设计它们的方式，以最大程度地减少肌肉力需求，同时保持中性腕姿势。另一个长期目标是实施机器学习技术，以检测可能在工人开始疲劳时可能发生的细微运动学变化，以便设备警告他们需要休息一下和/或更改自己的工作。