SBIR Phase I: Feasibility of estimating musculoskeletal injury risk of material handling workers with novel wearable devices

SBIR 第一阶段：使用新型可穿戴设备评估物料搬运工人肌肉骨骼损伤风险的可行性

• 批准号: 1548648
• 负责人: Haytham Elhawary
• 金额: $ 15万
• 依托单位: One Million Metrics Corp
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-01-01 至 2016-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1548648&HistoricalAwards=false
• 关键词: SBIR; Phase; Feasibility; estimating; musculoskeletal

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project consists of three major pieces. First is the reduction of musculoskeletal injuries for manual laborers, which already affects 600,000 workers each year. This will improve the quality of life of laborers, since an injury at work affects both their work life and their personal life. Second is to reduce the high costs associated to these injuries that need to be paid by employers, and which are estimated to be $15.2bn a year. These costs challenge the competitiveness of these companies. Thirdly, the worker injuries affect employee morale, absenteeism, productivity loss and employee turnover, all of which are challenges to the efficient running of a company.This Small Business Innovation Research (SBIR) Phase I project will study the feasibility of automatically evaluating the risk of musculoskeletal injury in the workplace using smart wearable devices. These injuries affect hundreds of thousands of workers per year in the US, and cost US companies more than $15bn in direct costs. This research goal depends on the achievement of two technical objectives (i) to prove that the sensors and developed algorithms can differentiate lifting events from other worker activities, and (ii) to demonstrate that the data collected by the sensors can be used to accurately predict the output of the NIOSH lifting equation, an ergonomics risk model widely accepted in industry. Estimations of the outputs of the equation performed by our device will be compared by those computed manually by a certified ergonomist. These wearable devices can quantify the risk of musculoskeletal injuries continuously over time, providing a deeper understanding of the factors that affect risk and the ability to take measures to reduce that risk before an injury occurs.

这项小型企业创新研究（SBIR）I期项目的更广泛的影响/商业潜力由三个主要内容组成。 首先是减少手动劳动者肌肉骨骼伤害，每年已经影响60万名工人。这将改善劳动者的生活质量，因为工作中的伤害会影响他们的工作生活和个人生活。 其次是减少与雇主需要支付的这些伤害相关的高成本，估计为每年152亿美元。这些成本挑战了这些公司的竞争力。 第三，工人受伤会影响员工的士气，缺勤，生产力损失和员工流失，所有这些都是对公司有效运行的挑战。这项小型企业创新研究（SBIR）I阶段项目将研究使用智能可穿戴设备在工作场所使用Musculoskeletable Inspections在工作场所骨骼受伤的风险的可行性。这些伤害在美国每年影响数十万工人，而美国公司的直接费用超过15亿美元。该研究目标取决于实现两个技术目标（i）的实现，以证明传感器和开发的算法可以区分提升事件与其他工人活动，并且（ii）证明传感器收集的数据可用于准确预测NIOSH提升方程的输出，这是一种在行业中被广泛接受的eniosh升降方程。通过认证的符合人体工程学家手动计算的方程式对我们设备执行的方程式输出的估计。这些可穿戴设备可以随着时间的流逝持续量化肌肉骨骼损伤的风险，从而更深入地了解影响风险的因素以及在受伤发生之前采取措施降低这种风险的能力。