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.

这个小企业创新研究（SBIR）第一阶段项目的更广泛的影响/商业潜力包括三个主要部分。 首先是减少体力劳动者的肌肉骨骼损伤，每年已经有60万工人受到影响。这将提高劳动者的生活质量，因为工伤既影响他们的工作生活，也影响他们的个人生活。 其次是减少雇主需要支付的与这些伤害相关的高额费用，估计每年为152亿美元。这些成本挑战了这些公司的竞争力。 第三，工伤影响员工士气、缺勤、生产力损失和员工流失，这些都是对企业高效运营的挑战。此次小型企业创新研究（SBIR）第一期项目将研究使用智能可穿戴设备自动评估工作场所肌肉骨骼损伤风险的可行性。这些伤害每年影响美国数十万工人，并使美国公司损失超过150亿美元的直接成本。该研究目标取决于两个技术目标的实现：（i）证明传感器和开发的算法可以将起重事件与其他工人活动区分开来，以及（ii）证明传感器收集的数据可以用于准确预测NIOSH起重方程的输出，这是一种在工业中广泛接受的人体工程学风险模型。由我们的设备执行的方程的输出的估计值将通过由认证的人体工程学家手动计算进行比较。这些可穿戴设备可以随着时间的推移不断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，并能够在损伤发生前采取措施降低风险。