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.
