Scientists are developing a new smartphone app that can help reduce risk of injuries in employees whose work requires repetitive motion. Strain of repetitive motion can lead to various musculoskeletal injuries, such as carpal tunnel syndrome or tendonitis in the wrists, arms and shoulders. Risks of injury not only cause workers to suffer, but can create massive inefficiencies for companies themselves, through hidden costs such as worker's compensation, lost time and reduced productivity.
"We want to solve these problems before people get hurt," said Rob Radwin, professor at University of Wisconsin-Madison in the US.
Existing methods for measuring risk of injury leave much to be desired: Health and safety professionals often make subjective judgements of risk based on a 0-10 scale of hand activity. Although these measurements provide fairly reasonable predictions, there is immense room for error in human observation, and such conclusions require valuable time, expertise and training in ergonomics and safety.
It also requires following the nuanced actions of many individuals over a long period of time. Current technology may be the key to facing, and ultimately fixing, this issue. Researchers already have developed computer vision algorithms to calculate hand activity level.
The measure for assessing health outcomes, will use their video footage to visualise and track repetitive motions - establishing pattern recognition at which the hand demonstrates repetitive movements, grasps and exertions. By combining their recent epidemiology findings with this new measurement, they can create a basis for engineers to measure risk for injuries and redesign certain jobs in the workplace. The ultimate goal is to not only create functioning, accurate measurements, but to make them widely accessible to companies via computer vision with smartphones.
"I envision an app, and I think all the technology we need exists on my smartphone today: a high definition camera, a high-speed processor, and the ability to do cloud computing," he said.
If Radwin can apply his measures to a smartphone application, manufacturing employers may assess risk of injury of their employees with relative ease. This would involve simply pointing a handheld video device, which is less intrusive and time-consuming than existing methods, such as attaching an instrument to a worker's arm or hand.
