Workplace injuries may be averted through a smartphone app

Scientists are apparently developing a new smartphone app that can help reduce the risk of injuries in employees whose work requires repetitive motions.

Workplace injuries aren’t rare, especially for workers whose jobs involve prolonged repetitive motions or intense physical labour. Having grappled with ways to prevent such injuries, workplaces can now have some respite through technology.

Scientists are apparently developing a new smartphone app that can help reduce the risk of injuries in employees, whose work requires repetitive motion.

Rob Radwin, a professor at the University of Wisconsin-Madison in the US, is working to solve these issues so that a situation where people can get hurt, can be avoided. As per the scientific explanation of the causes of such injuries, it is the strain of repetitive motion that can lead to various musculoskeletal injuries, such as carpal tunnel syndrome or tendonitis in the wrists, arms and shoulders.

Such risks not only cause workers to suffer, but also create massive inefficiencies for companies, through hidden costs, such as worker’s compensation, lost time and reduced productivity. However, a big concern for workplaces is that the current methods for measuring risk of injury are mostly inaccurate and left to subjective judgements. 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 still immense room for error in human observation. Such deductions also require valuable time, expertise and special training in ergonomics and safety. Also, the nuanced actions of many individuals require to be followed over a long period of time. Current technology may be the key to facing, and ultimately fixing, this issue. Researchers have already developed computer vision algorithms to calculate hand activity levels.

The measure for assessing health outcomes will use video footage to visualise and track repetitive motions — establishing pattern recognition— based on repetitive movements, grasps and exertions by the hands. By combining their recent epidemiology findings with this new measurement, they can create a basis for engineers to measure the risk of injuries and redesign certain jobs in the workplace. The ultimate goal is to not only create functional, accurate measurements, but to make them widely accessible to companies via computer vision with smartphones.

Professor Radwin believes that all the required technology to get this app working exists on people’s smartphones — a high-definition camera, a high-speed processor, and the ability to do cloud computing. 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.