Developing an AI-powered smart insole system to reduce the possibility of back pain among older workers: lessons from the Norwegian construction industry

Abstract

Abstract Blue-collar workers are generally more susceptible to specific health conditions such as musculoskeletal disorders, among which back pain is a significant problem for older workers. This study presents the design of a smart insole system developed as a part of the research and the practicality of its use in the construction industry, including an evaluation of its benefits and limitations. Pressure sensors in the soles generate heatmaps that allow us to identify incorrect posture using an adaptable Artificial Intelligence lifting engine. The data is used to evaluate the lifting actions in real-time and preemptively warn the individuals. Using the principles of participatory design as a starting point, the pilot phase, and testing of the solution, the pre-use survey was conducted among construction workers to understand their experience while interacting with the solution. The user testing period was followed by the feedback and evaluation period, which included getting informal feedback on the system. While it has shown the promise of a new solution, it still needs improved robustness and simpler instructions. Some minor technical challenges must be addressed before moving to the commercial stage. The results are used to evaluate further, improve the system, and make decisions in the product design.