Application of a Modular Wearable System to Track Workers' Fingers Movement in Industrial Environments

The growing demand for superior quality products at higher throughput rates and the constant evolution of industrial environments require an increasingly strict control over manual operations performed by workers. This paper presents a study evaluating the possibility of using a modular wearable system to track workers' fingers motion during different tasks in industrial environments. The system is composed by a series of modules with embedded sensors and electronics, each worn on a single finger, and an external data elaboration device. In order to test system performances, we simulated some actions potentially executed by workers in industrial environments. Achieved results show the system capability in discriminating between different ways of handling a tool, such as a precision screwdriver. In addition, results point out system ability in recognizing grasped objects. Finally, they highlight the possibility to identify different hand gestures to enhance human-robot interaction. System modularity permits using the lowest number of wearable modules that guarantees reliability and minimizes invasiveness at the same time.