Behavior modeling in industrial assembly lines using a wrist-worn inertial measurement unit

Abstract

In this study an approach to an imperceptible and reliable worker monitoring system for industrial assembly lines is presented. A single wrist-worn inertial measurement unit is attached to the active wrist of the worker and by using acceleration and angular speed information, the behavior of the worker is recognized. The recognition is done in two steps. First the data are divided into 2-s intervals in which the performed activity is recognized using a knn classifier so that the system is usable online. In the second step, a state machine is used to recognize the completed tasks by searching for continuous, unvarying activity chains. The approach was developed as user-independent, although it can be easily adapted to a user-dependent case. By using the approach, behavior was recognized correctly and, on average, the correct beginning and ending moments of the behavior were missed by only 1 s. Thus a reliable monitoring system can be developed for industrial assembly lines. This work was supported by the EU 6th Framework Program Project XPRESS.