AGIS: Automated Tool Detection & Hand-Arm Vibration Estimation using an unmodified Smartwatch

Abstract

Over the past three decades, it has been known that long-lasting and intense hand-arm vibrations (HAV) can cause serious diseases, such as the Raynaud- / White Finger-Syndrome. In order to protect workers nowadays, the long-term use of tools such as a drill, grinder, rotary hammer etc. underlie strict legal regulations. However, users rarely comply with these regulations because it is quite hard to manually estimate vibration intensity throughout the day. Therefore, we propose a wearable system that automatically counts the daily HAV exposure doses due to the fact that we are able to determine the currently used tool. With the implementation of AGIS, we demonstrate the technical feasibility of using the integrated microphone and accelerometer from a commercial smartwatch. In contrast to prior works, our approach does not require a technical modification of the smartwatch nor an instrumentation of the environment or the tool. A pilot study shows our proofof-concept to be applicable in real workshop environments.