A self-powered sensing wearable watch application in ship driver metaverse interaction

This paper proposes a self-powered sensing wearable watch (SPS-WW) based on TENG, applied in the metaverse interaction for ship driving (SD-MI). The SPS-WW uses point contact, which has the characteristics of low damping and high response, making it suitable for low-frequency external excitation in driving behavior. The SPS-WW is designed with a gradient distribution of three channels, which helps reduce the impact of ship tilt, thereby enhancing the diversity of signal collection and the accuracy of SD-MI decision-making. Under the excitation of the ship driver's hand movement, the SPS-WW device generates electrical signals on three channels through the friction of the polytetrafluoroethylene (PTFE) sphere and the copper plate. The low-power OpenBCI wirelessly transmits the collected voltage signals to a computer via WIFI. The trained deep learning model is deployed in the computer, which outputs recognition results based on the signals received in real time. The metaverse module, built on Unity and digital twin technology, visualizes the model recognition results in the virtual space. In a real ship's cockpit in China named "Taijiang" with the number 1307, the tested recognition accuracy was 96.18 %.