Capacitive-sensing module with dynamic gesture recognition for automotive applications
Juan Borrego-Carazo, David Castells‐Rufas, Jordi Carrabina, Ernesto Biempica · 2020
Capacitive sensing offers new possibilities for HMI product development. Its short range of interaction entails robustness against environmental noise and its flexibility for integration makes it a genuine technology for embedded systems. In the automotive context, capacitive sensing is explicitly devoted to driver interaction with car functionalities. However, the increasing complexity of captured signals and related interaction procedures impose severe difficulties for a classic modelling approach. Neural networks have demonstrated unbeatable performance in tasks with abundant data. Specifically, recurrent neural networks (RNNs) show excellent performance for tasks with inherent temporal structure. In this article, we develop a capacitive-sensing module that includes RNN-based dynamic gesture recognition, which has a suitable implementation size for embedded automotive applications.