Wearable Antennas for Cross-Body Communication and Human Activity Recognition

Abstract

This paper proposes a novel miniaturized wearable antenna (mosaic antenna) for cross-body communication featuring a superior performance compared to five commonly utilized wearable antenna topologies. The proposed mosaic antenna optimally excites the surface waves to enable cross-body communication yet still with a low profile and a miniaturized size. As a proof-of-concept of the unique capabilities of this antenna, an inkjet-printed flexible wearable prototype on Polytetrafluoroethylene (PTFE, also known as Teflon) has been fabricated in a highly customizable, scalable and low-cost process and has been used as an enabler for human activities recognition coupled with machine learning techniques powered by Google TensorFlow. By utilizing proof-of-concept on-body networks consisting of mosaic antennas, human activity can be detected with an accuracy 91.9% for RF signal-based recognition techniques, despite the variability among different users and environments.

Keywords

• Additive manufacturing
• flexible antenna
• human activity recognition
• machine learning
• minimized antennas
• wearable antennas