Body-resonance: transmission line-like wireless links enabling high-speed wearable communication
Seamless interaction between humans and Artificial Intelligence-empowered, battery-operated, miniaturized devices is reshaping wearable technology by forming an anthropomorphic artificial nervous system that demands high-speed, low-power connectivity. Besides being radiative, radio frequency links suffer absorption losses in non-line-of-sight scenarios and consume more than tens of milliwatts of power. Electro-quasistatic human body communication provides non-radiative links with ~100X better energy efficiency and ~30X superior signal confinement over radio wave-based wireless. However, it is limited by ~60-70 dB path loss, limited bandwidth, and data rates ≤30 Mbps, insufficient for applications such as High definition streaming, and distributed computing at wearable sensor nodes. To overcome these challenges, we propose Body-Resonance Human Body Communication, which leverages the human body's transmission-line behavior in the near-intermediate field to enhance channel capacity by up to 30X. It achieves approximately 20 dB higher channel gain and a wider bandwidth compared to electro-quasistatic regime, supporting data rates of hundreds of Mbps. Experimental results validate low-loss (~40-50 dB), wideband body channels that are more than 10X less leaky than antenna-based wireless links. Body Resonance can potentially open up the possibilities of immersive augmented/virtual reality and cooperative on-body computing by enabling energy-efficient, high-speed wearable networks across healthcare, defense, and consumer electronics.
Authors
- Shreyas Sen
- Qi Huang (ORCID: https://orcid.org/0000-0002-6808-6504)
- Mayukh Nath (ORCID: https://orcid.org/0000-0002-0305-6048)
- Samyadip Sarkar
- Sarthak Antal
Institutions
- Purdue University West Lafayette (US)
Publication Details
- Journal
- Communications Engineering
- Published
- 2025-12-20
- DOI
- https://doi.org/10.1038/s44172-025-00533-z
- Primary Topic
- Wireless Body Area Networks
- Type
- article
- Field-Weighted Citation Impact
- 0.00