RF Bandaid: A Fully-Analog and Passive Wireless Interface for Wearable Sensors - Ranganathan, Vaishnavi; Gupta, Sidhant; Lester, Jonathan; Smith, Joshua R.; Tan, Desney (Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 2018)
This paper presents a passive wireless RF sensor platform (RFSP), with only analog components, that harvests energy from an RF source and reflects data as a direct subcarrier modulation, thus making it battery free. A fully-analog architecture results in an ultra-low power device (under 200 μW) with a low component count, reducing the physical footprint. We envision such a platform to enable medical sensing systems that fit on a small bandaid like flexible structure, require no-battery, or charging and are able to provide continuous physiological monitoring. To realize this vision, we have developed and optimized a novel RF architecture that 1) directly maps sensor output to frequency modulation and transmits it to a remote receiver processing unit (RPU). This direct frequency mapping allows all further digitization and computation to be moved to the RPU – reducing power and size requirements on the RFSP; 2) harvests energy from the carrier signal transmitted by a simple continuous wave transmitter, thereby requiring no batteries or supercap; and 3) uses backscatter to communicate with the RPU enabling ultra-low power requirements. The total power consumption of our prototype device leveraging this architecture was measured to be between 35 μW and 160 μW. We demonstrate that the RFSP can harvest sufficient power, sense, and communicate continuously without necessity for energy storage at a distance of 4 m from a transmitter emitting a 915 MHz continuous wave at 26 dBm (0.39 W). Prior backscatter systems typically have power budgets of 1 mW and require energy storage (battery or supercap), RFSP's sub 200 μW power consumption provides a significant improvement and longer range for a given TX power. To demonstrate applicability to real-world health sensing and the flexibility to adapt to different sensors, this paper presents results from breathing, heart rate, temperature, and sound sensing applications.