We present a highly elastic strain gauge based on capacitive sensing of parallel, carbon nanotube-based percolation electrodes separated by a dielectric elastomer. The fabrication, relying on vacuum filtration of single-walled carbon nanotubes and hydrophobic patterning of silicone, is both rapid and inexpensive. We demonstrate reliable, linear performance over thousands of cycles at up to 100% strain with less than 3% variability and the highest reported gauge factor for a device of this class (0.99). We further demonstrate use of this sensor in a robotics context to transduce joint angles.

The emerging field of bioelectronic medicine seeks methods for deciphering and modulating electrophysiological activity in the body to attain therapeutic effects at target organs. Current approaches to interfacing with peripheral nerves and muscles rely heavily on wires, creating problems for chronic use, while emerging wireless approaches lack the size scalability necessary to interrogate small-diameter nerves. Furthermore, conventional electrode-based technologies lack the capability to record from nerves with high spatial resolution or to record independently from many discrete sites within a nerve bundle. Here, we demonstrate neural dust, a wireless and scalable ultrasonic backscatter system for powering and communicating with implanted bioelectronics. We show that ultrasound is effective at delivering power to mm-scale devices in tissue; likewise, passive, battery-less communication using backscatter enables high-fidelity transmission of electromyogram (EMG) and electroneurogram (ENG) signals from anesthetized rats. These results highlight the potential for an ultrasound-based neural interface system for advancing future bioelectronics-based therapies.

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