MagNI: A Magnetoelectrically Powered and Controlled Wireless Neurostimulating Implant

Abstract

This paper presents the first wireless and programmable neural stimulator leveraging magnetoelectric (ME) effects for power and data transfer. Thanks to low tissue absorption, low misalignment sensitivity and high power transfer efficiency, the ME effect enables safe delivery of high power levels (a few milliwatts) at low resonant frequencies ( 250 kHz) to mm-sized implants deep inside the body (30-mm depth). The presented MagNI (Magnetoelectric Neural Implant) consists of a 1.5-mm2 180-nm CMOS chip, an in-house built 4 2 mm ME film, an energy storage capacitor, and on-board electrodes on a flexible polyimide substrate with a total volume of 8.2 mm3. The chip with a power consumption of 23.7 W includes robust system control and data recovery mechanisms under source amplitude variations (1-V variation tolerance and 0.2-V data modulation depth). The system delivers fully programmable bi-phasic current-controlled stimulation with patterns covering 0.05-to-1.5-mA amplitude, 64-to-512-s pulse width and 0-to-200-Hz repetition frequency for neurostimulation.

Publication
IEEE Transactions on Biomedical Circuits and Systems
Avatar
Zhanghao Yu
PhD 2023, now at Intel
Avatar
Yan He
Ph.D. Student (started in 2018)
Avatar
Kaiyuan Yang
Associate Professor of ECE