Add to favorites

#Industry News

This neural implant can be both remotely charged and programmed

Engineers at Rice University’s Brown School of Engineering are touting the first neural implant capable of being programmed and charged remotely with a magnetic field.

Kaiyuan Yang, Jacob Robinson, Zhanghao Yu and Joshua Chen collaborated to develop the integrated MagNI (magnetoelectric neural implant) microsystem, which could allow imbedded devices such as a spinal cord stimulator with a battery-powered magnetic transmitter on a wearable belt, according to a news release.

MagNI is designed to use magnetoelectric transducers that allow the chip to harvest power from an alternating magnetic field outside the body. The system targets applications that require programmable, electrical stimulation of neurons that could help people with epilepsy or Parkinson’s disease, to name a few.

Yang believes MagNI presents clear advantages over current stimulation methods like ultrasound, electromagnetic radiation, inductive coupling and optical technologies. The magnetoelectric effect offers benefits over mainstream methods in both power and data transfer capabilities, according to the researcher.

“This is the first demonstration that you can use a magnetic field to power an implant and also to program the implant,” Yang said in the release. “By integrating magnetoelectric transducers with CMOS (complementary metal-oxide-semiconductor) technologies, we provide a bioelectronic platform for many applications. CMOS is powerful, efficient and cheap for sensing and signal-processing tasks.”

MagNI is designed differently from the standards of care like electromagnetic and optical radiation or inductive coupling in that the system would not create heating problems with the tissues that absorb the signals. Because it can transmit control signals, Yang said the MagNI system is also calibration-free, requiring no internal voltage or timing reference.

Yang and the research team are now working on two-way communication strategies to enable data collection from implants and more applications for the MagNI system.

Details

  • Houston, TX, USA
  • Kaiyuan Yang