December 1 - 6, 2024
Boston, Massachusetts

Event Supporters

2024 MRS Fall Meeting & Exhibit
EL05.04.05

Magnetoelectric Power for Networks of Wireless Implantable Devices

When and Where

Dec 3, 2024
4:00pm - 4:30pm
Sheraton, Second Floor, Independence West

Presenter(s)

Co-Author(s)

Jacob Robinson1,2

Rice University1,Motif Neurotech, Inc.2

Abstract

Jacob Robinson1,2

Rice University1,Motif Neurotech, Inc.2
Networks of miniature bioelectronic implants promise precise measurement and manipulation of complex physiological systems within the body. By distributing sensing and stimulation nodes throughout the heart, brain, or peripheral nervous system, we can better track and treat diseases and support advanced prosthetic technologies. One significant challenge in creating these bioelectronic networks is the inefficiency of wireless power and data transfer through biological tissue, especially as the number of implants increases. Here, we present a solution using magnetoelectric (ME) wireless data and power transfer. This technology allows networks of millimeter-sized bioelectronic implants to function with increasing power transfer efficiency as more devices are added to the network.<br/><br/>As an example, we show a proof-of-concept network of miniature cardiac pacing devices that can receive power and transmit data from the surface of a beating porcine heart. The scalability of ME WPT enables robust and efficient power transfer in bioelectronic implant networks, paving the way for building wireless closed-loop systems.<br/><br/>Introduction: Enhancing electrical neuromodulation treatments involves increasing the number of stimulation sites and personalizing their placement. Traditionally, this has been limited by the number of contacts that can be wired to a central controller. Wireless power transfer (WPT) technologies, including RF, volume conduction, ultrasound, and light, offer potential solutions. However, these methods face challenges in powering networks of devices efficiently. ME WPT, with its high power densities and wide misalignment tolerances, shows promise for wireless networks of implantable devices. We hypothesized that ME WPT would be suitable for powering such networks due to its minimal mutual coupling and large misalignment tolerances.<br/><br/>Efficient Power Transfer to Networks of Devices: We characterized the power transfer efficiency (PTE) of individual ME films powered by a planar transmitter (TX) coil. We found a linear relationship between the ME film received voltage and the axial magnetic field. The system PTE increased linearly with the number of implants, achieving up to 1.3% efficiency with six films receiving 2.2 mW each. This demonstrates the potential for efficient power transfer in networks of ME-powered implantable devices.<br/><br/>Limits of Scalability for ME-Powered Networks: We investigated the scalability limits of ME-powered networks by simulating the placement of multiple devices below a TX coil. A network of 25 films spaced 1 cm apart caused less than a 1% change in transmitter inductance and achieved an estimated system efficiency of up to 5%. Adding a second layer of 25 films at 2 cm distance increased the network to 50 devices, with an estimated efficiency of 7.5% and a 1.4% change in transmitter inductance.<br/><br/>Discussion: ME power transfer shows significant potential for enabling scalable networks of wireless, battery-free devices for neurostimulation. Its ability to pass through biological tissue with minimal loss at low frequencies allows for efficient power transfer to multiple devices. This technology can simplify the implementation of distributed systems, reducing the need for complex wiring and allowing for precise placement of devices tailored to individual patients' needs. Future developments may include bidirectional communication capabilities, leading to intelligent networks of implanted and wearable devices that enhance human health.

Symposium Organizers

Paschalis Gkoupidenis, Max Planck Institute
Francesca Santoro, Forschungszentrum Jülich/RWTH Aachen University
Ioulia Tzouvadaki, Ghent University
Yoeri van de Burgt, Technische Universiteit Eindhoven

Session Chairs

Zeinab Jahed
Ioulia Tzouvadaki

In this Session