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Bioelectric Analyses of an Osseointegrated Intelligent Implant Design System for Amputees

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Magnetoelectrics for Implantable Bioelectronics: Progress to Date.

Fatima Alrashdan¹, Kaiyuan Yang¹, Jacob T Robinson^1,2,3,4

¹Department of Electrical and Computer Engineering, Rice University, 6100 Main St, Houston, Texas 77005, United States.

Accounts of Chemical Research

|October 4, 2024

Summary

This summary is machine-generated.

Magnetoelectric materials enable advanced bioelectronics for neuromodulation. Researchers developed self-rectifying magnetoelectric metamaterials and programmable implants for precise, low-latency neural stimulation and communication.

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Area of Science:

Biomedical Engineering
Materials Science
Neuroscience

Background:

Magnetoelectric (ME) materials couple magnetic and electric properties, enabling tunable device functionalities.
Miniaturized ME transducers for bioelectronics face challenges with high resonant frequencies (>100 kHz) unsuitable for direct neuromodulation (<1 kHz).
Existing off-resonance approaches with magnetoelectric nanoparticles (MENPs) result in neural response latencies of several seconds.

Purpose of the Study:

To overcome the frequency mismatch in ME materials for effective neuromodulation.
To develop miniaturized, wirelessly powered, and precisely controlled bioelectronic devices for neural stimulation.
To enable adaptive neuromodulation and bidirectional communication in implantable devices.

Main Methods:

Investigated rectification methods to produce low-frequency signals from high-frequency ME resonance.
Developed self-rectifying magnetoelectric metamaterials (MNMs) for miniaturized stimulators.
Engineered digitally programmable implants (ME-BIT, DOT) with wireless power and data capabilities, including ME backscatter communication.

Main Results:

Achieved neural modulation in rat models with <5 ms latency using rectified ME stimulators and MNMs.
Demonstrated efficacy of ME-BIT and DOT for peripheral nerve and epidural cortical stimulation.
Established bidirectional communication and wireless power/data transfer using ME transducers for adaptive neuromodulation.

Conclusions:

Rectification techniques and novel MNMs effectively address the frequency mismatch for precise neuromodulation.
Digitally programmable ME implants offer advanced control and wireless capabilities for clinical bioelectronic applications.
ME backscatter communication enables further miniaturization and network integration for future adaptive neuromodulation systems.