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An active electronic, high-density epidural paddle array for chronic spinal cord neuromodulation.

Samuel R Parker¹, Jonathan S Calvert¹, Radu Darie¹

¹School of Engineering, Brown University, Providence, RI, United States of America.

Journal of Neural Engineering

|March 19, 2025

Summary

A new smart epidural electrical stimulation (EES) paddle with 60 electrodes and integrated electronics was developed. This high-density device demonstrated reliable 15-month in vivo performance in sheep, enabling advanced neural interface applications.

Keywords:

epidural electrical stimulation hermetic electronics high density array implanted device neuromodulation spinal electrophysiology

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Area of Science:

Biomedical Engineering
Neuroscience
Medical Devices

Background:

Epidural electrical stimulation (EES) is a valuable tool for nervous system research and therapy.
Current EES devices have limited electrode density due to wiring constraints.
There is a need for advanced EES systems with higher electrode counts and integrated electronics.

Purpose of the Study:

To develop and evaluate a novel smart EES paddle with a high-density, programmable electrode array.
To overcome the limitations of traditional EES devices by integrating active electronics on the paddle.
To assess the chronic in vivo performance and biocompatibility of the developed EES device.

Main Methods:

Development of a 60-electrode EES paddle with an embedded active electronic multiplexer.
Sealing electronics in ultra-low profile hermetic packaging.
Conducting ISO 10993-1 biocompatibility tests and leak rate analysis.
Chronic implantation and evaluation of the EES device in ovine lumbosacral spinal cords for 15 months.
Analyzing muscle responses and local field potentials to EES.
Utilizing machine learning for EES parameter inference based on spatial electrode encoding.

Main Results:

The smart EES paddle functioned nominally for over 15 months in vivo without device-related malfunctions.
The integrated multiplexer allowed for flexible and programmable electrode arrangements.
Stereotyped lower extremity muscle responses to stimulation were identified.
High-density recording revealed local field potential responses to EES.
Machine learning models accurately inferred EES parameters, reducing training data requirements.

Conclusions:

A high-density EES paddle with integrated active electronics has been successfully developed and evaluated in a chronic large animal model.
The device enables advanced computation and processing at the neural interface.
This technology opens new possibilities for studying nervous system function and developing therapies for neural injury and dysfunction.