Bioimplantable Wearable Sensor Applicable to Brain Connection

Successfully developed a flexible neural electrode that does not corrode in vivo, can measure neural signals over extended periods, and efficiently deliver electrical stimulation to cells.

The Electronics and Telecommunications Research Institute (ETRI) announced the successful development of a neural electrode composed solely of biocompatible gold (Au) and fluorine (F)-based polymers with excellent chemical durability, no water absorption or permeation. The results were published in ACS Applied Materials & Interfaces (ACSAMI), a journal published by the American Chemical Society.

The developed neural electrode has no chemical corrosion factors, enabling long-term stability when implanted in bodily fluids composed of various substances. Therefore, stable detection of brain neural signals and continuous stimulation of neural tissue are possible.

Silicon (Si)-based electrodes have strong mechanical strength but suffer from severe biological rejection responses. In contrast, electrodes based on flexible polymers exhibit minimal biological rejection but have encountered difficulties in bonding between the polymer substrate and metal electrode. Typically, adhesive layers such as chromium (Cr) and titanium (Ti) are used, but these adhesive layers have suffered from corrosion in the biological environment.

To address this issue, ETRI researchers improved adhesion between the gold (Au) electrode and a fluorine (F)-based polymer film with minimal hygroscopicity through plasma treatment. Additionally, they enhanced adhesion by heat-pressing the plasma-treated fluorine-based polymer film below its melting point to create chemical bonding between fluorine-based polymer layers.

Through this process, the researchers fabricated a 16-channel gold neural electrode with a diameter of 100 μm (micrometer) protected by the fluorine-based polymer film. Additionally, ETRI confirmed the chemical stability of the developed flexible neural electrode by verifying it did not corrode even when submerged in concentrated nitric acid at 70°C for over one hour.

The research team collaborated with Wonkwang University's Department of Basic Medicine, implanting the electrode in laboratory rat heads and inducing epilepsy with drugs to detect seizure signals and verify the performance of the neural electrode.

Professor Kim Min-seon of the School of Medicine at Wonkwang University also stated, "This electrode can be implanted in vivo to regulate brain and cardiac functions through continuous electrical stimulation of muscle and nerve cells. Furthermore, by attaching it to the scalp and dura mater for extended periods, it can measure and regulate brain activity and serve as a fundamental device for diagnosis and treatment of various brain diseases."

ETRI anticipates that this electrode will be widely applied to bioimplantable blood glucose sensors, wearable flexible sensors, neural prosthetic provision for limb-amputated patients, functional recovery for brain disease patients responding to aging, wearable sensors, and chemical sensors requiring durability in extreme environments.

In particular, the research team explained that due to excellent chemical durability, this technology will be effective for limb-amputated patients and artificial retina users who require continuous long-term electrode implantation in vivo.

Based on this technology, ETRI plans to focus on research and development including long-term in vivo stability and durability verification as well as process development for flexible cerebral cortex-implantable electrodes with hundreds of channels. Additionally, the institute stated it will verify medical efficacy through preclinical and clinical collaborative trials.

Furthermore, the research team explained that for brain-computer interface technology development, given that they have developed a highly sensitive electrode, the ultimate goal is to conduct electrical stimulation experiments on animals using the electrode, and then establish bidirectional communication between the neural network system through brain signal extraction.