News Release

DGIST develops a smart adhesive electrode that avoids nerve damage!

Peer-Reviewed Publication

DGIST (Daegu Gyeongbuk Institute of Science and Technology)

□ DGIST (President Kunwoo Lee) has announced that a research team led by Professor Sohee Kim of the Department of Robotics and Mechatronics Engineering has developed an electrode capable of safely encasing nerves without causing damage. The newly developed electrode features soft actuation technology that allows it to transform from a flat two-dimensional shape into a three-dimensional structure. This breakthrough is expected to enable the emergence of various next-generation soft bioelectronic devices, including electroceuticals suitable for peripheral nerve treatment.

 

□ Neural electrodes are devices that measure the electrical signals traveling through nerves. Alternatively, they stimulate nerves by transmitting small electrical currents. These electrodes are used to assist patients with nerve damage in regaining movement. They can also stimulate specific nerves to alleviate pain. However, without adequate contact between the nerve and the electrode, accurately measuring neural signals and effectively delivering the intended stimulation become difficult.

 

□ Conventional cuff electrodes wrap around the nerve securely. However, because nerves are smooth, wire-like structures, cuff electrodes tend to slip or rotate. To prevent this, the electrodes must be tightly fastened, which can compress the nerve, reducing blood flow and potentially causing nerve damage.

 

□ Due to these challenges, traditional methods struggle to securely encircle and affix on nerves. Consequently, in the absence of excessive compression, there is no way to maintain contact with the electrode. This impediment necessitated a new approach to ensure that electrodes would adhere stably without damaging the nerve.

 

□ To address these challenges, the research team developed a soft-actuated cuff electrode that allows the electrode to bend autonomously and wrap around the nerve. The novel electrode softly conforms to the nerve, allowing it to be securely fixed without the need for sutures. Unlike conventional electrodes, this design maintains firm adhesion without requiring excessive tightening around nerves, which makes it safer for long-term use. Noteworthily, the research team incorporated a three-dimensional convex structure that reduces the direct contact area with the nerve while enhancing adhesion, thereby enabling clearer neural signal detection without the risk of nerve damage.

 

□ The research team conducted long-term experiments to test the performance of this electrode when used on peripheral nerves and confirmed that it allows accurate neural signal measurement without causing damage. Furthermore, the electrode can selectively stimulate targeted nerves. Additionally, the three-dimensional structure plays a key role in ensuring strong adhesion while minimizing pressure, thereby preventing any harm to the nerve tissue or its function.

 

□ Professor Sohee Kim stated, “This study introduces a new concept of cuff-shaped electrodes that wrap around nerves, including peripheral and vagus nerves. With its ability to provide high-quality neural signal monitoring over the long term and enable minimal-current stimulation, this technology is expected to be widely utilized in various bioelectronic devices, such as implantable electroceuticals.”

 

□ Professor Sohee Kim is the corresponding author of the article reporting the results of this study, and Dr. Hyunmin Moon, a postdoctoral researcher at the Massachusetts Institute of Technology, is the first author. Additional contributions were made by Namsun Chou, a senior researcher at  the Korea Brain Research Institute, and Professor Ki-Su Park of the Department of Neurosurgery at Kyungpook National University Hospital. Their research findings have been published as a back cover article, titled “ABC,” in the prestigious international journal Advanced Materials.

 

- Corresponding Author E-mail Address : soheekim@dgist.ac.kr

 


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