A group of researchers at Georgia Tech have developed a nanomembrane electrode array that streamlines the process of electromyography (EMG) recording used in spinal cord compression treatment. The Bio-Interfaced Translational Nanoengineering Group, which develops smart bioelectronics for health and wellness, designed the electrode array to address limitations of standard EMG electrode systems. These systems, currently used in non-surgical electrostimulation therapy, have constraints that can affect treatment outcomes.

Electrostimulation therapy addresses mobility disorders caused by spinal nerve compression that arises due to arthritis, degenerative disc disease, disc herniation, or spinal injury. The treatment sends electrical pulses along nerve pathways to interrupt pain signals before they reach the brain. EMG recording monitors muscle activity along the spine during electrostimulation to monitor treatment effectiveness. 

Traditional systems use strong adhesives to attach large metal electrodes to the skin, requiring precise, time-consuming placement to ensure the reliability of data across treatments. Skin-irritating conductive gel provides signal transmission over multiple wires, resulting in discomfort for the patient, lengthy set-up times for clinicians, and increased chances of recording error.

The new EMG array is known as a large-area epidermal electronic system, or L-EES. It is made from a breathable, stretchable composite material. This nanomembrane consists of 16 electrodes suspended in rows of four within a biocompatible fabric. It has enhanced skin congruency to improve patient comfort and increase ease of placement. L-EES quickly covers large skin areas, reducing set-up times and potential for error. 

In a paper to be published in the journal Biosensors and Bioelectronics in October of 2020, the research group states that L-EES can record muscle activity with the same accuracy as conventional EMG systems. The paper also suggests that L-EES may improve the results of electrostimulation therapy by optimizing EMG electrode positioning and minimizing motion interference.