3D Printed Electrodes For Pediatric Autoimmune Disease Diagnosis

• Noah Durbin, Computer Engineering, University of Delaware

• Nathan Lazarus, Electrical and Computer Engineering, University of Delaware

Electrocardiography(ECG), Electromyography(EMG), and Electroencephalography(EEG) measure different bodily functions and activity through the use of electrodes to measure activity in muscles, the heart, and the brain. Pediatric care is a scene that gets much less attention for developing medical devices. For this project, childhood autoimmune disorders such as Juvenile Myositis(JM) are the target, the ability to monitor muscle strength and electrical signals is crucial to help with diagnosis and treatment. JM affects 22,000 children every year and causes weakness and inflammation in the muscles. Currently, there is a poor state of pediatric medical devices, strain testing and conventional EMG measurements are poorly suited for long-term use due to a variety of factors. EMG and strain testing is difficult due to how children’s body shape changes as they develop, as well as current EMG electrodes drying out rapidly over time. In this project, it is shown that it is possible to create customizable 3D-printed devices that can monitor muscle electrical signals through EMG and strain sensing. Here two separate tests were conducted that established a foundation for future work. 3D printed dry electrodes using Multi3D Electrifi, a copper-based filament was used to create electrodes that have relatively close contact impedance to Ag/AgCl electrodes of 50 to 75 Ohms. Multiple designs of these electrodes were tested with the best-performing one having only a few ohms more contact impedance than the industry standard. Strain testing using a combination of Electrifi and Ninjatek Chinchilla showed changes in resistance from 5 to 15kOhms as the sample stretched and unstretched. The advantages of 3D printing open many possibilities in pediatric care, to be able to fully customize devices to fit any patient while also being potentially viable options in monitoring signals over longer periods of time.