(J-375) Drawn-on-Skin Bioelectronics for Customizable and Reconfigurable High-Density Surface Electromyography

Introduction:
Electromyogram (EMG) mapping is a valuable technique that helps clinicians and scientists understand muscle health in different medical fields, from sports physiology to prosthetic control and rehabilitation research. However, accurately matching an individual's unique muscle anatomy with conventional tools (multielectrode arrays or MEAs) is technically challenging. The fixed construction of the MEAs makes it nearly impossible to match the muscle anatomy, resulting in missing relevant muscle activity, highly redundant data, complicated electrode placement optimization, and inaccuracies in classification algorithms. We developed drawn-on-skin (DoS) MEAs to address this issue. The DoS electrodes can be customized and reconfigured in situ to match each person's unique muscle anatomy.




Materials and Methods:
The high-density DoS MEAs were fabricated using a biocompatible conductive ink based on an Ag/poly(3,4-ethylenedioxythiophene)-poly(styrenesulfonate) (Ag-PEDOT:PSS) composite, water/acrylic emulsion-based insulator, ball pens, and stencils. The electrical performance and signal quality of the DoS MEAs was characterized and compared with other types of wearable bioelectronics/conventional grids. To evaluate the high-density recording capabilities of DoS MEAs, motor unit action potentials (MUAPs) were identified, their propagation was observed, and innervation zones were localized. The performance of the DoS MEAs in the presence of large muscle deformation was also compared with that of the conventional technology. DoS MEAs were rearranged relative to a fixed commercial grid during different hand gestures to reveal the missed information from the grid. Lastly, the gesture classification performance from EMG data obtained with customized DoS MEAs (compared with the commercial grid) was evaluated.




Results, Conclusions, and Discussions:
The DoS MEAs show uniform electrical properties and can map EMG activity with high fidelity under skin deformation-induced motion, stemming from the unique and robust skin-electrode interface. Like the commercial grids, the DoS MEAs could capture MUAPs, their propagation across the wrist flexor muscles, and an innervation band across the muscle group. Unlike the commercial grids, the DoS MEAs could capture EMG with consistent quality (with a high signal-to-noise ratio) despite large muscle movements during a seated exercise.


A significant advantage of DoS MEAs is that they can be reconfigured to match and extend the coverage of various muscles, enabling accurate localization of muscle activity and preventing missed information. DoS MEAs rearranged on the wrist flexors better reveal the center of muscle activity missed by the commercial grid during multiple hand gestures performed by human subjects. The DoS MEAs also produce highly informative data (as evidenced by principal component analysis) when customized to the specific anatomy of subjects, leading to accurate finger gesture detection compared with conventional technology. A human subject was able to control a robotic hand to perform various gestures while wearing the customized DoS MEA. As a large-area, tunable-density electrophysiological mapping technology, DoS MEAs could enable truly personalized monitoring and therapy.