Skin-interfaced medical devices are critically important for diagnosing disease, monitoring physiological health and establishing control interfaces with prosthetics, computer systems and wearable robotic devices. Skin-like epidermal electronic technologies can support these use cases in soft and ultrathin materials that conformally interface with the skin in a manner that is mechanically and thermally imperceptible. Nevertheless, schemes so far have limited the overall sizes of these devices to less than a few square centimetres. Here, we present materials, device structures, handling and mounting methods, and manufacturing approaches that enable epidermal electronic interfaces that are orders of magnitude larger than previously realized. As a proof-of-concept, we demonstrate devices for electrophysiological recordings that enable coverage of the full scalp and the full circumference of the forearm. Filamentary conductive architectures in open-network designs minimize radio frequency-induced eddy currents, forming the basis for structural and functional compatibility with magnetic resonance imaging. We demonstrate the use of the large-area interfaces for the multifunctional control of a transhumeral prosthesis by patients who have undergone targeted muscle-reinnervation surgery, in long-term electroencephalography, and in simultaneous electroencephalography and structural and functional magnetic resonance imaging.
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EEGLAB is freely available (http://www.sccn.ucsd.edu/eeglab/) under the GNU public license for non-commercial use and open source development, together with sample data, a user’s tutorial and extensive documentation. In-house MATLAB tools were adapted from the software tools developed at Duke University (https://wiki.biac.duke.edu/biac:tools) and are available on request.
The authors declare that all data supporting the findings of this study are available within the paper and its Supplementary Information.
The authors declare no competing interests
Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Device fabrication and development were carried out in part in the Frederick Seitz Materials Research Laboratory Central Research Facilities and Micro-Nano-Mechanical Systems Cleanroom, University of Illinois. L.T. acknowledges the support from Beckman Institute Postdoctoral Fellowship at UIUC. The materials and device engineering aspects of the research were supported by the Center for Bio-Integrated Electronics at Northwestern University. MRI experiments were performed at the Biomedical Imaging Center at the Beckman Institute, which also provided pilot hour support. K.J.Y. acknowledges the support from the National Research Foundation of Korea (grant nos NRF-2017R1C1B5017728 and NRF-2018M3A7B4071109) and the Yonsei University Future-leading Research Initiative (grant nos RMS2 2018-22-0028). Z.X. acknowledges the support from National Natural Science Foundation of China (grant no. 11402134). Y.H. acknowledges the support from NSF (grant nos 1400169, 1534120 and 1635443). J.W.L. gratefully acknowledges support from National Research Foundation of Korea (grant nos NRF-2017M3A7B4049466 and NRF-2018R1C1B5045721). M.M. acknowledges the support provided by Beckman Institute Predoctoral and Postdoctoral Fellowships. F.D. acknowledges the support provided by a Helen Corley Petit Scholarship in Liberal Arts and Sciences and an Emanuel Donchin Professorial Scholarship in Psychology from the University of Illinois. The authors would like to thank F. Lam for valuable discussions on electromagnetic simulations. We thank representatives of BrainVision LLC and Easycap GmbH for helpful conversations related to the equipment adaptations required for this project.
Supplementary figures, tables and references.
Signals obtained with the epidermal EMG array allow an amputee to control elbow, wrist and hand movements on the prosthesis.
Robustness of motion classification on vigorous tapping on the electrodes.
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Advanced Materials (2019)
Nature Biomedical Engineering (2019)
Nano Energy (2019)