Inkjet-printed fully customizable and low-cost electrodes matrix for gesture recognition

Printed Nanomaterials for All-in-One Integrated Flexible Wearables and Bioelectronics

Recent advancements in printing technologies allow for fabricating various wearable sensors, circuits, and integrated electronics. However, most printing tools have limited ranges of handling ink viscosity, a short working distance, and a limited feature size for developing sophisticated electronics. Here, this paper introduces an all-in-one integrated wearable electronic system via multilayer, multinanomaterial printing. Versatile, high-resolution aerosol-jet printing could successfully print Cu nanoparticles, Ag nanoparticles, PEDOT:PSS, and polyimide (PI) to manufacture nanomembrane composite structures, including skin-contact electrodes and wireless circuits. The printed polymer, PEDOT:PSS deposited on the Cu, ensures biocompatibility when making direct skin contact while enhancing electrical conductivity for electrodes. A self-assembled monolayer facilitates better adhesion of Cu nanoparticles on the PI. Also, using intensive pulsed light, a photonic sintering method minimizes Cu-oxidation while avoiding thermal damage. The combined experimental and computational study shows the mechanical flexibility and reliability of the printed integrated device. With human subjects, the flexible wireless bioelectronic system demonstrates superior performance in detecting high-fidelity physiological signals on the skin, including electromyograms, electrooculograms, electrocardiograms, and motions, proving its potential applications in portable human healthcare and persistent human-machine interfaces.

The Role of Interdigitated Electrodes in Printed and Flexible Electronics

Flexible electronics, also referred to as printable electronics, represent an interesting technology for implementing electronic circuits via depositing electronic devices onto flexible substrates, boosting their possible applications. Among all flexible electronics, interdigitated electrodes (IDEs) are currently being used for different sensor applications since they offer significant benefits beyond their functionality as capacitors, like the generation of high output voltage, fewer fabrication steps, convenience of application of sensitive coatings, material imaging capability and a potential of spectroscopy measurements via electrical excitation frequency variation. This review examines the role of IDEs in printed and flexible electronics since they are progressively being incorporated into a myriad of applications, envisaging that the growth pattern will continue in the next generations of flexible circuits to come.

Fully Screen-Printed PI/PEG Blends Enabled Patternable Electrodes for Scalable Manufacturing of Skin-Conformal, Stretchable, Wearable Electronics

Recent advances in soft materials and nano-microfabrication have enabled the development of flexible wearable electronics. At the same time, printing technologies have been demonstrated to be efficient and compatible with polymeric materials for manufacturing wearable electronics. However, wearable device manufacturing still counts on a costly, complex, multistep, and error-prone cleanroom process. Here, we present fully screen-printable, skin-conformal electrodes for low-cost and scalable manufacturing of wearable electronics. The screen printing of the polyimide (PI) layer enables facile, low-cost, scalable, high-throughput manufacturing. PI mixed with poly(ethylene glycol) exhibits a shear-thinning behavior, significantly improving the printability of PI. The premixed Ag/AgCl ink is then used for conductive layer printing. The serpentine pattern of the screen-printed electrode accommodates natural deformation under stretching (30%) and bending conditions (180°), which are verified by computational and experimental studies. Real-time wireless electrocardiogram monitoring is also successfully demonstrated using the printed electrodes with a flexible printed circuit. The algorithm developed in this study can calculate accurate heart rates, respiratory rates, and heart rate variability metrics for arrhythmia detection.

Feature stability and setup minimization for EEG-EMG-enabled monitoring systems

Delivering health care at home emerged as a key advancement to reduce healthcare costs and infection risks, as during the SARS-Cov2 pandemic. In particular, in motor training applications, wearable and portable devices can be employed for movement recognition and monitoring of the associated brain signals. This is one of the contexts where it is essential to minimize the monitoring setup and the amount of data to collect, process, and share. In this paper, we address this challenge for a monitoring system that includes high-dimensional EEG and EMG data for the classification of a specific type of hand movement. We fuse EEG and EMG into the magnitude squared coherence (MSC) signal, from which we extracted features using different algorithms (one from the authors) to solve binary classification problems. Finally, we propose a mapping-and-aggregation strategy to increase the interpretability of the machine learning results. The proposed approach provides very low mis-classification errors ( < 0.1 ), with very few and stable MSC features ( < 10 % of the initial set of available features). Furthermore, we identified a common pattern across algorithms and classification problems, i.e., the activation of the centro-parietal brain areas and arm's muscles in 8-80 Hz frequency band, in line with previous literature. Thus, this study represents a step forward to the minimization of a reliable EEG-EMG setup to enable gesture recognition.