Direct write of Dry electrodes on Healthcare Textiles

Author(s):  
Youssif Merhi ◽  
Shweta Agarwala
Keyword(s):  
1988 ◽  
Vol 49 (C4) ◽  
pp. C4-291-C4-294
Author(s):  
K. BARLOW
Keyword(s):  

2016 ◽  
Vol 136 (1) ◽  
pp. 18-23 ◽  
Author(s):  
Masahiro Inoue ◽  
Yasunori Tada ◽  
Yusaku Amano ◽  
Yosuke Itabashi ◽  
Tomonobu Sato ◽  
...  

2011 ◽  
Vol 26 (5) ◽  
pp. 495-498
Author(s):  
Kun-Peng CAI ◽  
Jing-Bo SUN ◽  
Bo LI ◽  
Ji ZHOU

Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1578
Author(s):  
Luisa Euler ◽  
Li Guo ◽  
Nils-Krister Persson

Textile electrodes, also called textrodes, for biosignal monitoring as well as electrostimulation are central for the emerging research field of smart textiles. However, so far, only the general suitability of textrodes for those areas was investigated, while the influencing parameters on the contact impedance related to the electrode construction and external factors remain rather unknown. Therefore, in this work, six different knitted electrodes, applied both wet and dry, were compared regarding the influence of specific knitting construction parameters on the three-electrode contact impedance measured on a human forearm. Additionally, the influence of applying pressure was investigated in a two-electrode setup using a water-based agar dummy. Further, simulation of an equivalent circuit was used for quantitative evaluation. Indications were found that the preferred electrode construction to achieve the lowest contact impedance includes a square shaped electrode, knitted with a high yarn density and, in the case of dry electrodes, an uneven surface topography consisting of loops, while in wet condition a smooth surface is favorable. Wet electrodes are showing a greatly reduced contact impedance and are therefore to be preferred over dry ones; however, opportunities are seen for improving the electrode performance of dry electrodes by applying pressure to the system, thereby avoiding disadvantages of wet electrodes with fluid administration, drying-out of the electrolyte, and discomfort arising from a “wet feeling”.


Micromachines ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 115
Author(s):  
Lukas Seewald ◽  
Robert Winkler ◽  
Gerald Kothleitner ◽  
Harald Plank

Additive, direct-write manufacturing via a focused electron beam has evolved into a reliable 3D nanoprinting technology in recent years. Aside from low demands on substrate materials and surface morphologies, this technology allows the fabrication of freestanding, 3D architectures with feature sizes down to the sub-20 nm range. While indispensably needed for some concepts (e.g., 3D nano-plasmonics), the final applications can also be limited due to low mechanical rigidity, and thermal- or electric conductivities. To optimize these properties, without changing the overall 3D architecture, a controlled method for tuning individual branch diameters is desirable. Following this motivation, here, we introduce on-purpose beam blurring for controlled upward scaling and study the behavior at different inclination angles. The study reveals a massive boost in growth efficiencies up to a factor of five and the strong delay of unwanted proximal growth. In doing so, this work expands the design flexibility of this technology.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Andrea Apicella ◽  
Pasquale Arpaia ◽  
Mirco Frosolone ◽  
Nicola Moccaldi

AbstractA method for EEG-based distraction detection during motor-rehabilitation tasks is proposed. A wireless cap guarantees very high wearability with dry electrodes and a low number of channels. Experimental validation is performed on a dataset from 17 volunteers. Different feature extractions from spatial, temporal, and frequency domain and classification strategies were evaluated. The performances of five supervised classifiers in discriminating between attention on pure movement and with distractors were compared. A k-Nearest Neighbors classifier achieved an accuracy of 92.8 ± 1.6%. In this last case, the feature extraction is based on a custom 12 pass-band Filter-Bank (FB) and the Common Spatial Pattern (CSP) algorithm. In particular, the mean Recall of classification (percentage of true positive in distraction detection) is higher than 92% and allows the therapist or an automated system to know when to stimulate the patient’s attention for enhancing the therapy effectiveness.


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