Multifunctional electronic textiles (e-textiles) incorporating miniaturized electronic devices will pave the way toward a new generation of wearable devices and human-machine interfaces. Unfortunately, the development of e-textiles is subject to critical challenges, such as battery dependence, breathability, satisfactory washability, and compatibility with mass production techniques. This work describes a simple and cost-effective method to transform conventional garments and textiles into waterproof, breathable, and antibacterial e-textiles for self-powered human-machine interfacing. Combining embroidery with the spray-based deposition of fluoroalkylated organosilanes and highly networked nanoflakes, omniphobic triboelectric nanogenerators (R F -TENGs) can be incorporated into any fiber-based textile to power wearable devices using energy harvested from human motion. R F -TENGs are thin, flexible, breathable (air permeability 90.5 mm s −1 ), inexpensive to fabricate (<0.04$ cm −2 ), and capable of producing a high power density (600 µW cm −2 ). E-textiles based on R F -TENGs repel water, stains, and bacterial growth, and show excellent stability under mechanical deformations and remarkable washing durability under standard machine-washing tests. Moreover, e-textiles based on R F -TENGs are compatible with large-scale production processes and exhibit high sensitivity to touch, enabling the cost-effective manufacturing of wearable human-machine interfaces.

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In article number 1904350, Ramses V. Martinez and co‐workers fabricate omniphobic triboelectric nanogenerators (RF‐TENGs) by combining embroidery with spray‐based deposition of fluoroalkylated organosilanes and highly networked nanoflakes, which enable the simple and cost‐effective transformation of any conventional textiles into waterproof, breathable, and antibacterial e‐textiles for self‐powered human–machine interfacing. E‐textiles based on RF‐TENGs are compatible with large‐scale production processes and exhibit high sensitivity to touch.

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The choice of best gestures and commands for touchless interfaces is a critical step that determines the user- satisfaction and overall efficiency of surgeon computer interaction. In this regard, usability metrics such as task completion time, error rate, and memorability have a long-standing as potential entities in determining the best gesture vocabulary. In addition, some previous works concerned with this problem have utilized qualitative measures to identify the best gesture. In this work, we hypothesize that there is a correlation between the qualitative properties of gestures (v) and their usability metrics (u). Therefore, we conducted an experiment with linguists to quantify the properties of the gestures. Next, a user study was conducted with surgeons, and the usability metrics were measured. Lastly, linear and non-linear regression techniques were used to find the correlations between u and v. Results show that usability metrics are correlated with the gestures’ qualitative properties ( R2 = 0.4).