Properties of Touch Events

Gao, Shuo; Yan, Shuo; Zhao, Hang; Nathan, Arokia

doi:10.1007/978-3-030-68948-3_2

Cited by 1 publication

(1 citation statement)

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“…Compared with the static test, the accuracy has slightly decreased, the max error is 4 mm. As for normally operation area condition (e.g., smartphones, electronic watches and sports bracelet), considering the size of operation area and the width of human finger, [ 39 ] the precision of touch interactivities almost 7 mm (e.g., typing with a 26‐key keyboard in iPhone7plus, playing music in Apple Watch). Though the accuracy was decreased in the dynamic test, the accuracy is still can be acceptable.…”

Section: Experiments and Resultsmentioning

confidence: 99%

A Novel Touch Interface with Ultrahigh Optical Transmittance Based on Electrical Impedance Tomography for Interactive Displays

Gao

Sun

2021

Adv Materials Technologies

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silver nanowire (AgNW)-poly(3,4-ethylene dioxythiophene):poly (styrene sulfonate) (PEDOT:PSS) composite transparent flexible electrodes with 96% transmittance at 550 nm. [19] Nevertheless, current techniques for high transparency electrodes require cleanroom fabrication conditions, limiting their successful use in commercial products. Furthermore, some of them still blocks 10%-3% light intensity during the visible spectrum, [11,24] indicating the need for extra power consumption to maintain the display performance compared to their counterparts without touch panels installed, which shortens battery's lifetime for portable smart devices, giving rise to unpleasant user experience.In this work, to achieve ultrahigh transparency while maintaining low material cost and a simple fabrication process, an electrical impedance tomography (EIT)-based technique is presented.EIT is a low-cost and easy-to-implement detecting technology that allows real-time imaging. [25][26][27] In previous works, EIT techniques have been applied in diverse applications. In 2013, Cao and Xu applied Calderon's method to a chest-like sensing region and utilized a direct algorithm for image reconstruction. [28] They successfully reconstructed a male normal breath chest image with a 16-electrode system. In the same year, Tawil et al. proposed an impedance measurement-based artificial skin for robotics. The artificial skin was constructed using four different layers. The top layer was made of soft suede. The second layer was a highly conductive fabric. The third was a flexible carbon-loaded layer, with 19 chromium-plated brass eyelets electrodes located at its edge. The bottom layer was made of a 5 mm thick open-cell polyurethane foam. In their work, the LogitBoost algorithm was used to classify the modality of eight different touch events (tap, pat, push, stroke, scratch, slap, pull, and squeeze), the accuracy can reach 71%. [29] In 2015, Zhang et al. proposed a wearable armband sensor (Tomo [30] ), which used an eight evenly spaced copper electrodes based structure and the support vector machine (SVM) algorithm to recognize eleven hand gestures, achieving an accuracy of 96.6%. In 2018, Russo et al. [31] proposed a 16-electrode-based three-layered tactile sensor. The top is a piezoresistive fabric layer with high resistance. The second layer is a honeycomb mesh and the bottom layer is based on highly conductive fabric material. By employing a quadratic discriminant analysis (QDA), the position recognition error of this sensor ranges from 1 to 10 mm, depending on the contact locations.In traditional touch interfaces, electrodes will block the light intensity of the display, so extra power is required to maintain the display performance. In this article, an eight-electrode electrical impedance tomography system for touch location detection is proposed to improve the transmittance. The electrodes are settled at the edge of the touch panel and a machine learning algorithm is used to perform the regression process. This system can achieve almost 1 mm m...

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Section: Experiments and Resultsmentioning

confidence: 99%