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Dive into the research topics where Shuo Gao is active.

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Featured researches published by Shuo Gao.


IEEE\/OSA Journal of Display Technology | 2016

Reduction of Common Mode Noise and Global Multivalued Offset in Touch Screen Systems by Correlated Double Sampling

Shuo Gao; Jackson Lai; Charles Micou; Arokia Nathan

Touch-based interactivity has become an important function in displays. This paper reports on the signal processing of touch signals in which touch interactivity is processed as an image, and correlated double sampling (CDS) algorithm is applied for both common-mode noise reduction and global multivalued offset cancellation. Based on experimental results, we achieved a boost in SNR of 7.6 dB. The processed signal reduces detection errors and power consumption of the system.


ACS Applied Materials & Interfaces | 2017

Ultrathin Multifunctional Graphene-PVDF Layers for Multidimensional Touch Interactivity for Flexible Displays

Shuo Gao; Xingyi Wu; Hanbin Ma; J. Robertson; Arokia Nathan

This paper presents a flexible graphene/polyvinylidene difluoride (PVDF)/graphene sandwich for three-dimensional touch interactivity. Here, x-y plane touch is sensed using graphene capacitive elements, while force sensing in the z-direction is by a piezoelectric PVDF/graphene sandwich. By employing different frequency bands for the capacitive- and force-induced electrical signals, the two stimuli are detected simultaneously, achieving three-dimensional touch sensing. Static force sensing and elimination of propagated stress are achieved by augmenting the transient piezo output with the capacitive touch, thus overcoming the intrinsic inability of the piezoelectric material in detecting nontransient force signals and avoiding force touch mis-registration by propagated stress.


IEEE Access | 2016

Piezoelectric vs. Capacitive Based Force Sensing in Capacitive Touch Panels

Shuo Gao; Victor Arcos; Arokia Nathan

High sensitivity force sensing is a desirable function of capacitance touch screen panels. In this paper, we report on a dynamic force detection technique by utilizing piezoelectric materials. The force-voltage responsivities are investigated for four widely used stack-ups, with various panel thicknesses and touch locations. Based on the theoretical analysis and simulation results, the maximum responsivity and the signal-to-noise ratio are achieved at 0.42 V/N and 59.1 dB, respectively. The proposed technique implements force sensing successfully, enhancing the human-machine interactivity experience.


IEEE\/OSA Journal of Display Technology | 2016

Reduction of Noise Spikes in Touch Screen Systems by Low Pass Spatial Filtering

Shuo Gao; David McLean; Jackson Lai; Charles Micou; Arokia Nathan

This paper reports on a low-pass spatial filtering technique for reduction of noise spikes in capacitive touch screen panels. Filter bandwidth is adjusted by dynamically evaluating attenuation of signal and noise spikes. Based on the experimental results, we boost the signal-to-noise ratio by 15.6 dB and attenuate noise spikes by 19.25 dB. The processed signal yields higher detection accuracy and lower power consumption.


IEEE\/OSA Journal of Display Technology | 2016

Fast Readout and Low Power Consumption in Capacitive Touch Screen Panel by Downsampling

Shuo Gao; Jackson Lai; Arokia Nathan

This paper reports on downsampling-based techniques to achieve low power consumption and fast readout for capacitive touch screen panels. Here, touch interactivity is processed as an image, which is downsampled and reconstructed to estimate the touch position. After the reconstruction, a regional scan is performed around the reconstructed touch location to retrieve accurate touch information. Based on experimental and simulation results, we successfully decreased readout time and power consumption by 11.3 ms (68%) and 8.79 mW (68.7%), respectively, when only 25% sensors were selected. The presented technique yields higher responsivity and lower power consumption while maintaining detection accuracy.


SID Symposium Digest of Technical Papers | 2017

P-209: Augmenting Capacitive Touch with Piezoelectric Force Sensing

Shuo Gao; Arokia Nathan


Archive | 2017

Processing signals from a touchscreen panel

Arokia Nathan; Shuo Gao; Jackson Lai


SID Symposium Digest of Technical Papers | 2018

P-193: High Force Sensing Accuracy in Piezoelectric Based Interactive Displays by Artificial Neural Networks

Shuo Gao; Jifang Duan; Zhicheng Wei; Arokia Nathan


IEEE Journal of the Electron Devices Society | 2018

User-Oriented Piezoelectric Force Sensing and Artificial Neural Networks in Interactive Displays

Shuo Gao; Jifang Duan; Vasileios Kitsos; David R. Selviah; Arokia Nathan


Archive | 2017

Touchscreen panel signal processing

Arokia Nathan; Jackson Lai; Shuo Gao

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Jifang Duan

University College London

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David McLean

University of Cambridge

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Hanbin Ma

University of Cambridge

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J. Robertson

University of Cambridge

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