Active stylus‐touch discrimination scheme based on anomaly detection algorithm

Abstract

AbstractThis paper proposes an anomaly detection (AD) algorithm that can discriminate stylus‐touch based on capacitive touch screen panel. The digital value acquired from an analog‐to‐digital converter (ADC) are transferred to an autoencoder including an encoder and a decoder. While the encoder classifies only two classes of a no‐touch and a finger‐touch, the decoder reconstructs the similar sequence to the input one according to the encoder's decision. Because the touch sequences caused by the stylus are not trained, the large difference between input and output sequences is used to discriminate the stylus‐touch from finger‐touch and no‐touch. The proposed method is evaluated by means of an 8‐inch capacitive touch panel, an AD touch detection board, and a stylus board. At the sequence length of 16 touch samples, the measured bit error rate (BER) of less than 10−6 for each touch case is equivalent to the previous support vector machine (SVM) scheme whereas the number of multipliers is dramatically reduced to 16, compared with 400 of the previous SVM method.