A Smart Pen Based on Triboelectric Effects for Handwriting Pattern Tracking and Biometric Identification

Abstract

The rapid development of artificial intelligence places high demands on human–machine interfaces. Various types of huma–machine interfaces have been implemented, including smart keyboards, electronic skins, and wearable motion sensors. Handwriting behavior has a high degree of interaction freedom, and handwriting characteristics offer high-security standards for human–machine systems. Herein, we propose a portable smart pen integrated with triboelectric displacement vector sensors to trace handwriting trajectories for human–machine interactions and biometric identification. A triboelectric pressure sensor array is evenly distributed along the pen case to sense displacement vectors, and an additional triboelectric sensor is placed on top of the pen to detect vertical force. By leveraging the resin pen refill as a tribopositive material and a nanowired polyethylene tribonegative layer attached to a Cu electrode, triboelectric signals are generated during the writing/moving process. The calculation and analysis of the sensor signals enable the recognition of handwritten patterns, including Latin letters and Arabic numerals. Moreover, the smart pen can be used to authenticate users based on their unique handwriting patterns, which can help take human–machine interfaces and cyber security to the next level. Furthermore, a custom smart pen operation mode that enables the control of a slide presentation demonstrates the smart pen’s potential for various human–machine interface applications.

A Triboelectric Sensor with Double Bubble Structure Applied in a High Security Double Lock System

“…There are four labels (deep, fast, normal, and holding) in a respiratory signal data set (described in Note S1), corresponding to four different breathing modes. Machine and deep learning algorithms have already been used to process the data collected by TENGs for classification, such as movements and gestures. , Here, we investigated four classification models on breathing patterns recognition, including Decision Tree (DT), Random Forest (RF), Multilayer Perceptron (MLP), and Long Short-Term Memory (LSTM), respectively. The related principles are described in Note S2.…”

Highly Sensitive Fabric Sensors Based on Scale-like Wool Fiber for Multifunctional Health Monitoring

“…23−25 Among them, fabric sensors are considered to be the most competitive candidates because of their prominent advantages of natural interwoven structure, superior portability, wearing softness, and comfort. Generally, most pressure/strain fabric sensors have been designed mainly based on the mechanisms of piezoelectric, 26−28 capacitive, 29,30 triboelectric, 31,32 and piezoresistive sensing. 33−35 Among these sensing types, piezoresistive fabric sensors draw tremendous attention due to their simple fabrication process, convenient signal acquisition, and easy signal processing.…”

“…To date, several common types of flexible electronics are recognized, i.e., thin film, − hydrogel, , paper, − and fabric. − Among them, fabric sensors are considered to be the most competitive candidates because of their prominent advantages of natural interwoven structure, superior portability, wearing softness, and comfort. Generally, most pressure/strain fabric sensors have been designed mainly based on the mechanisms of piezoelectric, − capacitive, , triboelectric, , and piezoresistive sensing. − Among these sensing types, piezoresistive fabric sensors draw tremendous attention due to their simple fabrication process, convenient signal acquisition, and easy signal processing. Especially, functional fabrics constructed through integrating conductive active fillers including zero-dimensional (0D) metal nanoparticles, , one-dimensional (1D) nanowires/nanotubes, − and two-dimensional (2D) nanosheets − with soft insulating fabric are expected to be attractive alternatives for pressure/strain fabric sensors.…”

An Intelligent Glove of Synergistically Enhanced ZnO/PAN-Based Piezoelectric Sensors for Diversified Human–Machine Interaction Applications

“…With the booming Internet of Things (IoT) industry, human-machine interaction (HMI) is gaining widespread attention as human and machines become more closely connected [1][2][3][4][5]. Traditional HMI devices (joysticks, remote controls, keyboards, etc.)…”