Bo Wen;Qian Wang;Bin Tian;Panwang Guo;Ziyi Gong;Ke Zheng;Jing Liang;Wei Wu
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All-Printed Flexible Multidirectional Strain Sensor With Dual-Mode Response for Human Motion Detection
The flexible multidirectional strain sensors that can distinguish different strain directions and magnitudes have attracted increasing attention. However, the previous designs of multidirectional strain sensors usually use the same type of sensing signals, which makes it difficult to decouple the response signals and hinders the simple distinction of strain directions. Herein, we propose a dual-mode response printed flexible multidirectional strain sensor (DRPMS) that uses resistance and capacitance signals to represent strains in the two principal planar directions, eliminating the requirement of conventional signal decoupling. With the assistance of machine learning algorithms, it can accurately distinguish the directions of strain with an accuracy rate of 98.3% and can detect different driving postures and wrist motions. The results demonstrate broad application potential in distracted driving behavior detection and human motion monitoring.
期刊介绍:
The fields of interest of the IEEE Sensors Journal are the theory, design , fabrication, manufacturing and applications of devices for sensing and transducing physical, chemical and biological phenomena, with emphasis on the electronics and physics aspect of sensors and integrated sensors-actuators. IEEE Sensors Journal deals with the following:
-Sensor Phenomenology, Modelling, and Evaluation
-Sensor Materials, Processing, and Fabrication
-Chemical and Gas Sensors
-Microfluidics and Biosensors
-Optical Sensors
-Physical Sensors: Temperature, Mechanical, Magnetic, and others
-Acoustic and Ultrasonic Sensors
-Sensor Packaging
-Sensor Networks
-Sensor Applications
-Sensor Systems: Signals, Processing, and Interfaces
-Actuators and Sensor Power Systems
-Sensor Signal Processing for high precision and stability (amplification, filtering, linearization, modulation/demodulation) and under harsh conditions (EMC, radiation, humidity, temperature); energy consumption/harvesting
-Sensor Data Processing (soft computing with sensor data, e.g., pattern recognition, machine learning, evolutionary computation; sensor data fusion, processing of wave e.g., electromagnetic and acoustic; and non-wave, e.g., chemical, gravity, particle, thermal, radiative and non-radiative sensor data, detection, estimation and classification based on sensor data)
-Sensors in Industrial Practice