Neural Network-Enabled Flexible Pressure and Temperature Sensor with Honeycomb-like Architecture for Voice Recognition.

Yue Su,Xu Zhang,Kainan Ma,Ming Liu

doi:10.3390/s22030759

Yue Su, Xu Zhang + Show 2 more

Open Access

https://doi.org/10.3390/s22030759

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Abstract

Flexible pressure sensors have been studied as wearable voice-recognition devices to be utilized in human-machine interaction. However, the development of highly sensitive, skin-attachable, and comfortable sensing devices to achieve clear voice detection remains a considerable challenge. Herein, we present a wearable and flexible pressure and temperature sensor with a sensitive response to vibration, which can accurately recognize the human voice by combing with the artificial neural network. The device consists of a polyethylene terephthalate (PET) printed with a silver electrode, a filament-microstructured polydimethylsiloxane (PDMS) film embedded with single-walled carbon nanotubes and a polyimide (PI) film sputtered with a patterned Ti/Pt thermistor strip. The developed pressure sensor exhibited a pressure sensitivity of 0.398 kPa in the low-pressure regime, and the fabricated temperature sensor shows a desirable temperature coefficient of resistance of 0.13% C in the range of 25 C to 105 C. Through training and testing the neural network model with the waveform data of the sensor obtained from human pronunciation, the vocal fold vibrations of different words can be successfully recognized, and the total recognition accuracy rate can reach 93.4%. Our results suggest that the fabricated sensor has substantial potential for application in the human-computer interface fields, such as voice control, vocal healthcare monitoring, and voice authentication.

Highlights

The human voice, as the main medium of communication with the outside world, plays a significant role in various aspects such as telecommunication, human-machine interaction, and the Internet of Things [1]
We demonstrate a flexible wearable pressure and temperature sensor to achieve accurate human voice detection, which is composed of the patterned Ti/Pt thermistor strip by magnetron sputtering, high-conductivity Ag thin-film electrodes, and honeycomb-like microarchitecture polydimethylsiloxane (PDMS) elastomers embedded with electrically conductive SWNTs
A wearable, flexible and neural network-enabled pressure and temperature sensor has been developed by integrating a polyethylene terephthalate (PET) film printed with the silver electrode, a filament-microstructured PDMS film embedded with single-walled carbon nanotubes, and a PI film sputtered with patterned Ti/Pt thermistor strip

Summary

Introduction

The human voice, as the main medium of communication with the outside world, plays a significant role in various aspects such as telecommunication, human-machine interaction, and the Internet of Things [1]. Conventional rigid microphones have been developed for accurately detecting human voice, but their applications are limited in noisy or windy environments. The flexible wearable pressure sensors that can provide electrical feedback in response to external pressure stimuli have been used for monitoring human voices [2,3,4,5,6,7,8,9,10,11,12]. By measuring vibrations in users’ neck skin and converting them into readable signals, these sensors have advantages of clear voice detection and antiinterference. Great achievements have been made in the fabrication of piezoresistive-type sensors, such as skin-conformity and technology compatibility, achieving high sensitivity in a wide measuring range remains a subject worthy of intense study

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