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Sensitivity-Enhanced Wearable Active Voiceprint Sensor Based on Cellular Polypropylene Piezoelectret Wenbo Li, Sheng Zhao, Nan Wu, Junwen Zhong, Bo Wang, Shizhe Lin, Shuwen Chen, Fang Yuan, Hulin Jiang, Yongjun Xiao, Bin Hu, and Jun Zhou ACS Appl. Mater. Interfaces, Just Accepted Manuscript • Publication Date (Web): 14 Jun 2017 Downloaded from http://pubs.acs.org on June 14, 2017

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ACS Applied Materials & Interfaces

Sensitivity-Enhanced Voiceprint

Wearable

Sensor

Based

on

Active Cellular

Polypropylene Piezoelectret Wenbo Li‡, Sheng Zhao‡, Nan Wu, Junwen Zhong, Bo Wang, Shizhe Lin, Shuwen Chen, Fang Yuan, Hulin Jiang, Yongjun Xiao, Bin Hu and Jun Zhou* Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, 430074, China KEYWORDS: Piezoelectret, voiceprint, active sensor, wearable electronics, self-powered

ABSTRACT: Wearable active sensors have extensive applications in mobile biosensing and human-machine interaction but require good flexibility, high sensitivity, excellent stability and self-powered feature. In this work, cellular polypropylene (PP) piezoelectret was chosen as the core material of a sensitivity-enhanced wearable active voiceprint sensor (SWAVS) to realize voiceprint recognition. By virtue of dipole orientation control method, the air layers in piezoelectret were efficiently utilized and the current sensitivity was enhanced (from 1.98 pA/Hz to 5.81 pA/Hz at 115 dB). The SWAVS exhibited the superiorities of high sensitivity, accurate frequency response and excellent stability. The voiceprint recognition system could make correct reactions to human voices by judging both of the password and speaker. This study presented a voiceprint sensor with potential applications in non-contact biometric recognition and safety guarantee systems, promoting the progress of wearable sensor networks.

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INTRODUCTION Owing to the urgent demands for evaluation, adjustment and extension of human’s somatic functions, wearable active sensors show an extensive market prospect in mobile biosensing and human-machine interaction.1-11 Recently, researchers have contributed promising achievements in wearable sensing field to detect real-time physiological status and capture the meaningful features, such as body temperature monitoring in assessments of physical status;12, 13

arterial pulse measurement and blood pressure determination in prognosis of sickness;14, 15

human motion detecting and recording in sports training and healthy recovery;16-18 multi-point tactile sensing in imitation of human organ functions.19, 20 In addition, the detection of human voice which contains rich information and valuable individual features is vitally important in mobile bio-sensing and non-contact system control. Traditional commercial microphones own high sensitivity and excellent electro-acoustic responses.21-23 However, the indispensable external power source and solid-state structure will cause inconvenience and uncomfortableness to the users, which always confine their applications in wearable electronics.24 In contrast, flexible and self-powered acoustic sensors based on piezoelectric and triboelectric materials 25-34 have outstanding performance in fitting human body and working sustainably, but suffer from deficiencies such as low piezoelectric modulus (PVDF: ~20 pC/N) and high Young's modulus (PVDF: 102~103 MPa, PZT: 104~105 MPa),25-30 or the two-layer separated structure.31, 32 Besides, as a porous thin-film material, cellular polypropylene (PP) piezoelectret with high piezoelectric modulus (102~103 pC/N), low Young's modulus (0.1~1 MPa) and especially low acoustic impedance (2 MPa·s/m) is particularly appropriate for voice sensing.33-34 Herein, we introduce a new type of sensitivity-enhanced wearable active voiceprint sensor (SWAVS) based on cellular PP piezoelectret. Previous literatures utilize the stacking method to promote the voltage sensitivity of cellular PP.35 But current signal, in comparison to voltage, is more suitable to characterize the variation of the voice signal, which is more 2 ACS Paragon Plus Environment

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sensitive in detecting the voiceprint of human speaking. Through the dipole orientation control method, the current sensitivity of the SWAVS is enhanced from 1.98 pA/Hz to 5.81 pA/Hz at 115dB. The current output reaches 2.79 µA/m2 under stimulating sound frequency and intensity of 800 Hz and 115 dB, respectively. In addition, our SWAVS exhibits accurate frequency response and excellent stability. In response to human voice, our SWAVS shows high signal to noise ratio (up to 20) and high energy ratio (up to 10), demonstrating its unique advantage in human voice sensing. Moreover, a voiceprint recognition system based on the SWAVS could simultaneously identify the password and recognize the speaker, indicating the potential applications in non-contact biometric recognition and safety guarantee systems. RESULTS AND DISCUSSION Fabrication of a SWAVS. The fabrication of a SWAVS began with the low-cost and light-weight cellular PP piezoelectret film, which was expanded via thermal expansion technique and polarized with corona charging method.14 As illustrated in Figure 1a, three pretreated cellular PP films were laminated together, as well as the top and bottom textile-based electrodes. The detailed fabrication process was given in Figure S1. The digital picture of the device demonstrated its excellent flexibility (Figure 1b). The cross-section view scanning electron microscope (SEM) image exhibited the final laminated components of the device in Figure 1c, showing the multi-layer structure and the textile electrodes clearly. The Young’s module (Figure S2a) and tensile strength (Figure S2b) measurements showed the mechanical property of the device. The bottom and middle PP layers were covered with silver (Ag) on one side by magnetron sputtering as the inner electrodes. The two external electrodes were both fabricated on a piece of nylon cloth covered with Ag. The Energy Dispersed X-ray (EDX) spectrum of the electrode (Figure S2c) demonstrated the Ag@nylon structure. The electrode was repeatedly bent and released (as illustrated in Figure S3) for 10,000 times and the I-V curves remained almost the same (Figure S2d). The insert SEM 3 ACS Paragon Plus Environment


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image (Figure S2d) indicated that no noticeable surface morphology degradation was proved after the test. Working mechanism for a SWAVS. The cellular PP piezoelectret contains abundant air bubbles inside, which endow the material with the piezoelectric-like property.35 However, previous theoretical studies reveal that the abundant air bubbles are mostly wasted and the corresponding formula about output current is derived:36

ε d ε g de de I (t ) = Q0 ( g e + 1) − Q0 ε r d air_0 RS ε 0ε r RS ε 0ε r d air_0

1

d

t

 d e d air (t )  − RSε 0 [ ε re t + ∫0  + e ε g   ε r 1

ε d d d d (t ) − RS ε −Q0 ( g e + 1) 2 2 e 2 [ e + air ]e R S ε0 εr εr ε r d air_0 εg

[ 0

de

εr

t+

t

∫0

dair ( m )

εg

dm ]

t

∫e

d air ( m )

εg

1 de [ m+ RS ε 0 ε r

dm ]

md

∫0

air

( x)

εg

(1) dx ]

0

dm

where I(t) is the real-time output current, which changes with the compressed deformation dair(t). The other parameters are all constants related to the specific device: R is the external load, S is the device area, Q0 is the original charge on the electrodes, ε0 is the vacuum permittivity, εr is the relative permittivity of the electret, εg is the relative permittivity of the gas, de is the thickness of the electret and dair_0 is the original thickness of the gas gap. In the theoretical model, the air bubbles are simplified to the air gaps layer by layer and the total number of the layers is defined as n. However, according to Equation (1), the output current is independent of the layer number n, which means one layer of air is equivalent to n layer of air, indicating the redundant air layers are useless for the outputs. Above results were also verified by finite element simulation in Figure S4, using the COMSOL Multiphysics simulation software. Two models were established in the simulation, respectively: a single-air-layer piezoelectret model (Figure S4a) and a multi-layer model laminated by three pieces of same piezoelectrets (Figure S4b). All the piezoelectret layers were polarized at the same orientation and reacted to the same stimulation. The simulation results (Figure S4d and e) exhibited that the current outputs of the one-layer-model and the three-layer-model were exactly the same. 4 ACS Paragon Plus Environment

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Herein, to avoid the waste of air layers and promote the outputs of laminated devices, a novel dipole orientation control method to fabricate the laminated piezoelectret device is proposed. Based on the condition that the three air layers in the original laminated device (Type I) are polarized in the same orientation, the middle air layer is reversely polarized in the SWAVS (Type II). The working mechanism of two type devices are both based on electrostatic induction. Figure 2a illustrates the working period of the Type II device and the similar working mechanism diagram of original Type I device is given in Figure S5. Specifically, COMSOL Multiphysics simulation software is used to simulate the potential distribution in the devices. As shown in Figure 2a-I, the six inner boundaries of air and PP are charged after corona polarization. Because of the reverse polarization in the middle air layer, the surfaces (s1, s4, s5) hold the positive charges and the corresponding potential is positive (red parts), while the surfaces (s2, s3, s6) hold the negative charges and the corresponding potential is negative (blue parts). When external force is applied to the device, the air bubbles are compressed but the captured charges remain unchanged. As a result, the dipole moments in the air components will reduce. Simultaneously, the reduction of the potential and electric field in electret components are observed (Figure 2a-II), leading to the loss of charges on the electrodes and the generation of the instantaneous negative current signal in the circuit. After the ultimate compression (Figure 2a-III), the device will recover to original state because of its intrinsic elasticity. It is a reverse process of the compressing process, the increase of potential and electric field is observed (Figure 2a-IV) and an instantaneous positive current signal flowing back is generated. As shown in Figure 2b, the difference between two type devices is the dipole arrangements, which is actually the main cause of current promotion. The equivalent circuit models of the two type devices are showed in Figure 2c. In the whole working period, the three layers can all be regarded as current sources. The three current sources in Type I are in series and the current output is limited by the lowest one: iI = min(i1+i2+i3). However, the 5 ACS Paragon Plus Environment


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Type II device is a three-layer parallel model and the output current is the sum of the three current sources (iII = i1+i2+i3), which is more effective than Type I. The conclusion is also verified by the finite element simulation. It can be seen in Figure S4c that the polarization of the middle layer in the three-air-layer model is set to be the opposite orientation, compared with the case in Figure S4b. The simulation results (Figure S4e and f) exhibit that the output current of Type II is almost three times to type I (Figure 2d). Furthermore, experimental evidence is given in Figure 2e. First of all, to understand the influence of the polarization orientation in single cellular PP piezoelectret film clearly, each 6 single-layer devices were fabricated with negative and positive polarization method. The peak currents of the negative and positive polarized devices are showed in Figure S6, illustrating the repeatability and uniformity of the two polarization method. In contrast experiment, two of three-layer laminated devices were fabricated only with the difference in the polarization orientation of the middle layer, just as the simulation models in Figure S4b and c. They were both tested using the single-frequency voice from 200 Hz to 800 Hz under the sound pressure level (SPL) of 115 dB. The experimental results exhibit an obvious promotion of Type II device in output current from 1.43 to 4.46 nA (about 0.89 to 2.79 µA/m2) at 800 Hz. The current ratio is almost three times (Figure 2e), which matches the simulation results very well. In Figure 2e, the relationship between peak current and frequency is linear and the slope can be regarded as the sensitivity. The frequency sensitivity (at 115 dB) of Type II device is 5.81 pA/Hz which has been enhanced by 3 times than Type I device (1.98 pA/Hz). It has been proved in above three aspects (circuit theory, finite element simulations and experimental facts) that the SWAVS (Type II) owns larger output current than the original device (Type I) under the same voice stimulation. The dipole orientation control method can effectively enhance the sensitivity of the acoustic sensor. Single-frequency acoustic response of a SWAVS. To assess the sensing performance of the SWAVS in various acoustic environments, a series of systematical experiments were carried 6 ACS Paragon Plus Environment

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out. The current responses to different SPL were measured at the frequency of 800 Hz. As indicated in Figure 3a, the current outputs exponentially increase with SPL. It can be explained by the definition of SPL, which is given as follows: SPL = 20 log

(2)

where SP is the actual sound pressure and SPref is the reference sound pressure (usually a constant: 20 µPa). The sound pressure is the applied force on the device, which is linear to the current outputs according to the working mechanism of piezoelectret generators. Therefore, SPL would certainly have an exponential relationship with the current outputs. It is further investigated in Figure 3b about the dependence of peak current response on the incident SPL. Exactly as discussed in the previous section, a linear relationship of log Ipeak and SPL is experimentally observed at all the frequencies, respectively. Meanwhile, the linear coefficients at different frequencies are all the same, meaning that the slope of log Ipeak and SPL is independent of frequency. Moreover, the intercept is found to be linear with the frequency in Figure S7a. Through linear fitting method, the expression of peak current is obtained: (, SPL) = (1.07 × 10 × − 9.39 × 10" ) × 10 #⁄

%$(3)

The detailed fitting process can be found in the section entitled “Fitting process of output peak current” in the Supporting Information. In addition, the fitting curves fit well with the original data in Figure S7b indicating that the fitting formula is reliable. From Equation (3), the sensitivity can be calculated. The frequency sensitivity at different SPL is 1.07 × 10-17 × 10SPL/20 A/Hz. Besides the pressure sensitivity is 5.35 × 10-11 × f - 9.39 × 10-11 A/Pa. Besides, the relationship between transferred charge and SPL is investigated and the corresponding piezoelectric coefficient d33 is calculated: '(( =

) *

= /×

+ ,-. 012⁄34 ×%


(4)


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Here, Q (the transferred charges) is calculated by the integral of current and F (stimulated force) is calculated by F=S*SP, where S is the effective area (4 × 4 cm2) and SP is derived by Equation (2). As shown in Figure 3c, the transferred charge exponentially increases with SPL, while the unchanged d33 shows the independence of d33 to SPL. The frequency response of the SWAVS is also measured. At the stimulated SPL of 115 dB, the peak current increases linearly with frequency from 1.3 nA at 200 Hz to 4.5 nA at 800 Hz (Figure 3d). The partial enlarged views of these current signals (Figure S8) clearly reveal that the signal shapes are all in standard sine waveform. The signal frequencies are all consistent with the stimulated voice, indicating the excellent frequency responding ability of the SWAVS. The d33 coefficient and the transferred charge at different frequencies, as illustrated in Figure 3e, both remains unchanged. As a wearable sensor, the SWAVS was attached to a curved surface to show its property stability at a bending state. The insert in Figure 3f shows the bending state of the device when attached to a white cylinder with the diameter of 8 cm. The schematic diagram of the bended device and the bend degree θ is given in Figure S9a. The responding currents under different frequency for original and bending states are consistent with each other well and the current ratio is close to 1, showing the stable property of the flexible SWAVS. Furthermore, the peak current (Figure S9b) also shows good stability at different bend degrees (less than π). A further step was taken to characterize the directivity of the SWAVS. A fixed voice was utilized to stimulate a completely suspended SWAVS from different directions at a distance of 30 cm and the responses were showed in the polar diagram (Figure 3g). As the flexible device is not so flat at the suspended state, the responses at the incident angle are a little higher than the other part. It should be noted that the response reduce rapidly when the incident angle is close to 90° or 270°, which shows the direction selectivity of the SWAVS. The stability of the SWAVS is a very important property to ensure its ability of continuous working. Herein, the device continously worked for about 2,000,000 cycles under 8 ACS Paragon Plus Environment

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the acoustic stimulation of 800 Hz and 115 dB (Figure 3h). Simultaneously, we measured device stability the under a mechanical stress (4 N, 5 Hz) for about 18,000 cycles continuous working (Figure S10). The outputs at different cycles indicated the ignorable variation and excellent stability in continuous working. Complex-frequency acoustic response of a SWAVS. The complex-frequency acoustic response was measured under the stimulation of human voice. Figure 4a shows the real-time current signal in response to human speaking at a distance of 30 cm. When the speaker spoke the numbers “2”

“0” “1”

“6” one by one, the current signals were observed clearly and

the Signal to Noise Ratio (SNR) reached almost 20. Such high SNR avoids the device from the interference of environmental noise and indicates its excellent performance in human voice sensing. Figure 4b shows the short-time energy spectrum of the acquired current signal. The real-time energy distribution of the human voice is clearly reflected and the highest Energy Ratio (ER) of voice and noise reaches 10, which is useful in the distinction of actual voice and environmental noise. By virtue of the high ER, the actual voice signal can be intercepted from noise and then used in the signal analysis. The intercepted signal of the last word (as framed in Figure 4a) is showed in Figure 4c, elaborately indicating the rich high frequency signals that responding to the concrete dynamic change in human voice. The high-frequency details can be used to characterize the voiceprint of the speaker, which will be of great significance in voiceprint recognition and similar applications. Furthermore, to characterize the frequency distribution of the spoken human voice, the short-time Fourier transform of the acquired current signal was carried out. The Fourier spectrum (Figure 4d) indicates that the voice contains frequencies ranging from 0 to 4 kHz but the major components locate around 500 Hz, which are more important to characterize the human voiceprints. Performance of the voiceprint recognition system. By virtue of the compelling superiorities, including high acoustic impedance, high voice sensitivity, high SNR, excellent stability and 9 ACS Paragon Plus Environment


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flexibility, the SWAVS is used in a voiceprint recognition system. As illustrated in Figure 5a, the SWAVS is a foremost active sensor to detect voice, acting as the core in the schematic diagram of the whole voiceprint recognition system. In the actual demonstration, the SWAVS was sew on the cuff of a lab coat. When the speaker spoke to his cuff, the detected acoustic wave would be converted to a current signal by the SWAVS, and then collected by a data acquisition card, which was controlled by the portable computer (PC). The voiceprint features would be extracted and contrasted with the library files, which had been recorded before by the actual owner of the system. The judgment results contain two parts: password identification (judging from single-number contrasts) and speaker recognition (judging from the comparison of acquired voiceprint features and the library data). Then, the two judgment results would be displayed on the screen together with the instantaneous current signal and also transmitted to a single-chip microcomputer, which acted as a controller to realize the system react through simple logical algorithms. There would be several conditions when someone tried to open the voiceprint-lockbox as we demonstrated. Firstly, the owner spoke the right password “2016” and the detected current signal was showed in Figure 5b. As illustrated in Figure 5c, the four numbers were identified and showed on the screen. The password indicator and the speaker indicator both turned green, meaning that the password and the speaker were both correct. Therefore, the indicator LED on the voiceprint-lockbox turned green and the box opened automatically. Secondly, the owner spoke the wrong password “1234” as showed in Figure 5d. The system judged out the right speaker and the wrong password and the box kept locked, as illustrated in Figure 5e. Thirdly, a cracker spoke the right password “2016” as showed in Figure 5f. The system judged out the wrong speaker and the right password and the box kept locked, as illustrated in Figure 5g.


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The whole demonstration process is showed in Supporting Video 1 and the short-time Fourier spectrums of the acquired current signals in the three situations are given in Figure S11. Only the right speaker and right password can open the voiceprint-lockbox, demonstrating that the reliable SWAVS together with the voiceprint recognition mechanism can ensure the safety of the private items, and this facility can be applied in the advanced non-contact biometric recognition and safety guarantee systems, etc. CONCLUSIONS In summary, we design a new type of sensitivity-enhanced wearable active voiceprint sensor (SWAVS) based on cellular PP piezoelectret. The SWAVS, with sensitive and stable response to acoustic stimulations, exhibits tripled output current (from 0.89 to 2.79 µA/m2) and enhanced sensitivity (from 1.98 pA/Hz to 5.81 pA/Hz at 115 dB) through dipole orientation control. In human voice detection, the obtained high signal to noise ratio (up to 20) and high energy ratio (up to 10) demonstrate the unique advantage of SWAVS in human voice sensing and voiceprint recognition. As an instantiation, we contribute a voiceprint recognition system based on the SWAVS. Notably, human voice sensing and voiceprint recognition are realized simultaneously. Our study offers a novel strategy for wearable non-contact bio-recognition sensor and safety guarantee system. EXPERIMENTAL SECTION Fabrication of cellular polypropylene piezoelectret films: The commercial biaxially oriented cellular PP films (Treofan film EUH75) were firstly cut into 5 × 5 cm2 samples as the raw material. The samples were placed into a hermetic chamber, filled with nitrogen gas with a gas pressure of 3 MPa. After heating the chamber to 90 ℃ and keeping for 1 hour, the gas pressure inside was quickly deflated to atmospheric pressure within 5 seconds and the samples were taken out. During the process, the thickness of the samples would be expanded to be more than two times. Then, the samples were polarized in the perpendicular direction 11 ACS Paragon Plus Environment


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via a corona charging setup, which was made up of a positive or negative high voltage DC power supply and a corona needle. The chosen voltage polarity was used to control the dipole orientation of the samples. During the charging process, cellular PP was placed 5 cm below the needle and the charging voltage was maintained -20 kV or +22 kV for 10 min. Subsequently, magnetron sputtering system was used to coat silver (Ag) as electrodes (4 × 4 cm2) on the samples and the textile membranes. Assembly of the SWAVS: Three negative polarized PP were laminated together using double-sided adhesive tape (3M, series XQ, non-conductive) and then sandwiched between two textile-based electrodes, forming the original three-layer device (Type I). For the SWAVS (Type II), a positive polarized PP was sandwiched between another two negative polarized PP and then the two textile-based electrodes were attached, forming the opposite polarization orientation in the second PP layer. Simulation: The simulation process included steady state simulation and transient simulation. For steady state simulation, the COMSOL electrostatic module was utilized to calculate the potential distribution of the device under a given constraint condition according to Gauss’s law. For transient simulation, a harmonic mechanical motion dair(t)=A×[cos(ωt)-1] was given. The COMSOL electrostatic module, deformation geometry module and circuit module were utilized to calculate the current output according to Gauss’s law and Kirchhoff's law. The initial conditions came from the results of the steady state simulation. Characterization: The morphology of the samples was imaged by a high-resolution field emission scanning electron microscope (FEI Nova NanoSEM 450). The conductivity of the Ag electrode was characterized by Keithley 2400. The Young’s modules and tensile strength were measured by universal testing machine (Reger RWT10). A loudspeaker (Edifier R18T 2.0) was utilized to generate voice with accurate frequency and adjustable volume. The sound pressure level was measured using a decibel meter (TES-1350A). The output characteristics of the device were measured using a NI PCI-6259 data acquisition card and a Stanford 12 ACS Paragon Plus Environment

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Low-noise Current Preamplifier (Model SR570). A single-chip microcomputer (Arduino UNO R3) was used to control the commercial LEDs and the electronic lock (SY-XG08). In the test, the samples were adhered to a plate in the perpendicular direction to the loudspeaker. The voice frequency was controlled by changing MP3 files with a programmed waveform. And the sound pressure level was controlled by adjusting the volume of the loudspeaker. ASSOCIATED CONTENT Supporting Information. The Supporting Information is available free of charge at http://pubs.acs.org. Characterization of the textile-based electrode. Measurements of the conductivity stability. Comparison of different structures. Working mechanism of original device. The repeatability and uniformity of the two polarization methods. Fitting results and process of output peak current. The partial enlarged view of the current outputs. Short-time Fourier spectrum of the acquired current signals. AUTHOR INFORMATION Corresponding Author E-mail: [email protected] Author Contributions The manuscript was written through contributions of all authors. All authors have given approval to the final version of the manuscript. ‡These authors contributed equally. ACKNOWLEDGMENT This work was financially supported by the National Natural Science Foundation of China (51322210, 61434001, 51672097), the National Program for Support of Top-notch Young Professionals, the Fundamental Research Funds for the Central Universities (HUST: 2015MS004), Director Fund of WNLO and Frontier and Key Technological Innovation Special Foundation of Guangdong Province (2014B090915001). The authors thank the 13 ACS Paragon Plus Environment


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facility support of the Center for Nanoscale Characterization & Devices, WNLO-HUST and the Analysis and Testing Center of Huazhong University of Science and Technology.


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Figure 1. Fabrication of a SWAVS. a) Schematic diagram, b) digital picture and c) cross-section view SEM image of a SAVS, indicating the multi-layer structure and flexibility.



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Figure 2. Working mechanism of a SWAVS. a) Finite element simulation of periodic potential change indicates the working mechanism of a SAVS, when it was in (I) original, (II) compressing, (III) ultimate compressed and (IV) releasing conditions, respectively. b) Schematic model of dipole configuration for the original (Type I) and sensitivity-enhanced (Type II) devices. c) Equivalent circuit models, d) normalized simulating current outputs and e) experimental current outputs of the two type devices.


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Figure 3. Single-frequency acoustic response of a SWAVS. a) Current responses to different sound pressure level (SPL) under a given frequency of 800 Hz. b) Dependence of peak current on the incident SPL. c) The transferred charges and d33 coefficients under different SPL. d) Current responses to different frequency under a given SPL of 115 dB and e) the corresponding transferred charges and d33 coefficients. f) Comparison of frequency response at original state and bending state for a SWAVS. Inset indicates the digital picture of the bending device. g) Polar diagram shows the directivity of a SWAVS. h) The durability test under SPL of 115 dB and frequency of 800 Hz for about 2,000,000 cycles continuous working.



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Figure 4. Complex-frequency acoustic response of a SWAVS. a) The real-time current signal in response to a speaker who was 30 cm away from a SWAVS. b) The short-time energy spectrum reflects the real-time energy distribution of the human voice and the highest energy ratio of voice and noise reaches 10. c) The intercepted signal of the last word shows the rich high frequency details in the voiceprint of the speaker. d) The short-time Fourier spectrum of the acquired current signal indicates the frequency distribution of the spoken human voice.


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Figure 5. Performance of the voiceprint recognition system. a) The schematic diagram of the voiceprint recognition system. Instantaneous current response of a SWAVS at different situations: b) right speaker spoke right password, d) right speaker spoke wrong password and f) wrong speaker spoke right password. c, e, g) Digital pictures show the corresponding recognition results and the final system reactions for the above-mentioned situations (b, d, f), respectively.



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TOC


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Sensitivity-Enhanced Wearable Active Voiceprint ... - ACS Publications

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