Condenser Microphone Research Articles

MEMS and ECM Sensor Technologies for Cardiorespiratory Sound Monitoring-A Comprehensive Review.

This paper presents a comprehensive review of cardiorespiratory auscultation sensing devices (i.e., stethoscopes), which is useful for understanding the theoretical aspects and practical design notes. In this paper, we first introduce the acoustic properties of the heart and lungs, as well as a brief history of stethoscope evolution. Then, we discuss the basic concept of electret condenser microphones (ECMs) and a stethoscope based on them. Then, we discuss the microelectromechanical systems (MEMSs) technology, particularly focusing on piezoelectric transducer sensors. This paper comprehensively reviews sensing technologies for cardiorespiratory auscultation, emphasizing MEMS-based wearable designs in the past decade. To our knowledge, this is the first paper to summarize ECM and MEMS applications for heart and lung sound analysis.

Prediction of Vascular Access Stenosis by Lightweight Convolutional Neural Network Using Blood Flow Sound Signals.

This research examines the application of non-invasive acoustic analysis for detecting obstructions in vascular access (fistulas) used by kidney dialysis patients. Obstructions in these fistulas can interrupt essential dialysis treatment. In this study, we utilized a condenser microphone to capture the blood flow sounds before and after angioplasty surgery, analyzing 3819 sound samples from 119 dialysis patients. These sound signals were transformed into spectrogram images to classify obstructed and unobstructed vascular accesses, that is fistula conditions before and after the angioplasty procedure. A novel lightweight two-dimension convolutional neural network (CNN) was developed and benchmarked against pretrained CNN models such as ResNet50 and VGG16. The proposed model achieved a prediction accuracy of 100%, surpassing the ResNet50 and VGG16 models, which recorded 99% and 95% accuracy, respectively. Additionally, the study highlighted the significantly smaller memory size of the proposed model (2.37 MB) compared to ResNet50 (91.3 MB) and VGG16 (57.9 MB), suggesting its suitability for edge computing environments. This study underscores the efficacy of diverse deep-learning approaches in the obstructed detection of dialysis fistulas, presenting a scalable solution that combines high accuracy with reduced computational demands.

Fiber-optic bionic microphone based compact sound source localization system with extended directional range.

Traditional sound source localization (SSL) systems based on electret condenser microphone arrays are bulky because their localization accuracy depends on the size of the array. Inspired by the hearing mechanism of the parasitic fly Ormia ochracea, the localization accuracy of miniature bionic SSL devices breaks through the limitations of device size, but their ability to localize low-frequency sound sources over a wide angular range remains a challenge. In this work, a compact low-frequency SSL system with an extended directional range was prepared using two bionic micro-electro-mechanical system diaphragm based fiber-optic microphones, which form a non-coplanar array with a size of Φ44 mm × 13 mm. An algorithm for quantifying the azimuthal angle of a sound source is established for the prepared SSL system. Simulation and experimental results show that the prepared SSL system is capable of determining the propagation direction of acoustic signals with a frequency of less than 1 kHz in the azimuthal range from -90° to 90°, with a linear response in the range from -70° to 70°, and an angular measurement accuracy of the system within the range of ±7°.

Two-dimensional sound pressure distribution: Visualization and calibration-free quantification via optical wave microphone CT scanning

In recent years, the optical wave microphone has emerged as an innovative technique, employing Fraunhofer diffraction of a laser beam, and shows promising applications in various acoustic domains where high electric and/or magnetic fields preclude the use of traditional microphones. This study utilized an optical wave microphone computed tomography (CT) scan and calibration-free quantification to ascertain sound pressure levels at multiple distances from the ultrasonic oscillator. The cornerstone of this study, which is different from the author’s previous studies, is the quantification of sound pressure distribution via a theoretical model that encompasses all physical parameters pertinent to the optical wave microphone’s experimental arrangement. This method has proven effective in visualizing and quantifying the two-dimensional sound pressure distribution emitted by an ultrasonic oscillator (40 kHz) without the necessity for calibration. The results demonstrate that the sound pressure distribution determined using the calibration-free optical wave microphone CT scan is in good agreement with the measurements obtained through a condenser microphone.

Design of osteosynthesis plate for detecting bone union using wire natural frequency

We have developed a novel osteosynthesis plate with bone union detection using a wire's natural frequency (BUDWF) to provide the quantitative result of bone union detection. The concept for detecting bone union is measuring the rate of frequency change. The frequency is measured from sound generated from the wire attached to a modified plate. The plate is modified from a Syncera ADLER B0409.10 and attached with 0.3 mm diameter 316L stainless steel wire. The sound generation mechanism was created by PEEK and installed on the plate to generate the sound. The preliminary experiments were conducted on a Sawbones tibia composite mimic. We used the cut Sawbones to create fracture samples with a 0, 0.5, 1-, 2-, and 5-mm gap representing the fractured bone with different gap sizes and prepared uncut Sawbones as a union sample. These samples were tested five times, and the sound was recorded from a condenser microphone and analyzed. We found that the BUDWF can differentiate samples with a fracture gap above 2 mm from the union sample, as the differences in the rates of frequency change between samples with a fracture gap above 2 mm and union samples were statistically significant. However, there was a limitation that the BUDWF plate was still unable to differentiate the 0 mm fracture gap and the union sample in this study.

Identifying steady and pulsatile two-phase flow regimes with pressure drop signals and acoustic emissions

Identifying two-phase flow regimes is vital for understanding phase-change heat and mass transfer processes. Traditionally, flow regime identification has relied on subjective flow visualization studies, which are then converted to flow regime maps applicable to specific operating conditions. However, these conventional, largely subjective, maps fall short in predicting abrupt changes in flow patterns that often occur during regular operation of vapor compression and absorption heat pumps and other thermal systems. Conventional flow regime maps are also inadequate for addressing the transient, intermittent, or periodic flow regimes that occur in boiling and condensation enhanced using acoustic and other emerging techniques. Therefore, there is a pressing need for alternative flow regime identification techniques that can adapt and reliably track rapid and local changes in two-phase hydrodynamics. Promising candidates for dynamic flow pattern classification include high-resolution pressure drop signals and acoustic emission spectra, which can provide insights into the local hydrodynamics within a flow channel. To assess the feasibility of these measurement techniques, differential pressure and condenser microphone measurements are recorded alongside high-speed videos of a two-phase flow of saturated R134a. The total mass flux and vapor quality are varied to understand the effects of phase velocity and liquid inventory on wave propagation in the channel. Additionally, forced oscillations are introduced to a steady two-phase flow to analyze their impact on flow patterns and their corresponding pressure drop and acoustic signals. Statistical analyses, including Gaussian mixture modeling, are employed to reveal characteristic pressure drop probability associated with each flow pattern, which form the basis for developing a model capable of predicting flow regimes in both steady and oscillating flows. The resulting framework introduces a new flow regime identification technique that can adapt to dynamic operating conditions, benefiting a wide range of thermal systems and phase-change processes.

Exploration of Digital Filter on Cardiac Monitor through Carotid Pulse and PCG (Phonocardiogram)

Heart defect early detection and correct diagnosis have become important healthcare priorities. Tools for monitoring cardiac problems are constantly being developed, with the PCG (Phonocardiogram) and Cardiac Monitor via Carotid Pulse essential for heart evaluation. Although condenser microphones embedded in electric stethoscopes have been used in past research as PCG sensors, more advancements are still required to reduce received noise. This study investigates how well a Chebyshev type-II digital filter works to reduce noise on the cardiac monitor using PCG and carotid pulse. The PCG sensor is the GY-MAX 9814 module, which is interfaced with an Arduino Uno microcontroller. Matlab, Visual Studio (used as a graph viewer), and Doppler Simulator (used as a phantom cardiac signal) are used. SNR (Signal to Noise Ratio) is used in the analysis to assess the effectiveness of two digital filter orders. The average SNR value for the Doppler Simulator is 0.001404 dB at order 2, however, it climbs dramatically to 18.60023 dB at level 4 according to the results of the SNR analysis. The average SNR value in human signals is 11.50718 dB before the filter, 0.001404 dB after the post-order 2 filter, and 12.0009 dB after the post-order 4 filter. According to the results, the digital filter of order 4 is more effective in reducing noise. This study highlights the possibility of an order 4 digital filter to improve the Cardiac Monitor through PCG and Carotid Pulse. Through enhanced signal quality, the creation of this gadget holds the potential for streamlining the identification of cardiac problems. Future developments in this technology could lead to more precise and trustworthy cardiac exams, which would help with early diagnosis and treatment of cardiovascular health.

Design and implementation of domestic dual-SIM telesecurity alarm system using voice code recognition

Violent crime cases which include, robbery, rape, and homicide are terribly on the rise, and the role of security in combating this menace cannot be overemphasized. This research presents a security device that aims at fighting violent crimes using voice recognition technology. The work also tends to solve the issue of network downtime when the user is out of reach for help in time of attack. In this work, a voice processing unit which comprises the condenser microphone, an amplifier, a shift register, and a timer was designed. The processing unit circuit was incorporated into microcontrollers which create Human-Device interaction and the GSM communication unit which is made up of two GSM modules. The two microcontrollers used in the design are PIC18F4520 and PIC16F873A. The microcontrollers were programmed with C++ using the MPLAB IDE software and the circuit simulation was done using Proteus Design Suite version 8. The result shows that the appropriate authority receives SMS whenever the pre-recorded code is mentioned. The result also shows that during network downtime, the second GSM module sends an SMS to the appropriate authority. Evaluating the performance of this work, it was observed that the device works best in a calm area compared to a noisy area. This work is designed to work in domestic areas like homes, offices, malls, and mainly areas free from so much noise. Therefore, this work has successfully reduced the crime rate in emergencies.

Comparison of two acoustic test fixtures for measuring impulse level dependent attenuation

In the American National Standards Institute (ANSI) S12.42-2010 standard for measuring insertion loss of hearing protection devices (HPDs) in impulsive noise, the range of peak sound pressure levels for the impulses is 132 to 168 dB peak sound pressure level (dB pSPL). The specification of the acoustic test fixtures (ATFs) included an IEC 60318-4 ear simulator fitted with a microphone. The microphones typically used are a ¼” cartridge and have a dynamic range up to about 169 dB pSPL. For most small caliber firearms, the peak SPLs are less than 170 dB SPL at the location of the shooters ear (Schulz et al. 2013). For some military weapon systems that produce impulses greater than 170 dB pSPL, impulse insertion loss cannot be assessed without exceeding the microphone maximum dynamic range. Some condenser microphones have maximum dynamic ranges of 190 dB pSPL. This paper compares insertion losses for HPDs measured on two GRAS 45CB ATFs with microphones with maximum dynamic ranges of 169 and 193 dB pSPL. Waveform distortion, field probe to unoccluded transfer functions between the ATF and field probe will be examined for distortion and accuracy when estimating the impulse level dependent attenuation.

Micro-electromechanical systems sensor characterization for acoustic prognostic health management

Prognostic Health Management (PHM) is the process used to optimize machinery use by detecting faults and predicting failures and a machine’s remaining useful life. PHM is especially important to electro-mechanical systems in order to maximize a system’s availability and effective operation. The use of Micro-Electromechanical Systems (MEMS) accelerometers and microphones for PHM analysis is beneficial because it enables non-destructive acoustic testing with reduced cost, reduced size, and more efficient vehicle integration with other electronics than current methods. This research quantitatively studies a variety of MEMS sensors to understand how they measure acoustic data in a lab setting and on a truck with a diesel engine compared to piezoelectric accelerometers and condenser microphones. Diesel engines are common in many vehicles and hybrid-electric power systems, so the results will be applicable to a variety of situations. By applying signal processing techniques and PHM condition indicators to the data, standardized metrics can be developed to determine the best sensor for different PHM analyses.

Tony F. W. Embleton in the Acoustics Section, Physics Division, of the National Research Council of Canada (NRCC)

Tony completed his PhD in three years at Imperial College (London) studying under Dr. R.W.B. Stephens. He then joined George Thiessen and Edgar Shaw at NRCC to form the core of what became arguably the most influential and productive research group in acoustics in Canada from the 1960s to the 1980s. An important activity was service to industry, a role Tony embraced by collaborating with industry associations, participating in committees and directing his research activities. Working with George Thiessen, he succeeded in reducing the noise of couch rolls, a major source of noise in paper making, by randomizing the pattern of holes through which air was sucked to dry the paper. Other successful noise control projects included staggered stator blades for gas turbine engines and mufflers for rock drills. Tony made seminal contributions to outdoor sound propagation and refined condenser microphone calibration. In addition to his research and outreach, he found time for professional service to the ASA and CAA, including serving as founding editor of what is now Canadian Acoustics, and to develop standards and mentor younger scientists, He is remembered for his cheerfulness and willingness to provide advice and engage in conversation on any and all topics.

Highly-sensitive wafer-scale transfer-free graphene MEMS condenser microphones

Since the performance of micro-electro-mechanical system (MEMS)-based microphones is approaching fundamental physical, design, and material limits, it has become challenging to improve them. Several works have demonstrated graphene’s suitability as a microphone diaphragm. The potential for achieving smaller, more sensitive, and scalable on-chip MEMS microphones is yet to be determined. To address large graphene sizes, graphene-polymer heterostructures have been proposed, but they compromise performance due to added polymer mass and stiffness. This work demonstrates the first wafer-scale integrated MEMS condenser microphones with diameters of 2R = 220–320 μm, thickness of 7 nm multi-layer graphene, that is suspended over a back-plate with a residual gap of 5 μm. The microphones are manufactured with MEMS compatible wafer-scale technologies without any transfer steps or polymer layers that are more prone to contaminate and wrinkle the graphene. Different designs, all electrically integrated are fabricated and characterized allowing us to study the effects of the introduction of a back-plate for capacitive read-out. The devices show high mechanical compliances Cm = 0.081–1.07 μmPa−1 (10–100 × higher than the silicon reported in the state-of-the-art diaphragms) and pull-in voltages in the range of 2–9.5 V. In addition, to validate the proof of concept, we have electrically characterized the graphene microphone when subjected to sound actuation. An estimated sensitivity of S1kHz = 24.3–321 mV Pa−1 for a Vbias = 1.5 V was determined, which is 1.9–25.5 × higher than of state-of-the-art microphone devices while having a ~9 × smaller area.

Photoacoustic Imaging using Diode Laser for Soft Tissue Visualization

This study aimed to develop a photoacoustic imaging system using a diode laser as a radiation source, and a condenser microphone as a soft-tissue image detector. These tools were set in a static position and combined with the mechanic component to move the object table in the X-Y direction and were controlled by a computer with a LabView program. The result showed the built photoacoustic imaging system was used to analyze soft tissue using a diode laser in the frequency range of over 15 kHz with a 24%-47% duty cycle modulation. Furthermore, the minimum shift of the mechanic component X-Y stage was 0.02 mm, the sampling data rate was 1 second/pixel, and the image showed soft tissue intensity is generally higher than non-biological materials.

A non-dimensional time-domain lumped model for externally DC biased capacitive microphones with two electrodes

Microphones that utilize externally biased capacitive transduction (condenser microphones) are typically being modeled in lumped parameter networks where the mechanical, acoustical, and electrical elements are all represented as passive electronic circuit components. Those models have been shown to be insufficient to fully describe crucial aspects of this type of transducer, such as the pull-in phenomenon in which, after a certain distance and for a certain bias voltage, the moving electrode, typically a flexible membrane, attaches itself to the stationary. In this paper, we account for several non-linearities present in an extended simplified model of such a transducer in the time domain and identify the different factors related to its nonlinear response. We derive a time-domain non-linear non-dimensional system of equations for the coupled lumped model where we also take into account parasitic capacitances that are usually present and can significantly affect the overall electroacoustic performance as well as the fringing fields due to the nonhomogeneous electric field between the electrodes and nonlinearities related to damping due to the thin-film of air between the electrodes. We present the nondimensionalization method we used that allows for the identification of a novel set of nondimensional parameters that characterize the non-linear behavior of our system in the time-domain. A designer can use these parameters to optimize for linearity in the voltage response of the transducer. We post-process our time-domain solution to calculate the response to the fundamental excitation frequency and discuss the harmonic distortion. It is shown that coupling the electrical nonlinearities to the mechanical can significantly contribute to the nonlinear voltage response of the transducer. Our model agrees well with nonlinear measurements of analog microelectromechanical (MEMS) microphones for a set of physical values of the nondimensional parameters.

Experimental System and Software: Two-dimensional Return of the Platform to the Sound Source

We created a system, debugged it, and conducted experimental studies of the two-dimensional rotation of the supporting platform (with a camera, and a light source.) on the source of sound waves. The system was assembled based on two SYNCO Mic-M3 cardioid condenser microphones and an Alesis IO-4 sound card. We wrote original software for analyzing and transmitting the result of processing harmonic acoustic signals for the response of the Arduino Uno control board. The rotation of the 2D platform is caused by two MG995 servos controlled by this microcontroller. We used a model of a serial COM port, which allows to send data received from the platform in the form of packets for processing by a portable personal computer. Based on the results of the experimental test and the basis of the literature data, a model of control of the two-dimensional platform of returning to the source of sound has been offered.

Cartilage Conduction Sounds in Cases of Wearing Different Transducers on a Head and Torso Simulator with a Manipulated Ear Pinna Simulator.

Cartilage conduction is known widely as a third hearing transmission mechanism after the air and bone conduction methods, and transducers dedicated to the production of cartilage conduction sounds have been developed by several Japanese companies. To estimate the acoustic performance of the five cartilage conduction transducers selected for this study, both airborne sounds and cartilage conduction sounds were measured. Airborne sounds can be measured using a commercial condenser microphone; however, cartilage conduction sounds are impossible to measure using a conventional head and torso simulator (HATS), because the standard-issue ear pinna simulator cannot reproduce cartilage conduction sounds with the same spectral characteristics as the corresponding sounds measured in humans. Therefore, this study replaced the standard-issue simulator with a developed pinna simulator that can produce similar spectral characteristics to those of humans. The HATS manipulated in this manner realized results demonstrating that transducers that fitted the entrance to the external auditory canal more densely could produce greater cartilage conduction sounds. Among the five transducers under test, the ring-shaped device, which was not much larger than the entrance to the canal, satisfied the spectral requirements.

An affordable and easy-to-use tool to diagnose knee arthritis using knee sound

Arthritis, the most common form of osteoarthritis, affects millions of individuals worldwide. While it can affect any joint in the body, it predominantly affects the hands, neck, back, knees, and hips. Traditional imaging technologies like X-rays are impractical for diagnosing knee pathology and are insufficient for detecting disease symptoms, especially in the early stages of damage. Invasive procedures such as arthroscopy are often required to identify changes, but they are unsuitable for repeated assessments, follow-ups, or monitoring. Vibro-acoustography (VAG), which utilizes vibration and acoustic signals from the human knee during movement, has emerged as a non-invasive diagnostic tool. However, muscle-induced low-frequency irregularities triggered by knee movement significantly impact the accuracy of VAG signals. In this study, a novel machine learning-based approach is introduced for detecting knee osteoarthritis by processing sound signals recorded by a condenser microphone. Knee sounds from both healthy and osteoarthritic patients were captured during knee swing motions (flexion and extension). Three features were extracted from the knee sounds and classified using the Perceptron, MLP, SVM, GRNN, and RBF classifiers. The performance of different features and classifiers was compared, revealing that one feature demonstrated robust results with a high accuracy of 87% and an F1-score of 0.86. Compared to other conventional methods, the proposed approach is characterized by its speed, affordability, portability, and user-friendliness, with the potential for easy development into a mobile application.

Sphygmomanometer Dynamic Pressure Measurement Using a Condenser Microphone.

There is a worldwide need to improve blood pressure (BP) measurement error in order to correctly diagnose hypertension. Cardiovascular diseases cause 17.9 million deaths annually and are a substantial monetary strain on healthcare. The current measurement uncertainty of 3 mmHg should be improved upon. Dynamic pressure measurement standards are lacking or non-existing. In this study we propose a novel method of measuring air pressure inside the sphygmomanometer tubing during BP measurement using a condenser microphone. We designed, built, and tested a system that uses a radiofrequency (RF) modulation method to convert changes in capacitance of a condenser microphone into pressure signals. We tested the RF microphone with a low-frequency (LF) sound source, BP simulator and using a piezoresistive pressure sensor as a reference. Necessary tests were conducted to assess the uncertainty budget of the system. The RF microphone prototype has a working frequency range from 0.5 Hz to 280 Hz in the pressure range from 0 to 300 mmHg. The total expanded uncertainty (k = 2, p = 95.5%) of the RF microphone was 4.32 mmHg. The proposed method could establish traceability of BP measuring devices to acoustic standards described in IEC 61094-2 and could also be used in forming dynamic BP standards.

Round-robin tests of the different types of sensors for floor impact sounds and vibrations

Recently, floor impact noise monitoring system was introduced for residents to control making noises spontaneously using sound and vibration sensors. The present study aims to investigate the performance and characteristics of various current using sound and vibration sensors which can be eventually compatible with the floor impact noise monitoring system. For measurements of sound sensors, 7 sound microphones were used including 2 condenser types, 4 dynamic types, and 1 electro condenser type. Also, 6 vibration meters were used including 2 MEMS types, 2 Piezo types, and 2 spring types. Sound levels were measured in a semi-anechoic chamber using white noise in the frequency range from 63 Hz to 12.5 kHz. Vibrations were measured using high density wooden panel with an impact ball in the frequency range from 16 Hz to 4 KHz. Round-robin tests were done to confirm the exact performances of all the sensors under same condition. As a result, it was found that dynamic type microphones show the most similar response characterization in comparison with the reference condenser microphone especially in the air-borne sound frequency range from 250 Hz to 2 KHz. Also, it was found that spring type vibration meters show the most appropriate characterization at 63 Hz, most critical structure-borne sound frequency. Thus, the results drawn from the round-robin tests could be used for floor impact noise monitoring systems with the benefit of both economy and performance.

Sensitivity of an optical feedback interferometer for acoustic waves measurements.

This work presents a sensitivity study on the use of an optical feedback interferometer to measure acoustic pressure from plane waves. The sensitivity is established by linearising the interferometer's governing equations. It is shown to be independent of the acoustic wave frequency but dependent on configuration parameters such as the optical feedback parameter or the length of the laser through which the acoustic wave passes. Experimental validation is carried out using three acoustic waveguides in the 0.5-18 kHz range. The sensitivity obtained enables broadband acoustic pressure measure with a low mean relative error in comparison with a reference condenser microphone.