to vibration, temperature fluctuations and electromagnetic interference and more resistant to noises due to the absence of wires and installation of circuits close to the MEMS crystal.
Besides MEMS microphones, inexpensive, precise, and compact MEMS accelerometers can be used to detect acoustic signals. These devices became popular in the middle of the nineties of the past century. They contain one-, two-, or three-axis microsensors that can measure acceleration simultaneously on one or several coordination axes .
MEMS elements usually contain an electronic signal converter circuit that significantly simplifies the use of these devices. The converter of up-to-date MEMS accelerometers contain an electrometric amplifiers, 12- or 16-digit digital-to-analog converter and digital interface that usually uses the I2C serial data communication protocol. The ADXL103 MEMS accelerometer is widely used in smartphones and tablets. It costs six dollars and has the resolution of 1 mcg and operating range of frequencies from 5 Hz to 2.5 kHz. Its dimensions are 5 x 3 x 2 mm, and its weight is less than 2 g .
There are data on successful experiments on the use of up-to-date MEMS accelerometers to record breath sounds. The 12M1 MEMS accelerometer was used in adult volunteers. It successfully registered not only pulse fluctuations of the front chest wall but also breath sounds. Placing an accelerometer sensor on the front wall of the trachea allowed recording its vibrations within the range of 4.5 kHz in smokers whose length of smoking was over 5 yrs. The sounds recorded matched with pathologic side tones accompanying chronic bronchitis .
Based on the research findings and recommendations presented in Table 1 , the authors chose the following types of acoustic sensors for the initial research stage: electret, piezoelectric, and MEMS microphones. As opposed to other representatives of this group, the level of sensitivity of compact dynamic microphones did not allow recording weak acoustic signals.
During the experiments, it was revealed that sensors based on MEMS microphones recorded the highest-quality bronchopulmonary sounds. The microphones were installed into a sound-detecting head of the binaural stethoscope. Signals detected by the sensor were transmitted to a notebook's microphone input, where they were digitized by a sound AD converter (16 bit, 44.1 kHz) and recorded on a PC hard drive in the form of WAVE files without any loss of quality.
Figure 1 demonstrates a graphic representation of breath sounds obtained by means of the acoustic sensor based on the MEMS microphone.
As it is seen from Figure 1 that demonstrates the graphic representation of breath sounds produced by the bronchopulmonary system, the acoustic sensor based on the MEMS microphone allows recording high-quality acoustic signals of the human bronchopulmonary system. Signals contain a maximum volume of useful information and minimum volume of noises hindering the diagnosis making process in case of auscultation. In this case, the acoustic sensor was placed in the area of the right second intercostal space. The frequency range of the signal recorded was 60-140 Hz .
Bronchopulmonary signals recorded by means of the sensor designed by the authors can be used for further mathematic processing. It will allow singling out signal fragments corresponding to patients' inspiratory/expiratory sections. They can be analyzed further to automatically diagnose patients' disease.
Unlike the noises of the human bronchopulmonary system, most sound vibrations reasoned by heart sounds and noises are beyond the limits of sound perception. Therefore, during the registration of phonocardiograms an acoustic sensor should register sound vibrations beyond perception by ear. It is possible to make up the complete picture of heart noises by analyzing phonocardiograms obtained in each frequency range. As for the diverse filtration schemes, the Maass and Weber scale (Table 2) used in the modern phonocardiographs has the greatest practical importance nowadays.
In order to perform the long-term monit