MONITORING OF BREATHING BY BIOACOUSTIC METHOD

Summary

This paper describes a method of the breathing detection based on the sensing of acoustic signals in trachea. Parameters of the breathing, detection inspiration and expiration and apnoea pause are possible to determine from these signals. This method is simple and easy to use, portable and provides an accurate measurement and seems to be well suited for use as a modern breathing monitor. Monitoring of Respiration is important for monitoring respiration towards observation quality sleeping or The Sudden Infant Death Syndrome (SIDS).

Keywords:
Breathing, biomedical sensors, biological signals

Introduction

Organism needs the energy for an arrangement of the all vital function. Energy is released by the oxidation of the energy matter (saccharides, lipids and proteins).

Water and carbon dioxide are evolved too. Continuous supply of the oxygen and removing carbon dioxide are necessary by the oxidative processes. Therefore, the respiration falls into basic vital functions. In medicine this function is needed to sense and to detect its parameters. This article describes a solution of respiration diagnostics. Concretely it is thought the external respiration (pulmonary).

The organism is possible to imagine as the biological system generating biological signals that transfer information of the biological system. These signals are nearly always continuous. Bio signals are possible to divide according to origin into electrical, magnetic, acoustic, chemical, mechanical, optical, impedance, thermal, radiological and ultrasonic [5, 6].

The respiration can be detected in various ways. One of methods is the detection of the gas flow (Fleish pneumotachometer). Further, the respiration is possible to detect from the EEG signal. The method based on the imaging of the acoustic signals appears as very attractive.

Typical lung volumes and mechanism of the respiration are measured by the functional examine of lungs. One of the ways of study regulation respiration cycle is monitoring of breathing paradigm – depending among basic quantities of ventilation: respiration frequency, minute ventilation, inspiration and expiration time, apnoea pause, the respiration volume.

Further parameters are: pressures and flow rates of respiration gases, lung plasticity, depending between the flow and the volume, resistance of airways [1, 2].

Characterization of Breathing

The breathing cycle is divided into four different successive phases: inspiratory phase, inspiratory pause, expiratory phase and expiratory pause. The breathing cycle is defined here as starting with the onset of inspiration at the moment when the air inflow starts. When the airflow stops, the inspiratory phase ends and the inspiratory pause begins and lasts until the air begins to flow out from the lungs and the expiratory phase starts. The expiratory phase is followed by the expiratory pause, which lasts until the end of the breathing cycle [3].

Method of Monitoring

Bioacoustic method is based on measuring acoustic signals originating in the trachea (Fig. 1). The microphone is used to measure these acoustic signals. The acquired signal of the microphone m(t) is consisted of different sources. Additional signals are added to the desired signal a(t). The equation (1) describes the relationship between the signal m(t) and the signal components. Constituent components are divided in four categories originating from: a) the airflow in the trachea, b) disturbances at the interface between the microphone and skin, c) internal components from the body without relation to the airflow and d) external components generated by the events in the environment where the measurements are made [3].

where

m(t) ... signal observed by the microphone

a(t) ... vibration airflow in the trachea

y(t) ... disturbances from the interface between the microphone and skin

i₁(t) ... internal disturbances from the blood flow

i₂(t) ... other internal disturbances, e.g. from vessel movements

e₁(t) ... external continuous disturbances

e₂(t) ... external transient disturbances 

The measure system in Fig. 2 was used for finding the information about the measured acoustic signal. Measure system is composed of four parts: microphone part, signal preprocessing, interface and PC. 

The microphone part converts acoustic signal into electrical signal. Microphone 1 senses breathing signal originated in trachea – signal a(t). This microphone also senses additional signals added to the desired signal a(t) – external signals. The microphone 2 is used only for sensing external signals. Signals from both microphones are subtracted to cancellation of external signals. These signals from microphones are amplified by signal preprocessing block and converted to digital form by interface. Processing of signals is provided in PC by software LabView. Fig. 3 shows microphone part with MEMS microphone and its electrical scheme.

In Fig. 4 is illustrated algorithm for processing signals of microphones. Signals from both microphones are converted to digital form by DAQ device. These signals are subtracted to cancellation of external signals. Level adjustment block serve for equalization of both signal level from microphones. Afterwards it follows filtration of signal in band 200Hz – 800Hz. This eliminates the remaining spurious signals. FFT block pursues conversion signal from time domain to frequency domain (spectrum). Finally, signal in time domain and its spectrum are displayed. RMS block calculates RMS value of signal. The RMS signal is compared with level of service set for detection of apnea.

The acoustic signal of the breathing occurs in frequency band from 200Hz to 800Hz, see Fig. 5. Therefore, the sampling frequency must be greater than 1600 Hz. The repeated breathing pattern and differences between inspiration and expiration are possible to read in the time behavior of the signal. The smooth beginning and the abrupt ending are often obvious during the inspiration. On the other hand, the behavior of the expiration shows the abrupt beginning and the smooth ending. Both phases are separated with the inspiratory and expiratory pauses. Fig. 6 illustrates breathing pattern – inspiration and expiration.

Recent advances in Micro-Electro–Mechanical System (MEMS) technology enable complex miniaturized systems for biomedical applications – e.g. the integration of the Surface Acoustic Wave (SAW) sensors with a MEMS microphone [4]. The small size and wireless operation shows wide range of its potential patient monitoring applications including monitoring breathing sounds in apnea patients, monitoring chest sounds after cardiac surgery and also monitoring chest sounds of the newborns by causing minimal discomfort. Fig. 7 represents the concept of the SAW based wireless acoustic sensor. Acoustic signal from trachea are detected by microphone cause the change of the impedance of the sensor (microphone) connected across the output Interdigital Transducer (IDT) and the amplitude and phase of the reflected signal is as well as change and this is transmitted by the antenna. 

Another concept is depicted in Fig. 8. Sensory system contains cheap commercially available MEMS microphones. The detection of the breathing is based on the pick-up of the acoustic signal by the sensor and subsequent processing in PC. The communication between sensor and PC is wireless. The input part comprises the microphone which converts the acoustic signal to the electric signal. After this signal is amplified and digitalized. Subsequently, the signal is coded and sent by the transmitter. The receiver gives the information to PC where the breathing is analyzed. Two microphones are used in this system. The microphone 1 is used for sensing of the breathing – signal a(t). This microphone also senses additional signals added to the desired signal a(t) – external signals. The microphone 2 is used only for sensing external signals. Signals from both microphones are added to cancellation of external signals. The power part is used for the feeding sensor (battery, thermo or vibration principle). 

Conclusion

Methods, based on the monitoring of the chest motion, do not inconvenience patient with sensors placed on the body. On the other hand, it is necessary that the patient is at rest on bed. Acoustic method is very interesting for the non-invasive measurement of the breathing and for the possibility of CMOS MEMS integration. Further, this method is simple and easy to use, portable and provides an accurate measurement and seems to be well suited for the use as a modern breathing monitor. Parameters of the breathing, the detection of inspiration and expiration and the apnoea pause are possible to determine from the time behavior.

Acknowledgement

This research has been supported by the Czech Science Foundation project No. 102/09/1601 "Intelligent Micro and Nano Structures for Microsensor Realized Using Nanotechnologies" and partially by The Ministry of Interior of the Czech Republic research program No. VG20102015015.

Jiri Kroutil,M.Sc.

Department of Microlectronics

Faculty of Electrical Engineering

Czech Technical University in Prague

Technicka 2, CZ-166 27 Prague

E-mail:kroutj1@fel.cvut.cz

Phone: +420 224 352 356