Monitoring of Breath Sound under Daily Environment
by Ceiling Dome Microphone
Yoshifumi NISHIDA, Toshio HORI, Takashi SUEHIRO, and Shigeoki HIRAIIntelligent Systems Division, Electrotechnical Laboratory
Abstract
This paper proposes a new method for monitoring normal breath sounds in our daily environment where
many kinds of noise exist. In a typical conventional
breath monitor, a thermistor, an accelerometer, or acontact-type microphone must be attached directly
to the person’s body such as near the nose and themouth, or over the chest wall and the trachea. This
paper focuses on key issues stemming from a factorof the environment; extraction of breath sounds fromsensor signals contaminated by environmental noise,and the realization of a monitoring system suitablefor our homes. The features of normal breath sounds
were clariﬁed by frequency analysis. Based on the features, a method for extracting normal breath sounds is
discussed. This paper also describes a ceiling dome microphone, which is a kind of a parabolic sound concentrator. It has a function of detecting normal breathingsounds with high sensitivity while keeping the room’s
appearance natural. The gain obtained by such a concentrator is analyzed theoretically from an acoustic
point of view. Experimental results conﬁrmed the feasibility of the proposed method.

1

Introduction

Daily personal healthcare at home is a topic of great
concern recently. Continuous monitoring of a person’s physiological status by him or herself is required.
An unrestrained and non-invasive means of observing
physiological status is the key technology to realize
it. Visual, tactile, and/or auditory sensors are quite
suitable for this purpose.
The authors are experienced in conducting clinicalstudies for monitoring respiratory conditions of a patient with the help of doctors at a hospital. The
human respiratory system is very complex and understandably requires monitoring with many sensors
such as pressure sensors to monitor the chest and abdomen’s movement, thermistor for airﬂow around thenose and mouth, a contact-type of microphone forsnoring, oximeters for oxygen saturation, and mercury
sensors for posture. Indeed, these sensors can monitor
physiological values certainly as long as they are usedadequately. Actually, however, they very often failto monitor continuously. For example, in 48 percentof the cases (21 of 43 cases) in the clinical study theauthors conducted, the monitoring system failed tomeasure the physiological values continuously enoughto diagnose disease. This suggests that even in a hospital where more priority is given to accurate monitoring than to comfortable monitoring, unrestrained
monitoring is required to minimize this failure.
The aim of this paper is to propose a new method formonitoring normal breath sounds in a daily environment where many kinds of noise exist. This method
has the possibility of use for monitoring respiratory
airﬂow in place of a conventional airﬂow monitor suchas a thermistor, an accelerometer, or a contact-type of
microphone.
This paper focuses on key issues stemming from a factor of the environment; 1) extraction of breath sounds
from sensor signals contaminated by environmental
noise, and 2) realization of a monitoring system suitable for use in our homes.
As for 1), in Section 2, the spectral characteristics ofnormal breath sounds are clariﬁed and a method for
detecting the sounds is discussed.
Frequency analysis of breath sounds has been attemptedby a number of researchers. In particular, Gavriely et
al. accurately characterized normal breath sounds andwheezing breath sounds[1, 2]. They used a contacttype of microphone which had a useful frequency response in the range of 0.02[Hz] to 2[kHz], and attached
it to the subject’s body over the chest wall and thetrachea. In contrast, the authors characterize normal
breath sounds which are emitted from the nose andpropagate in the air, using a condenser microphonewhose useful frequency response ranges from 30[Hz]to 100[kHz].
As for 2), a ceiling dome microphone, a kind of aProc. of 2000 IEEE International Conference on System, Man and Cybernetics, pp1822-1829, 2000
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parabolic sound collector, is presented in Section 3.
The gain obtained by the microphone is analyzed theoretically from an acoustic point of view.

Figure 1 shows the spectral distribution of normal
breath sounds measured in an environment where thenoise level is 38.5[dB(A)]. The normal breath sounds
were measured at a distance of 100[mm] from the subject’s nose. The microphone used is a non-directional
1/4-inch condenser microphone which has a useful frequency response in the range of 30[Hz] to 100[kHz]. Itssensitivity is −48[dBreV/Pa]. In the ﬁgure, the grayarea indicates normal breath sounds and the whitearea indicates background noise. This ﬁgure showsthat normal breath sounds include a wide range of
frequencies in an audio range.

Sound Pressure Level [dB]

BreathAir Purifier
PC/AT
Refrigerator
Air Conditioner
TV
Phone
None

90
80
70
60
50
40
30
20
10
0

0

2

4

6

8

10

12

14

16

18

20

Frequency [kHz]Fig. 2: Comparison between normal breath sounds
and background noise (0 to 20[kHz])ground noises in the range of 0 to 100[kHz]. This ﬁgure indicates that the frequency of deep breath sounds
reaches an ultrasonic range. The maximum frequency
is around 50[kHz]. In the ﬁgure, the two noises whosesound pressure level is about 40[dB] at 28[kHz] and56[kHz] come from a PC/AT computer.

100
BreathNone90Sound Pressure Level [dB]

Normal Breath Sounds

80
70
60
50
40
30
20
10
0

0

2

4

6

8

10

12

14

16

18

20

Frequency [kHz]Fig. 1: Spectral characteristics of normal breathsounds (0 to 20[kHz])In Fig. 2 noises generated by such sound sources as an
air conditioner, an air cleaner, a refrigerator, a telephone, a TV, and a computer are superimposed on
Fig. 1. These sounds were measured at a distanceof 100[mm]. The white area indicates the noises fromthese devices. The ﬁgure shows that compared withnormal breath sounds, noises generated by these devices have relatively limited and unique frequency distribution patterns. This indicates that it is possible
to detect normal breath sounds by selecting the range
where signal-to-noise ratio is high, and in the case of
our environment, the range is 5 to 15[kHz].
Figure 3 shows the spectral distribution of normal
breath sounds, deep breath sounds, and other back-Sound Pressure Level [dB]

2

100

100
Breath(deep)
Breath(normal)
Air Purifier
PC/AT
Refrigerator
Air Conditioner
None

90
80
70
60
50
40
30
20
10
0

0

10

20

30

40

50

60

70

80

90

100

Frequency [kHz]Fig. 3: Comparison among normal breath sounds,
deep breath sounds, and background noise (0 to
100[kHz])
Based on the above analysis, let us consider a methodfor detecting normal breath sounds. In general, theintensity of sound is proportional to 1/r2 in the freesound ﬁeld, where r denotes the distance from thesound source. Since the sound pressure level (SPL) in
decibel of normal breath sounds is at most 30[dB] at a
distance of 100[mm] from the source, if normal breathsounds are measured at a distance of 1,000[mm], theProc. of 2000 IEEE International Conference on System, Man and Cybernetics, pp1822-1829, 2000
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SPL of normal breath sounds falls 20[dB] to 10[dB],which is equal to the SPL of background noise, andthen it becomes impossible to detect normal breathsounds. This means that measuring the high-frequency
content of normal breath sounds is not enough to identify normal breath sounds. To detect normal breathsounds, it is necessary to measure the sounds at a position close to the source or at a position relatively distant from the source using a directional microphone.
The authors deal with a method for detecting breathsounds using a directional microphone in the next section.

3

Ceiling Dome Microphone

To detect the only sound that comes from a certain direction, we can utilize a super-directional microphonesuch as a microphone array[3], a reﬂector type of microphone (typically, a parabolic sound collector), ora line microphone. Generally speaking, if the microphones are the same in the characteristic length,
the resulting sensitivity is also the same even if theirmeasuring principles are diﬀerent. The reﬂector typeof microphone realizes high sensitivity easily withoutcomplex signal processing. This study adopts thistype of microphone for detecting breath sounds.
A parabolic, elliptical, or spherical concave is used forthe sound reﬂector. While a parabolic reﬂector is suitable for collecting a plane wave, that is to say when
the sound source is far from the reﬂector, an ellipticalone is suitable when a sound source is emitted from apoint and is near the reﬂector. However their sensitivities are not very diﬀerent from each other. Considering that a spherical concave which is widely used fora ceiling dome is applicable for use as a sound reﬂector, and that such a sound reﬂector can be embedded
into the living space as interior decoration, this paper
deals with a spherical sound reﬂector and discusses
sound concentration using it.

Fig. 4: Room with ceiling dome microphone installedceiling dome
microphone

900mm

Fig. 5: Ceiling dome microphone

3.1

System conﬁguration and outlineof speciﬁcation

The authors constructed a ceiling dome microphonewhich consists of the ceiling dome for a sound reﬂector,
a condenser microphone, a lighting ﬁxture, and a hostcomputer. Figure 4 shows a photograph of the roomwith the ceiling dome microphone installed and Fig. 5
shows a photograph of the ceiling dome microphone.
This device has two functions: indirect lighting andcollecting sound. The ceiling dome is used to reﬂect

both light and sound. The microphone is set at the
acoustic focal point of the reﬂector. The microphone
is non-directional in hemisphere and its frequency response is almost ﬂat between 30 to 20,000[Hz]. Itssensitivity is −42[dBreV/Pa]. The device can detectsound coming from a certain direction with high sensitivity while keeping the room’s appearance natural.
In our room, it is positioned above the bed to detect
breath sounds during sleep. The gain obtained by theProc. of 2000 IEEE International Conference on System, Man and Cybernetics, pp1822-1829, 2000
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ceiling dome ranges from −18 to 31 [dB] depending
on frequency of sound. The radius of curvature is775[mm] The diameter of the dome is 900[mm]. The
host computer samples output from the microphone
via an AD converter at 40[kHz].
Theoretical analysis on sound concentration caused by
the ceiling dome is described in Section 3.2.1. The
experimental results are reported in detail in Section
3.2.2.

3.2

Theoretical analysis of sound concentration due to spherical concave

3.2.1

Theory of sound concentration

ditions we used. Although we can see the acoustic
focus roughly from the ﬁgure, it is unclear whether
it is an apparent acoustic focus or the real one because this sound reﬂection model is based on geometrical acoustics. In geometrical acoustics, the phase
diﬀerence resulting from the diﬀerence in the lengthof propagation courses of the sound rays is not considered. Accordingly, we cannot discuss the eﬀect of
frequency on sound concentration. This paper analyzes sound concentration theoretically using a wave
equation.
-Vs dSdS

Ps

ξspherical reflector

spherical reflector

R
Ps

2000

sp
he
r ic
al

Φr

Rs
θ

1800

wa
ve

r1
(0,0,Zc)

1600

P
r

1400
center

[mm]

1200

z

Φ0
y

1000

x
sound source

800

Fig. 7: Model of sound reﬂection by spherical concave
600
400
200
sound source

0
-400

-200

0

200

400

[mm]
Fig. 6: Sound concentration by spherical concave
Figure 6 shows the reﬂection of a sound wave by aspherical concave. The sound source is assumed to
be a single sound source. In this ﬁgure the size of theconcave and the distance between the concave and thesound source are the same as those of the actual con-Figure 7 deﬁnes the variables that describe the reﬂector, sound source, and other points. It is assumed thatthe sound source is a single sound source and that thereﬂector is a spherical concave. The reﬂection coeﬃcient on the reﬂector is assumed to be 1.0.
In the absence of a reﬂector, the velocity potential Φ̇s
at a point Ps on the reﬂector is expressed by
U0 −jkr,(1)e
4πrwhere U0 , k and r denote the volume velocity of thesound source , the wave number of the sound wave,
and the distance of Ps from the sound source.
Then, the particle velocity V̇s at Ps becomes
Φ̇s

V̇s

=

∂ Φ̇s
∂r
U0 (1 + jkr) −jkr
e
.
r2

= −
=

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If kr  1, we may writeV̇s =jkU0 −jkr.
e4πr

In the above equation, if ∆ξ∆θ is constant, we obtain  sin θkρωU0 R2 ∆ξ∆θ(2)

If the reﬂector is placed in this sound ﬁeld and it does
not vibrate, the particle velocity V̇s becomes 0. Thismeans that the velocity potential generated by thereﬂected wave can be considered to be that generated
by the reﬂector vibrating at particle velocity −V̇s .
According to Rayleigh’s theory[5], when the only small
element dS situated at Ps vibrates at volume velocity−V̇s · dS and the rest does not vibrate, the velocity
potential caused by the element dS is expressed byV̇s e−jkr1dΦ̇r = −dS,
2πr1
where r1 denotes the distance of a point P from Ps
which is the position of the element dS. The velocity potential from the whole reﬂector is obtained byintegrating dΦ̇r . ThusΦ̇r

dΦ̇r = −=V̇s e−jkr1
dS,
2πr1

(3)

from which, by eliminating V̇s using Eq. (2), we obtainΦ̇r = −

jkU0 e−jk(r+r1 )dS.
8π 2 r · r1

Hence, the sound pressure Ṗr at P becomes
Ṗr

=
=

jωρΦ̇rkρωU0 e−jk(r+r1 )dS,
8π 2 r · r1

(4)

where ω is the angular velocity, and ρ is the densityof air. Note that r and r1 change in accordance withthe position of the element dS.
To prepare for numerical analysis, we must digitize
Eq. (4). If the position of the sound source lies in theorigin and Ps is expressed by
Ps = (Rs sin θ cos ξ, Rs sin θ sin ξ, Rs cos θ + Zc ),dS can be replaced by∆S=

R2s sin θ∆ξ∆θ,and Eq. (4) is digitized as follows.
Ṗr=kρωU0 R2s   e−jk(ri +r1i )sin θ∆ξ∆θ
8π 2
ri · r1i|Ṗr |

s

=

8π 2

(

ri · r1icos(k(ri + r1i )))2

  sin θsin(k(ri + r1i )))2 .
ri · r1i−→−−→(ri = |Ps |, r1i = |Ps P |)+((5)

Using Eq. (5), we can calculate the sound pressure
distribution by changing the position of P to ﬁnd thetheoretical acoustic focus.
3.2.2

Results of numerical analysis

Figure 8 shows the gain obtained by the ceiling dome.
The vertical axis indicates
P1
Gain = 20 log
[dB],
(6)
P0
where P1 denotes the sound pressure at an acoustic focus (0,0,1.56)[m] and P0 denotes the sound pressure at
the same position without the ceiling dome. The position of the sound source is (0,0,0)[m]. In the ﬁgure,the dots express measured values. The line expresses
theoretical values. The theoretical values were calculated using Eq. (5).
From the ﬁgure, we can see that the gain increases
gradually, and that the measured values correspondto the theoretical ones considerably although the measured values are a little less than the theoretical ones.
This means that the fundamental theory of acoustics
can be used to explain the acoustic features of a spherical sound reﬂector. The same theory would be applicable to other kinds of concave reﬂectors.
From the ﬁgure, we can see that the gain is maintainedat more than 20[dB] for high frequency sounds of morethan 6[kHz]. Since in normal breath sounds the signalto-noise ratio is high in the range of 5 to 15[kHz],the ceiling dome microphone is suitable for detecting
normal breath sounds.
Figure 9 depicts sound ﬁelds near the dome when frequency is 500[Hz] to 40[kHz]. Each sound ﬁeld issolved by numerical calculation using Eq. (5). The
vertical axis indicates the height from the center ofthe curvature of the dome. The ﬁgure shows that the
acoustic focal point moves as the frequency changes.
To be precise, in an audio region, the acoustic focal
point is not coincident to that calculated by geometrical acoustic method. However, as the frequency becomes higher, the acoustic focus becomes closer to thegeometrical acoustic focus as shown in Fig. 10. The
geometrical acoustic focus is calculated by sound ray
tracing method[4].

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800
40
theoretical value
30

z [mm]

600

Gain [dB]20
measured value

10

400

0
2000

4000

6000

8000

10000

12000

14000

16000

18000

20000

200

-10
-20

0

-30

-450

Frequency [Hz]

800

600

600

z [mm]z [mm]

Fig. 8: Gain from ceiling dome microphone (comparison between measured and theoretical values)
800

400

200

400

200

0

0
-450

0

450

-450

x [mm]

0450

x [mm]

800

600

600

z [mm]

400

400

Let us consider the calculation of the directional pattern of the dome ceiling. According to Helmholtz’s
theorem of reciprocity, the sound pressure at focal
point A ((0, 0, 1.56)[m]) given by a sound source situated at another point B is the same as the soundpressure at point B given by a sound source situated atpoint A. Therefore, to calculate the directional patternusing Eq. (5), we have only to calculate the pressure
distribution near (0,0,0) when the sound source exists in the focus. Figure 11 shows the directional pattern of the dome ceiling microphone around the soundsource situated at (0,0,0). While the ceiling dome microphone has little directivity for low frequency soundsof less than 1[kHz], it has sharp directivity for highfrequency sounds of more than 5[kHz].

200

200

0

0

0
-450

0

450

-450

0

Frequency is 2[kHz] and 5[kHz]
800

600

600

z [mm]

800

400

500 Hz1 kHz

450x [mm]

x [mm]z [mm]

Fig. 10: Sound ﬁeld solved by geometrical acoustics
methodSensitivity [dB]z [mm]

Frequency is 500[Hz] and 1[kHz]
800

450

0

x [mm]

-10

3 kHz

-20

5 kHz
-30
8 kHz

400

20 kHz

-40
200

200

0

-400 -300 -200 -1000x [mm]

450

100

200

300

400

x [mm]

0

-450

0

-450

0

450

x [mm]

Frequency is 20[kHz] and 40[kHz]Fig. 11: Theoretical value of directional patternFig. 9: Sound ﬁeld near ceiling dome when the frequency is 500[Hz] to 40[kHz]Proc. of 2000 IEEE International Conference on System, Man and Cybernetics, pp1822-1829, 2000
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Detection of Normal Breath
Sounds by Ceiling Dome Microphone

one breath
exhalation sound4 [dB]

Figure 12 shows the experimental results of detecting
normal breath sounds using the ceiling dome microphone. The experiment was conducted in an environment where the noise level is 46.5[dB(A)]. The measurement was taken at a distance of 2,040[m] from thesubject’s nose. In the ﬁgure, (a) is the integral of
the power spectra of the measured sounds from 0 to
20[kHz], (c) is the integral of the power spectra from
5 to 15[kHz], (b) is the integral of the power spectraof background noises without the ceiling dome, and(d) is the integral of the power spectra of backgroundnoises when the ceiling dome exists. The results of (a)and (c) show that the integration in the region where
the signal-to-noise ratio is high is eﬀective for detecting normal breath sounds. The results of (b) and (d)indicate the dome ceiling has an eﬀect of reducing thebackground noise level.
Figure 13 shows the experimental results of detecting
normal breath sounds when the subject is in supine,lateral, and prone positions. The top ﬁgure explainsthat normal breath sounds consist of inhalation sounds
and exhalation sounds. These ﬁgures show that it ispossible to detect normal breath sounds irrespectiveof the subject’s posture.

inhalation sound

0

10

20

30

Time [s](Supine position)

4 [dB]

40

10a) integral(0 to 20 [kHz])20

30

Time [s]4 [dB](Lateral position)b) background noise(5 to 15 [kHz],
without concentrator)

0

10

20

30

d) background noise(5 to 15 [kHz])Time [s]Fig. 12: Experimental results of breath sound detection

4 [dB]c) integral(5 to 15 [kHz])

0

10

20

30

Time [s]5Conclusion

This paper proposed a new method for detecting normal breath sounds. By frequency analysis, the au-(Prone position)
Fig. 13: Detection of breath sounds when subject isin supine, lateral, and prone positions

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thors characterized normal breath sounds in comparison with background noise: 1) Breath sounds have awide range of frequencies in the audio range, 2) Electric appliances in the home have a relatively limited
and low range of frequencies, and in many appliances,
the frequency is less than 5[kHz], and 3) the signal-tonoise ratio is high in the range of 5 to 15[kHz].
This paper introduced a ceiling dome microphone, a
new device for collecting normal breath sounds while
keeping the room’s appearance natural. From an acoustic point of view, the authors discussed its frequency
response theoretically. The fundamental results of thefrequency response showed that the ceiling dome microphone constructed by the authors can maintain again of more than 20[dB] for high-frequency sounds of
6 to 20[kHz].
Finally, the authors demonstrated their proposed method
experimentally using an actual ceiling dome microphone. The experimental results conﬁrmed the effectiveness of the method and the feasibility of thefunction in a home environment.
In future studies, applying this method to more subjects including patients to clarify diﬀerences amongindividuals is deemed necessary.

Ray Tracing Technique,” Applied Acoustics, 18,
pp449–469, 1985
[5] J.W.S. Rayleigh, The Theory of Sound, Vol. 2,
Dover Publications (New York), (original) 1877,(reprint) 1945

Acknowledgments
We would like to thank Sojun Sato of the Metrology
Fundamentals Division in the Electrotechnical Laboratory for his useful suggestions on acoustics analysis.
This study was funded in part by a Grant-in-Aid fromThe Fluidity Promotion Research System of the Science and Technology Agency of Japan.

References[1] N. Gavriely, Y. Palti, G. Alroy, “Spectral Characteristics of Normal Breath Sounds,” Journal of Applied Physiology: Respiratory, Environment andExercise Physiology, Vol. 50, No. 2, pp307-314,
1981[2] N. Gavriely, Y. Palti, G. Alroy, J.B. Grotberg,“Measurement and Theory of Wheezing Breath
Sounds,” Journal of Applied Physiology: Respiratory, Environment and Exercise Physiology, Vol.
57, No. 2, pp481–492, 1984
[3] Y. Kaneda, J. Ohga: “Adaptive Microphone-array
System for Noise Reduction,” IEEE Trans. Acoust.
Speech & Signal Process., Vol. ASSP-34, No. 6,
pp1391–1400, 1986
[4] A. Krokstad, “Algorithmic Representation of theProc. of 2000 IEEE International Conference on System, Man and Cybernetics, pp1822-1829, 2000
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