Estimation of Oxygen Desaturation by Analyzing Breath Curve

Estimation of Oxygen Desaturation by Analyzing Breath Curve
Yoshifumi Nishida, Takashi Suehiro and Shigeoki Hirai
Intelligent Systems Division, Electrotechinical Labratory

1-1-4 Umezono, Tsukuba, Ibaraki, 305-8568, Japan
Tel: +81-298-61-5156, Fax: +81-298-61-5971, E-mail: ynishida@etl.go.jp[Received October 2, 1999; accepted November 17, 1999]

Abstract
The unrestrained monitor reduces monitoring load, but
the variety of physiological value is limited. We propose a
new method for measuring oxygen desaturation frequency
by analyzing Cheyne-Stokes-like breathing curves based on
the fact that the characteristic pattern of the curve occurs
at a high probability at oxygen desaturation. We conﬁrm
the eﬀectiveness of our proposal in experiments on patientswith sleep apnea and other disorders. This proposal is applicable to any sensors that monitor breathing curves andin calculating physiological values using unrestrained monitors at home and in screenings examination at hospitals
having no special equipment.

Keywords: Non-invasive Unrestrained Monitoring, Respiration, Cheyne-Stokes Breath, Oxygen Desaturation Estimation

1

Introduction

Despite increased interest in health, means of monitoring physiological conditions are limited except at special facilities such as hospitals due to the lack of easy-tooperate, inexpensive instruments for such monitoring.
Studies to ease the monitoring load include unrestrained
monitoring using sensors embedded in environement tomonitor physiological conditions from the body surface
or externally. Monitoring using portable instruments that
do not interfere with daily life is also called unrestrained
monitor, but our deﬁnition covers techniques that do not
require attaching devices to the body. Some related studies are already commercialized. Salmi and Alihanka et al.
monitored respiration, heart rate, and body movement using piezoelectric sensors on bed under sheets[1, 2]. Tamura
et al. monitored body movement using thermal sensors on
beds[3]. Ishijima monitored electrocardiogram using electroconductive ﬁber on beds[4]. Nishida et al. developed
a pressure imaging system and proposed an imaging algorithm to monitor posture, respiration, and body movementwith the system[5]. Harada et al. proposed an imaging algorithm to calculate positions of body parts in addition toposition by comparing with templates automatically madefrom physical models of the body[6]. Watanabe et al. proposed monitoring at high accuracy pressure changes using
a microphone in air mattresses and used a single system
to monitor physiological values such as pulse, heart rate,

respiration, snoring, body movement, and cough[7]. Using visual sensors, Ishihara et al. monitored respiration[8],Nakajima et al. monitored respiration, body movement,
and pulse[9, 10], and Nishida et al. proposed diagnosing
sleep apnea, respiration, and body movement using visual sensors above beds[11]. These unrestrained monitoring overcome problems of energy supply and instrument
size by choosing optimal sensors sites and ensure freedom
by using unattached monitoring instruments and reducing
physiological and psychological loads on patients.
Thus, the study of unrestrained monitors includes varied system and process development of how to monitor
basic vital signs easily. Such study is essential but, given
physiological values, development is poor and techniques
are limited to electrocardiograms, pulse, heart rate, respiration, respiratory sound, body movement, and posture.
Study of monitoring for other physiological values is required. We propose calculating oxygen desaturation frequency by analyzing breathing curves. At present, oxygen saturation is monitored by an invasive method or noninvasive one. In the invasive method, a sensor is inserted
into blood vessels or blood is sampled by drawing. Evenin the non-invasive method, only oxyhemogblobin method
is practicable and we must attach light emitting and receiving devices to ﬁngers or toes. The latter is well developed and monitoring instruments based on this principle
are widely used in clinics and at home thanks to its easy
operation, low cost, high accuracy[12, 13]. Few studies,
however, have calculated oxygen saturation or desaturation by unrestrained monitoring.

2

Oxygen Desaturation Monitoring Principle

2.1

Oxygen Saturation

Respiration keeps oxygen and carbon dioxide in body
ﬂuids within a constant range. Tidal air is controlled byrespiratory muscles such as the diaphragm and intercostals based on the oxygen and carbon dioxide concentration
detected by some internal sensors. The sensors exist in
carotid body of the common carotid artery and central
chemosensitive area of the medulla oblongata.
Oxygen saturation (Sa O2 ) expresses the percentage ofoxyhemoglobin molecules to all hemoglobin molecules andis almost 100 % in healthy subjects. Doctors ﬁnd oxygen
saturation monitoring important physiologically to judge
whether respiration is normal. This hardly changes in s-

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2.2

Extimation of Oxygen Desaturation

2.2.1

Cheyne-Stokes-Like Breathingaal decregradu

seTidal Air
gradual increase

In sleep apnea and other disorders, respiration such as
Cheyne-Stokes breathing occurs often. Cheyne-Stokes breathing is periodic respiration in which period of excess respiration with large tidal air and apnea are repeated andtidal air gradually increases and decreases, then respiration
stops altogether, i.e., central apnea occurs (Fig. 1)[14, 15].
Figure 2 shows Cheyne-Stokes breathing observed in 3
patients with sleep apnea. The ordinate shows abdominal
movement in respiration . This is monitored by a breathing monitor described later, and by monitoring distortionof chest and abdomen. In normal respiration, tidal air andrespiratory movement are closely related. Strictly speaking, this is not Cheyne-Stokes breathing because breathing does not stop completely, but such breathing curves
often occur in patients with breathing disorders during
sleep. Cheyne-Stokes breathing should be discussed distinguished from obstructive apnea caused by upper airway
obstruction because their causes are diﬀerent. We focusedon the curve and expand the deﬁnition of Cheyne-Stokes
breathing deﬁned as respiration with ventilation or eﬀort
respiration without ventilation accompanying gradual increase and gradual decrease, or sudden increase and gradual decrease, i.e., Cheyne-Stokes-like breathing.

apnea

Time
Fig.1: Cheyne-Stokes breath

Body movement at abdomen

Estimation of Oxygen Desaturation by Analyzing Breath Curvelight variation in tidal air such as deep breathing or apnea
of about 10 seconds, but in patients with breathing disorders, a change of 30-40% may be seen.
This paper proposes a new method for estimating oxygen desaturation frequency, not the absolute oxygen saturation, by analyzing Cheyne-Stokes-like breathing deﬁned
later. Oxygen Desaturation 4% index, which means how
many times oxygen saturation falls 4% par hour, is widelyused to evaluate the seriousness of breathing disorders andshare data among researchers.

0

50

100

150

200

250

Time [s]Fig.2: Example of Cheyne-Stokes-like breath

2.2.2

Estimation of Oxygen Desaturation Frequency

We studied the relation between respiration change andCheyne-Stokes-like breathing (Fig. 3). Four representative
physiological values describe respiration: snoring, nose andmouth airﬂow, chest and abdomen movement and oxygen
saturation. We used sensors (Fig. 4) of a typical system diagnosing for breathing disorders to monitor breathing, i.e.,pressure sensors to monitor chest movement, temperature
sensors to monitor nose and mouth airﬂow, microphones tomonitor snoring, oximeters to monitor oxygen saturation,and mercury sensors to monitor posture. Figure 3 shows 1
case of apnea and 4 of Cheyne-Stokes-like breathing, whichcorrelates well with oxygen desaturation.
We found the fact that Cheyne-Stokes-like breathing
occur at high probability in oxygen desaturation as provedin the next section. Based on the fact, this paper proposesa method for estimating oxygen desaturation frequency bymeasuring Cheyne-Stokes-like breathing frequency.
2.2.3

Veriﬁcation Experiment of Monitoring Principle

To verify the eﬀectiveness of our proposal, we monitored
apnea index (AI), oxygen desaturation 4% index (ODI4),
and Cheyne-Stokes index in 34 subjects —23 men and 11
women— having a body mass index (BMI) of 25.57[Kg/m2 ],a mean age of 46.8 years, and breathing disorders of diﬀering seriousness (Fig. 5-7). AI, ODI4, and Cheyne-Stokes
index show mean frequency per hour. The correlation of
ODI4 to Cheyne-Stokes index is 0.92, that of AI to CheyneStokes index is 0.76, and that of ODI4 to AI is 0.85. These
results demonstrate high correlation among ODI4, AI, andCheyne-Stokes index. The Cheyne-Stokes index shows a

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Estimation of Oxygen Desaturation by Analyzing Breath Curve

A :Apnea
CS:Cheyne-Stokes Breath
OD:Desaturation
Snore

A

Airflow at nose
& mouthCS CS CSCS
Movement at chest& abdomen
SaO2

OD OD OD OD
0

50

100

150

200

250

Cheyne-Stokes Index

50
45
40
35
30
25
20
15
10
5

Time [s]

0
0

20

40

Fig.5:
Comparison
Cheyne-Stokes index

SaO2

Snore

PostureFig.4: Typical sensors for monitoring breath status

higher correlation to the ODI4 than to AI (Fig. 5 and 6).
The apnea index tends to be unstable in patients with slight hypoxemia (Fig. 7). Thus, no apnea does not meanno oxygen desaturation. On the other hand, the CheyneStokes index shows uniform results for patients from slightness to seriousness. That means the index can be used for
estimation of oxygen desaturation frequency and for evaluating seriousness of hypoxemia.
2.2.4

between

ODI4

and

50

60

50

Model of Cheyne-Stokes-Like Breathing

Oxygen desaturation is not caused only by obstructive apnea, but most clinical apnea is this type, so we focusedon it (Fig. 8). In a simpliﬁed obstruction of the pharynx

Cheyne-Stockes Index

Body movement

80

ODI4

Fig.3: Comparison among parameters for monitoring breath

Air flow

60

45
40
35
30
25
20
15
10
5
0

0

10

20

30

40

AI
Fig.6: Comparison between AI and Cheyne-Stokes
index

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Estimation of Oxygen Desaturation by Analyzing Breath Curve



60
V̇

=

50

AI


(2)

A,B,C, and D are constants.
Obstructive apnea is caused when the force which respiratory muscles such as diaphragm and intercostals generate for respiration (respiratory muscle force) does notcontribute to ventilation. Using work Ẇr done by respiratory muscles for 1 respiration, eq. (2) is transformed into
eqs. (3) and (4).

40
30
20


V̇ =

10
0

A
D(PCO2 − B) 1 +PO2 − C

E · Ẇr0

Fp > Fb (opening conditions of obstruction)
Fp ≤ Fb
(3)



0

20

40

60

Ẇr = F (PCO2 − B) 1 +

80

ODI4


(4)

E and F are constants.

Fig.7: Comparison between ODI4 and AI

in obstructive apnea, Pout expresses oral internal pressure
and Pin internal esophageal pressure. Pout and Pin are
equal if there is no obstruction, and diﬀer if obstruction
occurs, i.e., Pin is less than Pout at inhalation and Pin isgreater than Pout at exhalation, and the force Fp is applied
to the part where the obstruction occurs.
Fp = S(Pout − Pin )(1)

Where S represents the cross section area of the obstruction.

PoutA
PO2 − CPin

Fig.8: Model of peripheral apnea
The approximation equation (2) is satisﬁed between 1
breath tidal air V̇ (tidal air), and the partial pressure ofarterial carbon dioxide () and partial pressure of arterial
oxygen (PO2 ). This indicates that increased PCO2 anddecreased PO2 increase tidal air. Decrease PO2 greatly
intensiﬁes the eﬀect of tidal air increase by increased PCO2 .

The Cheyne-Stokes-like curve in obstructive apnea is
explained by the above equations from work by respiratory muscles. Until Fp in eq. (1) satisﬁes Fb to open the
obstruction, PO2 decreases and PCO2 increases because
ventilation does not occur (lower in eq. (3)), and workby respiratory muscles increases dramatically (eq. (4)).
When Fp > Fb is satisﬁed and the obstruction opens (upper in eq. (3)), PO2 gradually increases (see eq. (4)).
The Cheyne-Stokes-like curve monitored is a gradualdecrease after a sudden, not gradual increase(Figs. 2 and
3). The reason why a sudden increase appears instead ofa gradual increase expected from the above equations isthat the curves shown in Figs. 2 and 3 are monitored withchest and abdomen movement, not with respiratory muscle
work which is used as a variable in the above equation,
The relation between respiratory muscle work and chest
and abdomen movement are explained as follows:
1) While obstruction is occurring, negative pressure in
the chest becomes higher when a person try to inhale air.
In this situation, the force of respiratory muscles is spentdecompressing pressure in the chest and moving internalorgans, not inhaling air. The respiratory muscle work is
not reﬂected in chest and abdomen movement. As a result, chest and abdomen movement seems to increase little,
although a high respiratory muscle force is generated. Respiratory muscle work is not correlated to actually observed
movement of chest and abdomen; 2) when the obstruction
becomes unblocked, explosive inhalation occurs, observed
as sudden movement; 3) after the obstruction disappears,
respiratory muscle work and observed movement of chest
and abdomen correlate well because the force of respiratory muscles is mainly spent ventilation, and chest and abdomen movement gradually decreases depending on tidal
air.

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Estimation of Oxygen Desaturation by Analyzing Breath Curve
3.1.1 Detection of Cheyne-Stokes-like breathing
Using Pressure Sensor Bed

3

Clinical Experiment Using Pressure
Sensor Bed

3.1

Pressure Sensor Bed

Using a pressure sensor bed (Fig. 9), we studied the applicability of calculating oxygen desaturation based on the
Cheyne-Stokes-like breathing curve; 210 high molecular
thick ﬁlm devices (FSRs)(Interlink) are located at 7[cm]spacing and ,using the property that as force applied on
FSR increases, its electric resistance decreases, we obtainpressure distribution imaging of 12[bits](Fig10).

We detected respiration by the equal phase sum method.
Respiratory movement is detected by the change of weight
distribution at contacts of sleeping subjects and the bed.
When the whole body is taken as the pressure image,breathing curves cannot be accurately monitored by a simple sum of pressure due to the inﬂuence of oﬀset by thephase diﬀerence in the pressure change because the subject’s weight does not change. The equal phase sum method
enables accurate detection of respiration by appropriate
summing controlling oﬀset considering the phase diﬀerencein pressure charge[5].
Figure 11 shows an example of Cheyne-Stokes-like curveusing the equal phase sum method. The ﬁgure shows,from the top, nose and mouth airﬂow, respiratory chest
and abdomen movement, oxygen saturation, and breathing curve detected by applying the equal sum method topressure images monitored using the pressure sensor bed.
The Cheyne-Stoke-like curve is detected using the pressure
sensor bed.

Airflow at noseand mouth
Movement at chest
and abdomen
SaO2

Fig.9: Pressure Sensor Bed

Breath curveby pressure sensor
bed

0

200

400

600

800

1000

Time [s]Fig.11: Cheyne-Stokes-like breath

3.1.2

Fig.10: Pressure Image

Finding Cheyne-Stokes Index Using Pressure Sensor Bed

With a group of 16 subjects —8 men and 8 women—
composed of people of sound healthy and patients withsleep apnea, we detected the Cheyne-Stokes index by unrestrained monitoring using the pressure sensor bed andcompared the result to ODI4 detected by an apnomonitor. The mean age of the subjects is 46.7 years and BMI
24.86[Kg/m2 ](Fig. 12). A high correlation of 0.85 was
conﬁrmed between the Cheyne-Stokes index detected by
the pressure sensor bed and ODI4.
Figure 13 compares the frequency of Cheyne-Stokeslike breathing and oxygen desaturation 4% at an intervalof 10 minutes with 3 patients with disease of diﬀerent seriousness. A high correlation was conﬁrmed between the

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Estimation of Oxygen Desaturation by Analyzing Breath Curve
Cheyne-Stokes index monitored by the pressure sensor bed
Frequency of OD4
and ODI4.
Frequency of Cheyne-Stokes Breath18
16

Frequency[Times/10 min]Cheyne-Stokes Index

20

14
12
10
8
6
4
2
0
0

10

20

30

40

ODI4

20
18
16
14
12
10
8
6
4
2
0

0:00

4

Conclusions

We proposed estimating oxygen desaturation frequency byanalyzing the breathing curve detected by unrestrained
monitoring.
The principle of this method uses Cheyne-Stokes-likebreathing curves, which occur at a high probability in oxygen desaturation, and conversely by detecting the curve,
oxygen desaturation frequency is counted.
We experimented with healthy people and patients withdisease of diﬀerent seriousness, conﬁrming our proposal’s
eﬀectiveness. We studied unrestrained monitoring applying this to proposed a pressure sensor bed we have developed.
Because this proposed method is applicable to sensors
to monitor breathing curve, it is expected to be applied to
calculate physiological values by unrestrained monitoringat home and screening tests at hospitals having no special
equipment.
Themes for future discussion are: 1) clinical examination to judge whether this method is applicable to healthy
subjects, including infants and the elderly, and patientswith other diseases, because we studied only healthy people and patients with sleep apnea, and 2) improvementof the breathing curve analysis algorithm to abstract the
Cheyne-Stokes-like curve.

Acknowledgments
We thank Prof. Tetuso Ishii, Prof. Mikiko Takayama,
Ms. Takumi Yamazaki of Tokyo Woman’s Medical Col-

(a)

1:00

2:00

3:00

4:00

5:00

6:00

20
18
16
14
12
10
8
6
4
2
0

0:00

7:00

8:00

9:00

10:00

Male, 61 year-old
BMI = 23.41[Kg/m2]

(b)

1:00

2:00

3:00

4:00

5:00

6:00

20
18
16
14
12
10
8
6
4
2
0

0:00

Fig.12: Comparison of ODI4 detected by conventional sensor and Cheyne-Stokes index detected bypressure sensor bed

Female, 58 year-old
BMI = 25.96[Kg/m2]

7:00

8:00

9:00

10:00

Female, 27 year-old
BMI = 20.40[Kg/m2]

(c)

1:00

2:00

3:00

4:00

5:00

6:00

7:00

8:00

9:00

10:00

Time [Hour]Fig.13: Comparison of histogram of Oxygen desaturation 4% (OD4) detected by conventional sensor and Cheyne-Stokes-like breathing detected bypressure sensor bed

lege for cooperating in examinations. We thank AssistantProf. Soichiro Miyazaki of Akita University for providing
useful information on diagnosis. We thank Mr. Tomohisa
Yoshimi of Denso Corporation for constructing the clinicalsystem. This study was funded in part by a Grant-in-Aid
from The Fluidity Promotion Research System of The Science and Technology Agency of Japan.

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