U.S. patent application number 15/211863 was filed with the patent office on 2016-11-10 for monitor for sids research and prevention.
The applicant listed for this patent is Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center. Invention is credited to Ruey-Kang Chang.
Application Number | 20160324466 15/211863 |
Document ID | / |
Family ID | 57222137 |
Filed Date | 2016-11-10 |
United States Patent
Application |
20160324466 |
Kind Code |
A1 |
Chang; Ruey-Kang |
November 10, 2016 |
MONITOR FOR SIDS RESEARCH AND PREVENTION
Abstract
Systems are described including a monitoring device dimensioned
for placement on a human. The monitoring device can include a
plurality of sensors for monitoring a sleep position, a
temperature, a carbon dioxide level and a respiration of the human.
The system can further including a processing unit coupled to the
monitoring device, the processing unit capable of processing
information from the plurality of sensors and performing an
algorithm to determine the presence of a sudden infant death
syndrome (SIDS) risk factor based on the information.
Inventors: |
Chang; Ruey-Kang; (Culver
City, CA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Los Angeles Biomedical Research Institute at Harbor-UCLA Medical
Center |
Torrance |
CA |
US |
|
|
Family ID: |
57222137 |
Appl. No.: |
15/211863 |
Filed: |
July 15, 2016 |
Related U.S. Patent Documents
|
|
|
|
|
|
Application
Number |
Filing Date |
Patent Number |
|
|
13957308 |
Aug 1, 2013 |
|
|
|
15211863 |
|
|
|
|
61680205 |
Aug 6, 2012 |
|
|
|
Current U.S.
Class: |
1/1 |
Current CPC
Class: |
G16H 40/67 20180101;
A61B 5/0836 20130101; A61B 5/01 20130101; A61B 5/4818 20130101;
A61B 2560/0242 20130101; A61B 5/746 20130101; A61B 5/0022 20130101;
A61B 7/003 20130101; A61B 5/11 20130101; G16H 40/63 20180101; A61B
5/4806 20130101; A61B 5/7275 20130101; A61B 2503/04 20130101; G16H
50/20 20180101 |
International
Class: |
A61B 5/00 20060101
A61B005/00; A61B 7/00 20060101 A61B007/00; A61B 5/083 20060101
A61B005/083; A61B 5/08 20060101 A61B005/08; A61B 5/11 20060101
A61B005/11; A61B 5/01 20060101 A61B005/01 |
Claims
1. A system comprising: a monitoring device dimensioned for
placement on an infant, the monitoring device having a plurality of
sensors for monitoring a sleep position, a change in the sleep
position, a temperature, a change in the temperature, a carbon
dioxide level, a change in the carbon dioxide level, a respiration,
and a change in the respiration of the infant; and a processing
unit coupled to the monitoring device, the processing unit capable
of processing information from the plurality of sensors and
performing an algorithm to identify a sequence of events, deduce a
sleep state of the infant, and determined a risk level for sudden
infant death syndrome (SIDS) based on the information.
2. The system of claim 1, wherein the carbon dioxide level sensor
optically detects the carbon dioxide level.
3. The system of claim 1, wherein the processing unit is a local
monitoring unit, the system further comprising a remote monitoring
unit.
4. The system of claim 1, further comprising: a wireless network
platform for onsite and remote monitoring.
5. The system of claim 1, wherein information from the plurality of
sensors comprises a first set of data corresponding to a first
sleep pattern of the infant and a second set of data corresponding
to a second sleep pattern of the infant, and wherein the
individualized algorithm is capable of comparing the first set of
data to the second set of data to determine a difference between
the first sleep pattern and the second sleep pattern.
6. The system of claim 1, wherein the risk level includes a low
risk, an increased risk, a moderate risk, or a high risk, wherein
the low risk is identified when the infant has a supine sleep
position, a normal body temperature, less than about 1% carbon
dioxide levels and normal airway flow; wherein the increased risk
is identified when the infant has a) a supine sleep position, a
rise of .gtoreq.0.5.degree. C. in body temperature, less than about
1% carbon dioxide levels, and normal airway flow or b) a supine
sleep position or a prone sleep position, a normal body
temperature, less than about 1% carbon dioxide levels, and normal
airway flow; wherein the moderate risk is identified when the
infant has a) a supine sleep position, a normal body temperature,
between about 1% to about 3.9% carbon dioxide levels, and normal
airway flow, b) a supine sleep position, a rise of
.gtoreq.0.5.degree. C. in body temperature, between about 1% to
about 3.9% carbon dioxide levels, and normal airway flow, c) a
supine sleep position or a prone sleep position, a normal body
temperature, between about 1% to about 3.9% carbon dioxide levels,
and normal airway flow, or d) a supine sleep position or a prone
sleep position, a rise of .gtoreq.0.5.degree. C. in body
temperature, between about 1% to about 3.9% carbon dioxide levels,
and normal airway flow; and wherein the high risk is identified
when the infant has .gtoreq.4% carbon dioxide levels.
7. The system of claim 1, wherein the processing unit is capable of
processing the information about the sleep position, the change in
the sleep position, the carbon dioxide level, the change in the
carbon dioxide level, the temperature, the change in the
temperature, the respiration, and the change in the respiration
from the plurality of sensors to create an 8-dimensional volumetric
space that characterizes the infant's sleep state and performing an
individualized algorithm using a Gaussian spheroid on the
8-dimensional volumetric space to determine the SIDS risk
level.
8. A method for monitoring a sleep environment that puts infants at
risk for sudden infant death syndrome (SIDS), the method
comprising: monitoring using a monitoring device dimensioned for
placement on an infant two or more of a sleep position, a change in
the sleep position, a respiration, a change in the respiration, a
temperature, a change in the temperature, a carbon dioxide level,
and a change in the carbon dioxide level of the infant;
automatically performing an algorithm, based on the monitoring, to
identify a sequence of events, deduce a sleep state of the infant,
and determined a risk level for SIDS; and displaying a result of
the algorithm; and sending an alert based on the risk level.
9. The method of claim 8, wherein the algorithm is an intelligent
algorithm for individualized infant sleep risk assessment.
10. The method of claim 8, further comprising: learning the
infant's sleep pattern from repeated monitoring to generate an
individualized algorithm for sleep risk assessment or determining
if a general or an individualized algorithm should be used to
determine the risk level of SIDS.
11. The method of claim 10, wherein the individualized algorithm
determines a magnitude of deviation between a first normal sleep
pattern of the infant determined by the monitoring and a second
sleep pattern of the infant determined by the monitoring.
12. The method of claim 8, wherein the algorithm classifies the
SIDS risk level as one of a low risk, increased risk, moderate
risk, high risk, or an emergency, wherein the low risk is
identified when the infant has a supine sleep position, a normal
body temperature, less than about 1% carbon dioxide levels and
normal airway flow; wherein the increased risk is identified when
the infant has a) a supine sleep position, a rise of
.gtoreq.0.5.degree. C. in body temperature, less than about 1%
carbon dioxide levels, and normal airway flow or b) a supine sleep
position or a prone sleep position, a normal body temperature, less
than about 1% carbon dioxide levels, and normal airway flow;
wherein the moderate risk is identified when the infant has a) a
supine sleep position, a normal body temperature, between about 1%
to about 3.9% carbon dioxide levels, and normal airway flow, b) a
supine sleep position, a rise of .gtoreq.0.5.degree. C. in body
temperature, between about 1% to about 3.9% carbon dioxide levels,
and normal airway flow, c) a supine sleep position or a prone sleep
position, a normal body temperature, between about 1% to about 3.9%
carbon dioxide levels, and normal airway flow, or d) a supine sleep
position or a prone sleep position, a rise of .gtoreq.0.5.degree.
C. in body temperature, between about 1% to about 3.9% carbon
dioxide levels, and normal airway flow; and wherein the high risk
is identified when the infant has .gtoreq.4% carbon dioxide
levels.
13. The method of claim 8, wherein a care provider is automatically
alerted when the SIDS risk level is classified as an emergency, the
care provider receives different alerts and recommended
interventions for different risk levels for SIDS, or the care
provider can adjust the alert to be sent to them for different
levels of risk for SIDS.
14. The method of claim 8, wherein the processing unit is capable
of processing the information about the sleep position, the change
in the sleep position, the carbon dioxide level, the change in the
carbon dioxide level, the temperature, the change in the
temperature, the respiration, and the change in the respiration
from the plurality of sensors to create an 8-dimensional volumetric
space that characterizes the infant's sleep state and performing an
individualized algorithm using a Gaussian spheroid on the
8-dimensional volumetric space to determine the SIDS risk
level.
15. An apparatus comprising: a housing dimensioned for placement
along a suprasternal notch region of an infant, the housing having
a first compartment and a second compartment; a plurality of
sensors for monitoring a sleep position, a change in the sleep
position, a temperature, a change in the temperature, a respiration
of the infant and a change in the respiration of the infant
positioned within the first compartment; a carbon dioxide sensor
for monitoring a carbon dioxide level of the infant and a change in
the carbon dioxide level of the infant positioned within the second
compartment; and a processing unit coupled to the plurality of
sensors and the carbon dioxide sensor, the processing unit capable
of processing information from the plurality of sensors and the
carbon dioxide sensor and performing an algorithm to identify a
sequence of events, deduce a sleep state of the infant, and
determined a risk level for sudden infant death syndrome (SIDS)
based on the information.
16. The apparatus of claim 15, wherein the first compartment is
separate from the second compartment.
17. The apparatus of claim 15, wherein the housing comprises a
connecting arm positioned between the first compartment and the
second compartment.
18. The apparatus of claim 15, further comprising a sensor for
monitoring an ambient temperature and a sensor for monitoring
ambient noise.
19. The apparatus of claim 15, wherein the first compartment
sensors have skin contact with the infant for sensing body
temperature and breathing sounds.
20. The apparatus of claim 15, wherein the second compartment
sensors have exposure to ambient air for sensing the CO.sub.2 level
from the infant's breathing, and ambient noise and temperature.
21. The apparatus of claim 15, wherein the risk level includes a
low risk, an increased risk, a moderate risk, or a high risk,
wherein the low risk is identified when the infant has a supine
sleep position, a normal body temperature, less than about 1%
carbon dioxide levels and normal airway flow; wherein the increased
risk is identified when the infant has a) a supine sleep position,
a rise of .gtoreq.0.5.degree. C. in body temperature, less than
about 1% carbon dioxide levels, and normal airway flow or b) a
supine sleep position or a prone sleep position, a normal body
temperature, less than about 1% carbon dioxide levels, and normal
airway flow; wherein the moderate risk is identified when the
infant has a) a supine sleep position, a normal body temperature,
between about 1% to about 3.9% carbon dioxide levels, and normal
airway flow, b) a supine sleep position, a rise of
.gtoreq.0.5.degree. C. in body temperature, between about 1% to
about 3.9% carbon dioxide levels, and normal airway flow, c) a
supine sleep position or a prone sleep position, a normal body
temperature, between about 1% to about 3.9% carbon dioxide levels,
and normal airway flow, or d) a supine sleep position or a prone
sleep position, a rise of .gtoreq.0.5.degree. C. in body
temperature, between about 1% to about 3.9% carbon dioxide levels,
and normal airway flow; and wherein the high risk is identified
when the infant has .gtoreq.4% carbon dioxide levels.
22. The apparatus of claim 15, wherein the processing unit is
capable of processing the information about the sleep position, the
change in the sleep position, the carbon dioxide level, the change
in the carbon dioxide level, the temperature, the change in the
temperature, the respiration, and the change in the respiration
from the plurality of sensors to create an 8-dimensional volumetric
space that characterizes the infant's sleep state and performing an
individualized algorithm using a Gaussian spheroid on the
8-dimensional volumetric space to determine the SIDS risk level.
Description
CROSS-REFERENCE TO RELATED APPLICATION
[0001] This application is a continuation application of U.S.
patent application Ser. No. 13/957,308, filed Aug. 1, 2013, which
claims priority to U.S. Provisional Patent Application Ser. No.
61/680,205, filed on Aug. 6, 2012, the entire disclosures of which
are hereby incorporated by reference.
FIELD
[0002] Device, system and methods for local and remote monitoring
infants, and algorithms for assessing an infant's sleep
environment. In particular, device, system and methods for
detecting sudden infant death syndrome (SIDS) risk factors.
BACKGROUND
[0003] Sudden infant death syndrome (SIDS) is one of the most
mysterious disorders in medicine. While the pathophysiologic
mechanisms of SIDS are not fully understood, many key environmental
risk factors for SIDS are known. The most important discovery has
been that the prone sleep position triples the risk for SIDS. This
discovery led to the national Back to Sleep campaign in 1994 and, a
dramatic, 58% decrease in SIDS incidence. Because SIDS commonly
occurs in apparently healthy infants, effective interventions for
SIDS will have impact on all 4.1 million infants born in the U.S.
each year.
[0004] Although the Back to Sleep campaign had tremendous initial
success, SIDS is still the leading cause of infant death beyond the
first month of life, and its incidence has not changed since 2000.
Scientific and public health communities now face two critical
barriers: (1) the roles of environmental risk factors in mechanisms
leading to SIDS remain unclear (i.e., why does Back To Sleep
work?); and (2) despite substantial resources devoted to educating
the public, >30% of U.S. infants (1.2 million) do not sleep in
the recommended supine position.
[0005] Apnea monitors have been used in infants for over 30 years.
However, these monitors of cardiorespiratory parameters have not
prevented SIDS because they target the wrong parameters.
Furthermore, changes in physiologic parameters are hard to
recognize by parents and often occur too late for intervention.
These monitors focused on only the physiologic parameters of the
infant but not the important environmental risk factors and how the
infant responds to the environmental changes. Thus, SIDS research
and prevention has encountered major obstacles and SIDS remains the
leading cause of death for infants over 1 month of age.
BRIEF DESCRIPTION OF THE DRAWINGS
[0006] The following illustration is by way of example and not by
way of limitation in the figures of the accompanying drawings in
which like references indicate like elements. It should be noted
that references to "an" or "one" embodiment in this disclosure are
not necessarily to the same embodiment, and such references mean at
least one.
[0007] FIG. 1 is a block diagram illustrating sensors implemented
within an infant monitoring device to detect the parameters of an
infant's sleep environment and an algorithm to determine the state
of an infant's sleep and the emergence of environmental risk
factors for SIDS.
[0008] FIG. 2A illustrates a top plan view of an embodiment of an
infant monitoring device.
[0009] FIG. 2B illustrates a side cross-sectional view of the
infant monitoring device of FIG. 2A.
[0010] FIG. 3A illustrates a top plan view of another embodiment of
an infant monitoring device.
[0011] FIG. 3B illustrates a side cross-sectional view of the
infant monitoring device of FIG. 3A.
[0012] FIG. 4A illustrates a perspective view of an embodiment of
an infant monitoring device.
[0013] FIG. 4B illustrates a perspective view of an embodiment of
the infant monitoring device of FIG. 4A having a cover.
[0014] FIG. 5 illustrates a schematic diagram of one embodiment of
an infant sleep environment monitoring system for local and remote
monitoring.
[0015] FIG. 6 illustrates one embodiment of an algorithm for
determining whether to monitor an infant for the presence of SIDS
risk factors using a general or individualized algorithm.
[0016] FIG. 7 illustrates one embodiment of a general algorithm for
monitoring and determining presence of SIDS risk factors, and
assigning the level of risk in order to generate local and remote
alarms.
[0017] FIG. 8 illustrates one embodiment of an individualized
"intelligent" algorithm for monitoring and determining presence of
SIDS risk factors, and assigning the level of risk in order to
generate local and remote alarms.
DETAILED DESCRIPTION
[0018] In this section we shall explain several preferred
embodiments of this invention with reference to the appended
drawings. Whenever the shapes, relative positions and other aspects
of the parts described in the embodiments are not clearly defined,
the scope of the invention is not limited only to the parts shown,
which are meant merely for the purpose of illustration. Also, while
numerous details are set forth, it is understood that some
embodiments of the invention may be practiced without these
details. In other instances, well-known structures and techniques
have not been shown in detail so as not to obscure the
understanding of this description.
[0019] A method, device and system for local and remote monitoring
of environmental risk factors for SIDS is described herein. In one
aspect, the device, system and method may be used to monitor for
SIDS risk factors in newborns and infants. The term "newborn"
generally refers to babies less than one month old, and "infants"
refers to babies under 12 months old. The method and device
described herein may be used to monitor a sleep environment of
newborns and infants and therefore may be used at home by a parent
or other infant care provider for monitoring on a daily basis.
Representatively, the sleep environment and infant may be monitored
simultaneously for SIDS risk factors, and based on such monitoring,
a diagnostic algorithm may be applied to detect a risky sleep state
of an infant and determine a risk level for SIDS occurrence.
[0020] The system therefore offers an approach to infant sleep
monitoring, in which both the infant and the infant's sleep
environment are monitored in order to detect modifiable
environmental risk factors for SIDS. Among the modifiable
environmental risk factors for SIDS, sleep position and head
covering by bedding are the two most prevalent and important
factors that can compromise an infant's airway and breathing.
Unsafe sleep position and head covering by bedding are also the
most easily correctable risk factors that can be identified and
intervened in time to avoid further deterioration that leads to
SIDS. Research has shown that SIDS rarely occurs in infants who are
in the supine position without the head covered. By keeping infants
in the supine sleep position and avoiding head covering during the
critical developmental period, it is believed based on medical
literature that SIDS incidence can be reduced by 70% or more.
Proposed mechanisms of death due to head covering include CO.sub.2
at rebreathing and heat stress, which may lead to decreased arousal
and apnea. It has been suggested that avoiding head covering can
reduce SIDS deaths by 27%. Thus, it is believed that by monitoring
CO.sub.2 levels along with the temperature of the infant, as is
provided by embodiments disclosed herein, clinically significant
head covering episodes can be detected and a care provider alerted
before SIDS occurs. This information in combination with monitoring
of risk factors of non-supine sleep position and abnormal breathing
will be important for care providers to identify risky sleep states
of infants so that appropriate interventions can be taken in time
to prevent SIDS.
[0021] To detect an infant's risky sleep environment of non-supine
sleep position and head covering by bedding, which could compromise
airway and breathing, a method and infant monitoring device using
sensors to monitor the infant and the infant's sleep environment
conditions are used. These sensors include a sleep position sensor,
a temperature sensor, a carbon dioxide sensor for head covering
episodes leading to overheating and carbon dioxide (CO.sub.2)
accumulation, and a respiration sensor to detect the airway flow.
In one embodiment, the device includes an accelerometer for
monitoring sleep position, a temperature sensor, a carbon dioxide
sensor and microphone to detect abnormal breathing. In some
embodiments, the infant monitoring device may include two
temperature sensors, one to monitor the infant's temperature and
one to monitor a temperature of the environment. The infant
monitoring device may further include an ambient noise sensor such
as a microphone to monitor environmental noises. The signal data
detected by the microphone serving as the ambient noise sensor may
be subtracted from the signal data detected by the microphone of
the respiration sensor to eliminate any ambient noise signals from
the infant breathing sound signals.
[0022] The infant sleep environment monitoring device may be part
of a monitoring system which includes a gateway at crib-side, and a
remote monitoring server. The gateway receives sensor input from
the infant monitoring device, processes the signals based on
built-in diagnostic algorithms, generates management
recommendations or alarms for care providers, and sends the data to
a remote monitoring server. As will be described below, the
integration of these sensors into a single device with algorithms
for sensor input processing can significantly improve detection of
a risky sleep environment prevent and help to prevent the
occurrence of SIDS.
[0023] In one embodiment, the monitoring device includes a first
portion and a second portion that form compartments for containing
the sensors, and a bridge connecting the first and second portions.
The first portion can be positioned on the infant so as to contact
a region of the skin at the suprasternal notch or upper chest area.
The first portion of the monitoring device can be dimensioned to
contain sensors that should be positioned near the suprasternal
notch. Representatively, the first portion can contain the sleep
position sensor, body temperature sensor, respiration sensor (e.g.
a microphone) and a microcontroller unit (MCU) with an integrated
radiofrequency (RF) transceiver. The second portion may be
dimensioned to contain all the other components of the device. Such
components may include, for example, the carbon dioxide (CO.sub.2)
sensor, an ambient temperature sensor, an ambient noise sensor such
as a microphone, a MCU with an integrated radiofrequency (RF)
transceiver, wireless transmitter, flash memory, voltage regulator
and a battery. Data from each of these sensors may be transferred
to a crib side gateway device and analyzed using the diagnostic
algorithm to determine the presence of SIDS risk factors. When the
presence of SIDS risk factors is determined, the monitoring device
or the crib side gateway may alert the care provider, for example
by sounding an alarm at a local alarm device or at personal mobile
devices. The diagnostic results may further be used to determine
management recommendations for a care provider. The management
recommendations may be displayed on a display such as a liquid
crystal display (LCD) touch screen of, for example, the gateway.
The device may be operated in a healthcare setting by, for example,
nurses, physicians, and/or nurse's assistants, at the infant's home
by the parent or other care provider, or at an infant day care
center.
[0024] In another embodiment, the monitoring device includes one
compartment that contains all the sensors, MCU, battery and all
other components.
[0025] The monitoring device will be placed on the infant's
suprasternal notch to upper chest area. Sensors including the
temperature sensor and respiration sensor will be located in the
undersurface of the device so that they have adequate skin contact
in order to provide adequate sensing of the infant's skin
temperature and airway sounds. Sensors including an ambient noise
sensor, ambient temperature sensor and CO.sub.2 sensor will be
located at the upper surface of the device so that they are exposed
to ambient sounds, temperature and CO.sub.2 level for adequate
sensing of the environment.
[0026] In one aspect, it is believed that a multi-sensor integrated
device as described herein will improve clinical care for newborns
and infants, revitalize public health efforts to reduce SIDS, and
advance scientific research in SIDS and sleep medicine. In
particular, by monitoring risk factors such as temperature and
CO.sub.2 at the same time, researchers will gain valuable data on
how thermal stress and CO.sub.2 rebreathing occur when a newborn or
infant changes position or the head becomes covered. Moreover, the
device will allow for evaluation of how these risk factors interact
with each other to produce apnea and/or SIDS. In addition, the
device includes a wireless transmission platform for
real-time--onsite and central--monitoring of the sleep states of a
large number of infants simultaneously. The platform is suitable
for large-scale deployment, due to the ease of use, low cost,
familiar consumer technology and interfacing, and data collection
at a central, secure server. The platform may also be useful in
pharmaceutical studies and vaccine trials in children who are
monitored for adverse reactions at home, as well as in sleep
research.
[0027] FIG. 1 is a block diagram illustrating the sensors that may
be integrated within the monitoring device to detect the parameters
of an infant's sleep environment and an algorithm to determine the
state of an infant's sleep and the emergence of environmental risk
factors for SIDS. In one embodiment, infant monitoring device may
include a sleep position sensor 102, a CO.sub.2 sensor 104, a body
temperature sensor 106, an ambient temperature sensor 108, a
respiration sensor 110 and an ambient noise sensor 112. Each of the
sensors may be used to monitor various parameters of the infant and
environment surrounding the infant.
[0028] Representatively, the sleep position sensor 102 may, in some
embodiments, be an accelerometer used to monitor a sleep position
of the infant as illustrated by block 114. The CO.sub.2 sensor 104
may be used to monitor a CO.sub.2 level around the nose and/or
mouth of the infant as illustrated by block 116. The body
temperature sensor 106 may, in some embodiments, be a thermistor
used to monitor a body temperature of the infant as illustrated by
block 118. The ambient temperature sensor 108 may also, in some
embodiments, be a thermistor. The ambient temperature sensor 108
may be used to monitor an ambient temperature of the infant's
environment as further illustrated by block 118. The respiration
sensor 110 may, in some embodiments, be a microphone that can
monitor the breathing sounds of the infant as illustrated by block
120. Similarly, ambient noise sensor 112 may also be a microphone,
this microphone, however, is used to monitor ambient noise as
further illustrated by block 120. The ambient noise may be
subtracted from the breathing sounds to derive acoustic signals
corresponding to the true breathing sounds of the infant.
[0029] Each of these monitoring parameters may then be used to
determine whether the infant is being exposed to an environmental
risk factor which may progress to SIDS. One such environmental risk
factor may be a prone sleep position or a side (lateral) sleep
position as illustrated by block 122. Such a risk factor is
determined from the information or data obtained by the sleep
position sensor 102. Other environmental risk factors can be
determined from the CO.sub.2 sensor 104. These risk factors may
include CO.sub.2 accumulation around the infant and/or CO.sub.2
rebreathing by the infant as illustrated by block 124. Finally, the
information obtained from the body temperature sensor 106 and/or
the ambient temperature sensor 108 may be used to determine whether
the infant is overheating and/or feverish as illustrated by block
126.
[0030] These environmental risk factors may then be used to
evaluate whether the infant is in a risky sleep state or event.
Representatively, if it is determined that the infant is in a prone
position or a side position (block 122), it may be concluded that
the infant is sleeping in an unsafe position as illustrated by
block 128. If, in combination with the unsafe sleep position (block
128), it is determined that CO.sub.2 is accumulating near the
infant and/or the infant is rebreathing CO.sub.2 (block 124), it
may be determined that the infant's face is wedged in bedding as
illustrated by block 130. This in turn, suggests that the infant's
airway may be compromised and/or apnea is occurring (block 134). An
infant with a comprised airway and/or apnea is at risk for SIDS as
illustrated by block 136. The infant should therefore be
immediately checked and a position of the infant changed to a safer
position.
[0031] Another risky sleep state or event suggested by CO.sub.2
accumulation and/or CO.sub.2 rebreathing (block 124) in combination
with overheating and/or fever (block 126) is head or face covering
by bedding as illustrated in block 132. A head or face covered by
bedding in turn suggests that the infant's airway may be
compromised and/or apnea is occurring (block 134). An infant with a
comprised airway and/or apnea is at risk for SIDS as illustrated by
block 136. The infant should therefore be immediately checked and a
position of the infant changed to a safer position.
[0032] Each of the sensors and their integration within a
monitoring device will now be described in more detail in reference
to FIGS. 2A-4B.
[0033] FIG. 2A shows a top plan view of one embodiment of a
monitoring device and FIG. 2B shows a cross-sectional side view of
the device of FIG. 2A. Monitoring device 100 may be formed by a
housing 202 that defines one or more compartments for containing
the various components of device 100. Housing 202 may be
dimensioned such that the one or more compartments may be
positioned at a suprasternal notch or upper chest area of the
infant. The suprasternal notch is chosen because it is: (1) the
center of the torso, therefore, suitable for sleep position
sensing; (2) directly over the trachea, to sense airway sounds; and
(3) very close to the nose, for sensing CO.sub.2 level in expired
air. It has been found that when infants, 1-6 months of age, sleep
face down that causes CO.sub.2 levels around the nose to rise to
3%, the CO.sub.2 level at the neck and upper chest can be detected
at 1-2%.
[0034] In one embodiment, housing 202 may include a first
compartment 204 and a second compartment 206. First compartment 204
may be dimensioned such that it can be attached to a portion of the
infant's skin at the suprasternal notch. In this aspect, first
compartment 204 can be dimensioned to contain components of device
100 that should be positioned closest to the infant's face during
monitoring. For example, first compartment 204 may be dimensioned
to contain sleep position sensor 102, respiration sensor 110 and
temperature sensor 106. First compartment 204 may also contain a
microcontroller (MCU) 210. Second compartment 206 may be
dimensioned to contain the remaining components including
components necessary for operation of device 100. For example,
second compartment 206 can contain CO.sub.2 sensor 104, ambient
noise sensor 112, ambient temperature sensor 108, battery 214, and
MCU 212. In this aspect, second compartment 206 may be larger than
first compartment 204. The compartments may, however, be the same
size or first compartment 204 may be larger than second compartment
206 depending upon the components that are to be contained therein.
The bridge between first and second compartments can be made of
rigid or flexible materials. The bridge will be used for electrical
connections to supply power to first compartment 204 from the
battery in the second compartment 206, and to transfer sensor
signals between the two compartments. In one embodiment, first
compartment 204 and second compartment 206 are in a non-planar
arrangement. During operation, first compartment 204 can be
attached to the skin at the suprasternal notch using, for example,
a layer of hypoallergenic adhesive hydrogel. When the first
compartment sensors have inadequate skin contact, such as device
misplacement or movement artifacts, an indicator light will flash
to alert the parents. Second compartment 206 can be placed on the
top of the subject's clothing and secured to the clothing by, for
example, buttons, straps or a hook and loop fastener such as
Velcro.RTM., or can be placed in a pocket or pouch that is secured
to the infant's clothing.
[0035] In the illustrated embodiment, first compartment 204 and
second compartment 206 are separate compartments attached to one
another by, for example, connecting arm 208. Connecting arm 208
provides sufficient space between the two compartments such that
first compartment 204 can be positioned at the suprasternal notch
while second compartment 206 is positioned over the subject's
clothing. In addition, connecting arm 208 can provide a conduit for
electrical connections and wiring between components within first
compartment 204 and second compartment 206. Although two separate
compartments are illustrated, it is further contemplated that more
than two compartments may be included and the compartments may be
open to one another or housing 202 may form a single compartment,
which contains each of the above-discussed components. Still
further, first compartment 204 and second compartment 206 may be
dimensioned to contain more or less of the previously discussed
components. An overall size of housing 202, including first
compartment 204 and second compartment 206, may be relatively
small, for example, from about 60 mm to about 70 mm long and from
about 30 mm to about 40 mm wide, but large enough so as not to be a
choking hazard for the infant.
[0036] Housing 202 may be a substantially rigid structure that is
made, for example, from a plastic or plastic-like material.
Alternatively, housing 202 may be a compliant structure such that
it can bend to conform to the dimensions of the surface upon which
it is attached. For example, housing 202 may be made of a fabric or
polymer material suitable for containing the sensors, such as, for
example, a neoprene material.
[0037] Each of the internal components of device 100 will now be
described in more detail. In one embodiment, sleep position sensor
102 may be any type of sensor capable of monitoring and/or
detecting movement of the subject. Representatively, sleep position
sensor 102 may be a triaxial accelerometer based on the digital
output type piezo-resistive 3-axis acceleration sensor (HAAM-372).
Such accelerometers have the range of .+-.2 g and .+-.8 g, and the
digital output minimizes noise. The accelerometer is electronically
connected to MCU 210 and passes signals thereto. The accelerometer
may include a programmable threshold detection function, such that
MCU 210 can be put to sleep and awakened by motion triggering. Any
algorithm, which may be implemented within MCU 210 or the main
processing unit, for sleep position identification based on an
accelerometer output can be used to determine the sleep position of
the subject.
[0038] Respiration sensor 110 may be any type of sensor capable of
monitoring an air flow or respiration of the subject.
Representatively, respiration sensor 110 may be an acoustic sensor
having on-board analog signal filtering which detects a respiratory
sound created when the subject inhales and exhales. For example,
respiration sensor 110 may be an electret or piezoelectric acoustic
sensor such as a microphone. In still further embodiments, a
suitable acoustic sensor may include a relatively thin MEMS type
sensor. Respiration sensor 110 is electronically connected to MCU
210 and passes signals thereto. In some embodiments, signals from
the sensor may be amplified, then passed through a low pass filter
before being recorded and digitized by MCU 210. Audio signals can
be sampled at approximately 22 Hz, slow enough to reduce power and
bandwidth requirements of device 100, while fast enough to preserve
the respiratory signature. The audio signals will be processed in a
local gateway associated with device 100, which can perform high
speed analysis and extract the signature of respiratory cycles for
further evaluation.
[0039] Temperature sensor 106 may be any type of sensor capable of
monitoring a temperature of the infant. In one embodiment,
temperature sensor 106 is a thermistor, such as the 402 medical
probe sensor from Measurement Specialties (Hampton, Va.). Typical
sensitivities for these thermistors are 0.1.degree. C. Temperature
sensor 106 should be placed in device housing 202, separate from
the main electronics to reduce thermal coupling to the circuitry of
MCU 210. Temperature sensor 106 is electronically connected to MCU
210 and passes signals thereto. Temperature sensor 106 can be
interrogated once per second, and then the collected data can be
stored in MCU 210 for reporting to, for example, the wireless
gateway.
[0040] Temperature sensor 108 may be any type of sensor capable of
monitoring a temperature of the ambient environment. Similar to
temperature sensor 106, temperature sensor 108 may be a thermistor.
Temperature sensor 108 may be electronically connected to MCU 212
and passes signals thereto. As can be seen from FIG. 2B,
temperature sensor 106 may be positioned within a portion of first
compartment 204 which faces the infant's skin while temperature
sensor 108 is positioned along a portion of second compartment 204
which faces the environment. These portions of compartments 204 and
206 may include openings 220 and 222, respectively, which allow the
sensors to monitor the temperature of the subject or the
environment directly. Openings 220, 222 may be covered by a
protective material 224, 226, respectively, that protects the
device while still allowing for heat transfer to the sensors (e.g.
a metal). Respiration sensor 110 may also be positioned near
opening 220 of first compartment 204 such that it is near the
infant's body an can detect breathing sounds through opening
220.
[0041] CO.sub.2 sensor 104 may be any type of sensor capable of
monitoring a CO.sub.2 level of the subject. CO.sub.2 sensor 104 is
electronically connected to MCU 212 and passes signals thereto. In
one embodiment, CO.sub.2 sensor 104 is an optical sensor.
Representatively, CO.sub.2 sensor 104 may be an optical sensor that
utilizes indicator dyes co-incorporated into a nanoporous matrix to
measure CO.sub.2 optically. For example, CO.sub.2 sensor may be an
optical sensor such as the EE892 Series optical sensor for OEM.
[0042] CO.sub.2 sensor 104 may be designed such that it is capable
of measuring CO.sub.2 levels between 0.25% and 4% with fast
response (in seconds) and sufficient sensitivity to detect CO.sub.2
concentration levels considered to be a SIDS risk factor.
Representatively, CO.sub.2 sensor 104 may detect CO.sub.2
concentrations in a range of from 0 to 100 mmHg with .+-.1 mmHg
accuracy and 10 second response time. CO.sub.2 sensor 104 may be
relatively small in that it has an overall volume of 1 cm.sup.3 or
less.
[0043] Although an optical CO.sub.2 sensor 104 is illustrated and
described, it is further contemplated that an electrochemical
CO.sub.2 sensor may be used as an alternative.
[0044] Ambient noise sensor 112 may be any type of sensor capable
of monitoring sounds from the ambient environment.
Representatively, ambient noise sensor 112 may be an electret or
piezoelectric acoustic sensor such as a microphone. In still
further embodiments, a suitable acoustic sensor may include a
relatively thin MEMS type sensor. Ambient noise sensor 112 is
electronically connected to MCU 212 and passes signals thereto. In
some embodiments, signals from the sensor 112 may be subtracted
from signals from the respiration sensor 110 to determine a signal
indicative of a breathing pattern of the infant, without any
ambient noise interference.
[0045] CO.sub.2 sensor 104 and ambient noise sensor 112 may be
positioned near opening 222 of second compartment 206 so that they
can monitor the desired environmental factors. The portion of
opening 222 over CO.sub.2 sensor 104 and ambient noise sensor 112
may be covered by an acoustically transparent material that allows
for air flow from the ambient environment to the sensors while
still providing a protective barrier against contaminants (e.g.
dust).
[0046] Device 100 may also include a battery 214 to provide power
to each of the sensors and MCU 210, 212 within device 100. Battery
214 may be, in some embodiments, a lithium polymer battery, which
can be custom ordered from manufacturers. Lithium polymer batteries
have high charge densities and good power densities, which are
needed for burst (peak-power) processing patterns. Such a battery
can be as lightweight as 1.2 grams with a capacity of 90 mAh at
3.7-4.2 V. Battery strength can be monitored periodically by MCU
210 or MCU 212.
[0047] FIG. 3A shows a top plan view of another embodiment of a
monitoring device and FIG. 3B shows a cross-sectional side view of
the device of FIG. 3A. In this embodiment, device 100 includes all
of the same components as described in reference to FIG. 2A and
FIG. 2B, except that in this embodiment, housing 202 includes a
single compartment 302. In this aspect, each of the sleep position
sensor 102, respiration sensor 110, temperature sensor 106,
CO.sub.2 sensor 104, ambient noise sensor 112, ambient temperature
sensor 108, and battery 214 are contained within the same
compartment. Housing 302 may also contain a single MCU 310 as
shown. It is contemplated, however, that more than one MCU may be
used, but is not required. Opening 220 and opening 222 may be
positioned on opposing sides of housing 202. Opening 220 and
opening 222 may be covered by a protective material 224, 226,
respectively, that provides a protective barrier against
contaminants (e.g. dust). Such material may be, for example, a mesh
or other similar material that protects against contaminants but
still allows for air to pass through it. In some portions of
openings 220, 222 the material may be a material that allows for
heat transfer (e.g. a metal). For example, the portions of openings
220 and 222 over temperature sensors 106 and 108, may be covered by
a metal material that protects the device while still allowing for
heat transfer to the sensors (e.g. a metal). The portions of
opening 222 over CO.sub.2 sensor 104, respiration sensor 110 and
ambient noise sensor 112 may be covered by an acoustically
transparent material that allows the sensors to detect CO.sub.2
levels and/or noises from the infant and environment.
[0048] FIG. 4A and FIG. 4B illustrate perspective views of another
embodiment of a monitoring device. FIG. 4A illustrates monitoring
device 400 with cover members 430 and 432 removed so that the
internal components can be seen more clearly.
[0049] Monitoring device 400 may be formed by a housing 202 that
defines one or more compartments for containing the various
components of device 400. Housing 202 may be dimensioned such that
the one or more compartments may be positioned at a suprasternal
notch of the subject. In one embodiment, housing 402 may include a
first compartment 404 and a second compartment 406. First
compartment 404 may be dimensioned such that it can be attached to
a portion of the subject's skin at the suprasternal notch. In this
aspect, first compartment 404 can be dimensioned to contain
components of device 400 that should be positioned closest to the
infant's face during monitoring. For example, first compartment 404
may be dimensioned to contain sleep position sensor 102,
respiration sensor 110 and temperature sensor 106, which are
identical to those previously discussed in reference to the
previous figures. Although not illustrated, an MCU may further be
contained within compartment 404.
[0050] Second compartment 406 may be dimensioned to contain the
remaining components including components necessary for operation
of device 400. For example, second compartment 406 can contain
CO.sub.2 sensor 104, temperature sensor 108 and ambient noise
sensor 108, which are identical to those previously discussed in
reference to the previous figures. Second compartment may also
contain inductor 418, voltage regulator 420, memory card 422,
battery 424, antenna 426 and MCU 428. In this aspect, second
compartment 406 may be larger than first compartment 404. The
compartments may, however, be the same size or first compartment
404 may be larger than second compartment 406 depending upon the
components that are to be contained therein. In one embodiment,
first compartment 404 and second compartment 406 are in a
non-planar arrangement. During operation, first compartment 404 can
be attached to the skin at the suprasternal notch using, for
example, a layer of hypoallergenic adhesive hydrogel. Second
compartment 406 can be placed on the top of the subject's clothing
and secured to the clothing by, for example, buttons, straps or a
hook and loop fastener such as Velcro.RTM..
[0051] In the illustrated embodiment, first compartment 404 and
second compartment 406 are separate compartments attached to one
another by, for example, connecting arm 408. Connecting arm 408
provides sufficient space between the two compartments such that
first compartment 404 can be positioned at the suprasternal notch
while second compartment 406 is positioned over the subject's
clothing. Connecting arm 408 8 is further dimensioned to provide a
conduit for wires or other components extending between components
within the first and second compartments 404, 406. An overall size
of housing 402, including first compartment 404 and second
compartment 406, may be relatively small, for example, from about
60 mm to about 70 mm long and from about 30 mm to about 40 mm
wide.
[0052] Housing 402 may be a substantially rigid structure that is
made, for example, from a plastic or plastic-like material.
Alternatively, housing 402 may be a compliant structure such that
it can bend to conform to the dimensions of the surface upon which
it is attached. For example, housing 402 may be made of a fabric or
polymer material suitable for containing the sensors, such as, for
example, a neoprene material.
[0053] As illustrated in FIG. 4B, housing 402 may further include
cover member 430 and cover member 432 that can be placed over first
compartment 404 and second compartment 406, respectively, to
enclose and protect the components contained therein. In some
embodiments, cover members 430, 432 form a water
resistant-enclosure. In this aspect, module housing 402 can be
cleaned and/or sanitized between uses. One or both of cover members
430, 432 may also be removable so that the internal components may
be removed and/or replaced as necessary.
[0054] In some embodiments, it is contemplated that device 400 may
be inductively charged using inductor 418, which may be an
inductive coil. In this aspect, monitoring device 400 can include
metallic pads, for example gold plated pads, formed on the outer
surface of housing 402, to facilitate recharging (by magnetic
connection to a recharging plate) and possibly reprogramming of the
device. Voltage regulator 420 may further be provided to control
and/or regulate an electric current used to operate one or more of
sensors 110, 112, 114 and 116.
[0055] MCU 212 may be any standard MCU, which includes, for
example, a processor core, memory, and programmable input/output
peripherals. In addition to monitoring the various operations of
device 400 (e.g., the battery strength), MCU 212 can be used to
process information obtained by one or more of sensors 102, 104,
106, 108, 110, and 112 and output such information to, for example,
the main processing unit (e.g. a computer). MCU 212 may further
include a radio. The radio may be a low power radio with a range of
approximately 10 to 50 meters at 1 mW of RF power. The radio in
conjunction with antenna 426 may be used to transmit signals to and
from device 400 as described in reference to FIG. 5.
[0056] In addition to a memory component integrated within MCU 212,
memory card 422 may be included in device 400. Memory card 422 may
be any type of electronic flash memory data storage device used for
storing digital information, e.g., information from sensors 102,
104, 106, 108, 110, and 112.
[0057] One or more of sensors 102, 104, 106, 108, 110, and 112 may
be installed on a wireless transmission platform 440. The wireless
transmission platform 440 can be used for wireless transmission of
data obtained by sensors 102, 104, 106, 108, 110, and 112 to a
remote location. Representatively, as illustrated in FIG. 4A, sleep
position sensor 102 and temperature sensor 106 can be installed on
wireless transmission platform 440.
[0058] FIG. 5 illustrates a schematic drawing of one embodiment of
a SIDS monitoring system. In this embodiment, it can be seen that
system 500 includes a wireless network platform for onsite and
remote monitoring. The wireless network may include gateway 502 by
the crib, an optional relay unit to extend the wireless range in
the home, and a remote monitoring server (RMS) 506. The local
gateway 502 communicates wirelessly with one or more of device 100
and sends data to the RMS through standard Internet connections
504. Some preprocessing is performed on the local gateway 502, and
critical alarms are sent directly to a local monitor 512 without
the need to pass through the Internet 504. The RMS 506 can be a
computer in a secure network that archives data from multiple
sources and provides the data for analysis or monitoring by remote
monitors 510, which may include a desktop computer, a portable
computer or a web-enabled smart phone. The RMS 506 can also provide
data updates to non-web cell phones as SMS or voice messages. The
gateway is responsible for receiving data from device 100 and
providing a route to the server on the Internet 504. The gateway
502 consists of a microcontroller with a built-in Ethernet
controller, a USB or Secure Digital (SD) card slot, and wireless
transceivers to communicate with the infant monitoring device. The
gateway system may be configured from a PC or may be a custom-made
gateway based on an ARM-9 network processor from ASIX84 or on the
Freescale Coldfire M52259. Alternatively, custom boards may be
constructed so that when resetting is needed, the system can boot
up in a fraction of a second, as compared to a minute on a PC.
[0059] Gateway 502 can contain the local intelligence for
generating alerts to caregivers. An algorithm (see Table 1) will be
installed in the gateway to detect "risky sleep states" (RSS's) of
the infants. In the event of an RSS, the gateway issues alerts to
the local monitor 512 (a computer or other network connected
devices) to make audio/visual alarms on site, or to the RMS
506.
[0060] It is noted that although a local gateway 502 is
illustrated, in some embodiments, the wireless transmission
platform may be a Bluetooth technology implemented within
monitoring device 100 and local gateway may be omitted 502. The
Bluetooth technology may allow for wireless transmission of data
from monitoring device 100 to a smartphone or other handheld device
capable of displaying the data locally or remotely.
[0061] Device 100 may be configured to use a low power radio to
conserve battery life and for safety considerations. The range will
be approximately 10 to 50 meters at 1 mW of RF power. If the range
of device 100 is not sufficient, relay nodes may be provided to
extend the effective range of device 100. One possibility will be
to place a relay node on the crib or in the bedroom to relay the
data to the main gateway.
[0062] RMS 506 may be a database system that is hosted by a
computer server. The purpose of RMS 506 is to receive data from the
gateway over the Internet and log the data into databases for
individual infants. In the case of a critical RSS--such as high
CO.sub.2 or apnea, the RMS will generate alerts, such as instant
messaging, text messages, phone calls with a synthesized message,
or other pre-determined forms of notification, in addition to
alarms by the gateway. Thus, the gateway 502 produces local alerts,
whereas the RMS 506 both receives alerts from the gateway (and logs
the events) and generates its own alerts. The RMS 506 can also
provide a web interface to its users and service providers. This
will give users with web browsers (including those on smart phones)
instant access to current status from anywhere. Applications (apps)
for smartphone users will be available for common operating systems
(such as iOS, Android and Windows) to gain direct access to RMS 506
and follow the monitoring of an infant in real time.
[0063] An algorithm for sleep state assessment and risky sleep
state (RSS) classification can be installed in the gateway. In the
algorithm, the cutoff points of the sensor data and risk levels are
based on current experimental studies, and these values can be
adjusted as more information becomes available. Accelerometers
detect body position by angle of rotation as a continuous variable.
However, output data will indicate one of the 3 sleep
positions--supine (face up, rotation)<45.degree., side (rotation
45.degree. to 134.degree.), and prone (face down, rotation
135.degree. to 180.degree.). The continuous variable of CO.sub.2
level will be categorized as <1%, 1-3.9%, and .gtoreq.4%. It has
been found that head covering can raise body temperature by
0.4.degree. C. Therefore, a rise in temperature of
.gtoreq.0.5.degree. C. above baseline will be considered
significant.
[0064] An "event" is defined as one of the following changes in the
infant's sleep: (1) turning from supine to the side or prone
position; (2) wedging of the face within bedding; or (3) a blanket
covering the head. An RSS is a considered a "state" of sleep,
generally following an event, with clinically significant changes
in CO.sub.2, temperature, or respiration. An event may or may not
lead to an RSS. Some events are cleared by infants (e.g. the infant
turns back to the supine position) without turning into an RSS.
[0065] SIDS risk factors may occur alone or follow a sequence, and
the interactions among risk factors can be complex. For example, an
infant rolls to the prone position, followed minutes later by a
rise in CO.sub.2. Or, after a blanket covers an infant's head, the
CO.sub.2 level rises, and the temperature also rises due to poor
heat dissipation. From the sequence of outputs of the sensors in
device 100, likely scenarios of the events and risky states are
constructed, and the risk levels associated with the scenarios
classified. In the algorithm, the sequences of events are
identified, the sleep state is deduced, and the associated risk
level for SIDS occurrence is determined. The current
classifications for the RSS risk levels are Low, Increased,
Moderate, High, and Emergency as shown in Table 1 below. This
classification system as well as the values used in the system can
be further adjusted as more research data become available.
TABLE-US-00001 TABLE 1 Five levels of RSS with probable scenarios
in the infant's sleep environment. Measures Sleep Body CO.sub.2
Airway Risk Level Position Temperature Level Flow Probable
Scenarios Low Risk Supine Normal <1% Normal Normal sleep
Increased Risk Supine Rise .gtoreq.0.5.degree. C. <1% Normal
Head covering or overheating Side or Normal <1% Normal Side or
prone sleep, Prone otherwise normal Moderate Risk Supine Normal 1%
to Normal Head covering & CO.sub.2 3.9% rebreathing Supine Rise
.gtoreq.0.5.degree. C. 1% to Normal Head covering & 3.9%
overheating Side or Normal 1% to Normal Face wedging & CO.sub.2
Prone 3.9% rebreathing Side or Rise .gtoreq.0.5.degree. C. 1% to
Normal Face wedging & head Prone 3.9% covering High Risk -- --
.gtoreq.4% Normal CO.sub.2 rebreathing risk for apnea Emergency --
-- -- NO flow Apnea
[0066] The above identified algorithm for RSS identification and
classification can be installed in the gateway, so that onsite
alerts can be generated in the event of a significant RSS.
Sequences of events can be simulated in the physiology lab, to
confirm that the sensors accurately detect the changes, and that
the algorithm correctly follows the sequence of changes that are
used to determine the risk levels.
[0067] An algorithm specifically designed for general and/or
individualized infant sleep risk assessment (ISRA) at home may
further be installed in the gateway. In particular, with respect to
an individualized algorithm, infants have different responses to
events during sleep, and the risks associated with an RSS may also
differ among infants. For example, with the head covered, some
infants keep the CO.sub.2 level under 1%, whereas other infants
have CO.sub.2 levels over 4%. Prone sleep position carries a much
higher risk for infants who do not have prone sleeping experience,
compared to infants who have such experience. Therefore, a Moderate
Risk state as classified by the general RSS algorithm, may pose a
moderate risk for one infant but a low risk for another. The ISRA
algorithm is therefore intelligent, taking into account each
infant's individual sleep patterns, so as to optimize risk
classification. Infants who are candidates for in home use can be
monitored for a period of time and then the ISRA algorithm refined
based on the monitoring for individualized risk assessment.
[0068] The ISRA algorithm can be based on a model independent
analysis and capable of mapping the likelihood of SIDS over a space
of several indicating variables. Alternatively, it can be based on
a rational common sense approach to analysis that is best described
as "deviation from normal" analysis. In this analysis an assumption
is made that the farther an infant deviates from normal sleeping
patterns, the more likely the infant is at risk (i.e., the higher
the risk) for SIDS.
[0069] The ISRA algorithm is based on eight variables: sleep
position, CO.sub.2 level, temperature, and respiration, and the
time derivatives of these 4 variables (i.e., how quickly they
change). These 8 variables are used to form an 8-dimensional
volumetric space that characterizes the infant's sleep state.
[0070] Representatively, a normalcy map such as a Gaussian spheroid
("normal" distribution) in accordance with the ISRA algorithm may
be used to evaluate infant risks. The normalcy map may include a
"normal" region of space which is the region having a relatively
high probability that the infant will be in this portion of the
space at any time. This is based on previously collected data for
the particular infant. The normal region is therefore considered
normal for the particular infant and does not pose a risk.
[0071] A probability distribution function is determined for the
infant based on the historical data. When the infant enters a sleep
state that is in a low probability section of the map, e.g., a "far
from normal" region, then this is considered a "deviation from
normal," and an alarm is set to warn the caregiver. Data analysis
will be used to determine the shape of the "normal" region of
space, which is the region with the most data. The regions outside
of the normal region are considered risky, with those regions
farthest from the normal region being the most risky and regions
closer being the least risky.
[0072] Although a Gaussian spheroid ("normal" distribution) is
described, it is contemplated that any type of distribution may be
used that is found sufficient to identify trends based on collected
data. Once the probability function has been determined, a maximum
likelihood fitting procedure is used to match the most likely
function shape to the data. This allows for a probability map over
the "space" of the infant's sleep, to identify conditions that
significantly deviate from normal.
[0073] It is contemplated that once the initial data specific to an
infant has been collected, the fitting and mapping procedures will
be automated for that infant. This will allow individualized maps
to be prepared so that alarms for risky states will be specific to
the sleep patterns of each individual infant. Representatively, in
one embodiment, the individualized algorithm for sleep risk
assessment may be based on a magnitude of deviation from a normal
sleep pattern of the infant from ranges and distribution
measurements obtained during a previous monitoring operation. The
normal sleep pattern ranges and distribution measurements for the
individualized algorithm may take into account parameters such as
sleep position, body temperature, carbon dioxide levels,
respiration sounds and time derivatives (rate of changes) of the
parameters.
[0074] FIG. 6 illustrates a flow chart of one embodiment of an
algorithm for determining whether to use a general or
individualized (intelligent) sleep risk assessment algorithm with a
particular infant. The determining algorithm 600 includes
determining whether the infant is to use the SIDS monitoring device
for sleep monitoring (block 602). If the device (e.g. monitoring
device 100 or 400) is to be used, the next step is to determine
whether the infant has been monitored before (block 604). If the
answer is yes, the system evaluates whether adequate sleep data is
available from that infant for generating the individualized
algorithm (block 606). If there is sufficient data, it is
determined that the individualized algorithm for RSS and alarms
should be used with that particular infant (block 608). If, on the
other hand, the infant has not been monitored before or there is
insufficient data to generate an individualized algorithm for that
infant, the general algorithm for RSS and alarms should be used
(block 610). Sleep data can then be collected for the infant so
that an individualized algorithm can be constructed (block
612).
[0075] FIG. 7 illustrates a flow chart of one embodiment of a
system for monitoring an infant for SIDS risk factors according to
the general algorithm. System 700 may include sensors 702. Sensors
702 may be any one or more of the previously discussed sensors 102,
104, 106, 108, 110 and/or 112. System 700 may monitor an input from
any one or more of the sensors (block 704). The input may be
monitored to detect any input data outside of a pre-defined
non-risky parameter range (block 706). If data outside of the
pre-defined parameter range is detected, the system automatically
performs the general algorithm to determine the presence of SIDS
risk factors, RSS and events (block 708). If a significant risk for
SIDS is detected (block 710), the results are displayed and an
alarm is activated, for example, at the local monitor alarm at the
crib side. The remote monitoring server (RMS) can then send the
alarm to the remote monitor (block 712). If, on the other hand, it
is determined that there is not a significant risk for SIDS, the
system continues monitoring sensor input (block 714).
[0076] FIG. 8 illustrates a flow chart of one embodiment of a
system for monitoring an infant for SIDS risk factors according to
an individualized algorithm. System 800 may include sensors 802.
Sensors 802 may be any one or more of the previously discussed
sensors 102, 104, 106, 108, 110 and/or 112. System 800 may monitor
an input from any one or more of the sensors and "learn" the normal
ranges of sensor readings for the infant (block 804). The input may
be monitored to detect any input data outside of a "normal range"
for the infant (block 806). For example, information from any of
the previously discussed sensors may be characterized as a first
set of data corresponding to a first sleep pattern of the infant
and a second set of data corresponding to a second sleep pattern of
the infant. The individualized algorithm is then capable of
comparing the first set of data to the second set of data to
determine a difference between the first sleep pattern and the
second sleep pattern to determine if the infant is at risk for
SIDS. The magnitude and rate of changes in the out of range
parameters are evaluated (block 808). The system then automatically
performs the individualized algorithm to determine the presence of
SIDS risk factor(s) and risk level associated with the sleep state
of the infant (block 810). If a significant risk for SIDS is
detected (block 812), the results are displayed and an alarm or
other suitable alert is activated, for example, the local monitor
alarm at the crib side. The remote monitoring server (RMS) can then
send the alarm to the remote monitor (block 814). If, on the other
hand, it is determined that there is not a significant risk for
SIDS, the system continues monitoring sensor input (block 816).
[0077] Although specific algorithms are described in reference to
FIG. 7 and FIG. 8, it is contemplated that based on the monitoring,
the system may automatically perform any of the above-discussed
algorithms to determine the presence of a SIDS risk factor. In one
embodiment, the results may be displayed by the system. For
example, the results may be displayed in an LCD display screen of
an associated main processing unit such as a computer. In one
embodiment, the algorithm performed by the system may include
determining a sequence of events indicating a change in the
subject's sleep state and determining a risk level for SIDS
occurrence based on the subject's sleep state. Determining the risk
level for SIDS occurrence may include classifying a detected SIDS
risk factor, or a combination of SIDS risk factors, as a low risk,
an increased risk, a moderate risk, a high risk or an emergency.
The care provider may be automatically alerted by the system when
the SIDS risk factor is classified as an emergency.
[0078] A device, such as RMS 506 or other main processing unit, for
performing the operations herein may be specially constructed for
the required purposes or it may comprise a general purpose computer
selectively activated or reconfigured by a computer program stored
in the computer. Such a computer program may be stored in a
computer readable storage medium, such as, but not limited to, any
type of disk including floppy disks, optical disks, CD-ROMs and
magnetic-optical disks, read-only memories (ROMs), random access
memories (RAMs), EPROMs, EEPROMs, magnetic or optical cards, Flash
memory devices including universal serial bus (USB) storage devices
(e.g., USB key devices) or any type of media suitable for storing
electronic instructions, each of which may be coupled to a computer
system bus.
[0079] The algorithms and displays presented herein are not
inherently related to any particular computer or other apparatus.
Various general purpose systems may be used with programs in
accordance with the teachings herein or it may prove convenient to
construct a more specialized device to perform the described
method. In addition, the invention is not described with reference
to any particular programming language. It will be appreciated that
a variety of programming languages may be used to implement the
teachings of the invention as described herein.
[0080] A computer readable medium includes any mechanism for
storing information in a form readable by a computer. For example,
a computer readable medium includes read only memory ("ROM"),
random access memory ("RAM"), magnetic disk storage media; optical
storage media, flash memory devices or other type of
machine-accessible storage media.
[0081] In the preceding detailed description, specific embodiments
are described. It will, however, be evident that various
modifications and changes may be made thereto without departing
from the broader spirit and scope of the claims. The specification
and drawings are, accordingly, to be regarded in an illustrative
rather than restrictive sense.
* * * * *