U.S. patent application number 12/911233 was filed with the patent office on 2011-02-17 for periodic disordered breathing detection.
Invention is credited to Jonathan Kwok, Kent Lee, Zheng Lin, Yanchuan Pu.
Application Number | 20110040201 12/911233 |
Document ID | / |
Family ID | 38576324 |
Filed Date | 2011-02-17 |
United States Patent
Application |
20110040201 |
Kind Code |
A1 |
Pu; Yanchuan ; et
al. |
February 17, 2011 |
Periodic Disordered Breathing Detection
Abstract
Systems and methods are directed to evaluating breathing
disorders, such as periodic disordered breathing. A signal
representative of patient respiration is developed, typically
patient-internally. An envelope of the signal is provided.
Periodicity of the envelope is detected, and presence and severity
of periodic disordered breathing is determined based on the
periodicity of the envelope.
Inventors: |
Pu; Yanchuan; (San Diego,
CA) ; Lee; Kent; (Shoreview, MN) ; Kwok;
Jonathan; (Holmdel, NJ) ; Lin; Zheng;
(Torrance, CA) |
Correspondence
Address: |
HOLLINGSWORTH & FUNK
8500 Normandale Lake Blvd, SUITE 320
MINNEAPOLIS
MN
55437
US
|
Family ID: |
38576324 |
Appl. No.: |
12/911233 |
Filed: |
October 25, 2010 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
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11392365 |
Mar 29, 2006 |
7819816 |
|
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12911233 |
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Current U.S.
Class: |
600/529 |
Current CPC
Class: |
A61B 5/4818 20130101;
A61N 1/3601 20130101; A61B 5/0816 20130101 |
Class at
Publication: |
600/529 |
International
Class: |
A61B 5/08 20060101
A61B005/08 |
Claims
1. A system, comprising: an implantable housing; detection
circuitry provided in the housing and configured to detect a signal
representative of patient respiration; and a processor configured
to detect periodicity of an envelope of the signal and determine
presence of periodic disordered breathing based on the periodicity
of the envelope by computing a parameter characterizing envelope
cycle length for multiple envelope cycles occurring within a time
window, the parameter comprising one or both of a standard
deviation (K.sub.SD) of duration for n envelope cycles and the
predetermined duration divided by a mean (K.sub.MEAN) indicative of
average envelope cycle length, wherein n is a number.
2. The system of claim 1, wherein the processor is configured to
detect regularity of envelope periodicity.
3. The system of claim 1, wherein the processor is configured to
determine presence of periodic disordered breathing by determining
regularity of envelope periodicity and a duration of envelope
cycles occurring within the time window of predetermined
duration.
4. The system of claim 1, wherein the processor is configured to
determine a duration of envelope periodicity.
5. The system of claim 1, wherein the processor is configured to
determine envelope periodicity if the standard deviation (K.sub.SD)
is less than a first threshold and n is greater than a second
threshold.
6. The system of claim 1, wherein the processor is configured to
determine presence of periodic disordered breathing if the standard
deviation (K.sub.SD) is less than a first threshold, n is greater
than a second threshold, and K.sub.MEAN falls within a third
threshold range.
7. The system of claim 1, wherein the processor is configured to
compute an estimated apnea-hypopnea index based on the periodicity
of the envelope.
8. The system of claim 1, wherein the processor is configured to
compute an estimated apnea-hypopnea index based on a number of
periodic disordered breathing events occurring within each of a
plurality of the time windows, a total duration of the plurality of
time windows defining a duration of patient sleep.
9. The system of claim 1, wherein the processor is configured to
determine severity of the periodic disordered breathing.
10. The system of claim 1, wherein the processor is configured to
determine severity of the periodic disordered breathing at least in
part by distinguishing between central sleep apnea and obstructive
sleep apnea.
11. The system of claim 1, wherein the processor is configured to
determine severity of a patient's heart failure condition by
determining presence of the periodic disordered breathing in each
of a plurality of physiological states.
12. The system of claim 1, wherein the processor is configured to
determine severity of the periodic disordered breathing at least in
part by determining a frequency of the periodicity and a stability
of the periodicity.
13. The system of claim 1, wherein the processor is configured to
determine severity of the periodic disordered breathing at least in
part by determining a depth of a change in peaks of the
envelope.
14. A system, comprising: an implantable housing; a respiration
sensor; detection circuitry provided in the housing and coupled to
the respiration sensor, the detection circuitry configured to
detect a signal representative of patient respiration; conditioning
circuitry provided in the housing and coupled to the detection
circuitry, the conditioning circuitry configured to (a) remove a
trend or a DC component of the signal representative of patient
respiration and rectifying the signal or (b) square and low pass
filter the signal representative of patient respiration; and a
processor communicatively coupled to the conditioning circuitry,
the processor configured to detect periodicity of an envelope of
the signal and determine presence of periodic disordered breathing
based on the periodicity of the envelope.
15. The system of claim 14, wherein the processor is configured to
detect periodicity of the envelope of the signal and determine
presence of periodic disordered breathing by computing a parameter
characterizing envelope cycle length for multiple envelope cycles
occurring within a time window.
16. The system of claim 14, wherein the processor is configured to:
detect periodicity of the envelope of the signal and determine
presence of periodic disordered breathing by computing a parameter
characterizing envelope cycle length for multiple envelope cycles
occurring within a time window; and compute an estimated
apnea-hypopnea index based on a number of periodic disordered
breathing events occurring within each of a plurality of the time
windows, a total duration of the plurality of time windows defining
a duration of patient sleep.
17. The system of claim 14, wherein the processor is configured to
compute a parameter characterizing envelope cycle length for
multiple envelope cycles occurring within the time window, the
parameter comprising one or both of a standard deviation (K.sub.SD)
of duration for n envelope cycles and the predetermined duration
divided by a mean (K.sub.MEAN) indicative of average envelope cycle
length, wherein n is a number.
18. The system of claim 14, wherein the processor is configured to:
determine severity of the periodic disordered breathing at least in
part by determining a frequency of the periodicity and a stability
of the periodicity; or determine severity of the periodic
disordered breathing at least in part by determining a depth of a
change in peaks of the envelope.
19. The system of claim 14, wherein the processor is configured to
distinguish between central sleep apnea, obstructive sleep apnea,
and hypopnea.
20. A system, comprising: means for developing a signal
representative of patient respiration from within a patient; means
for detecting periodicity of an envelope of the signal; and means
for determining presence of periodic disordered breathing based on
the periodicity of the envelope by computing a parameter
characterizing envelope cycle length for multiple envelope cycles
occurring within a time window, the parameter comprising one or
both of a standard deviation (K.sub.SD) of duration for n envelope
cycles and the predetermined duration divided by a mean
(K.sub.MEAN) indicative of average envelope cycle length, wherein n
is a number.
Description
RELATED PATENT DOCUMENTS
[0001] This application is a divisional of U.S. patent application
Ser. No. 11/392,365 filed on Mar. 29, 2006, to issue as U.S. Pat.
No. 7,819,816 on Oct. 26, 2010, which is incorporated herein by
reference in its entirety.
FIELD OF THE INVENTION
[0002] The present invention relates generally to detecting the
presence of breathing disorders and, in particular, periodic
disordered breathing.
BACKGROUND OF THE INVENTION
[0003] Sleep is generally beneficial and restorative to a patient,
exerting great influence on the quality of life. The human
sleep/wake cycle generally conforms to a circadian rhythm that is
regulated by a biological clock. Regular periods of sleep enable
the body and mind to rejuvenate and rebuild. The body may perform
various tasks during sleep, such as organizing long term memory,
integrating new information, and renewing tissue and other body
structures.
[0004] Lack of sleep and/or decreased sleep quality may have a
number of causal factors including, e.g., respiratory disturbances,
nerve or muscle disorders, and emotional conditions, such as
depression and anxiety. Chronic, long-term sleep-related disorders
e.g., chronic insomnia, sleep-disordered breathing, and sleep
movement disorders may significantly affect a patient's sleep
quality and quality of life.
[0005] Sleep apnea, for example, is a fairly common breathing
disorder characterized by periods of interrupted breathing
experienced during sleep. Sleep apnea is typically classified based
on its etiology. One type of sleep apnea, denoted obstructive sleep
apnea, occurs when the patient's airway is obstructed by the
collapse of soft tissue in the rear of the throat. Central sleep
apnea is caused by a derangement of the central nervous system
control of respiration. The patient ceases to breathe when control
signals from the brain to the respiratory muscles are absent or
interrupted. Mixed apnea is a combination of the central and
obstructive apnea types. Regardless of the type of apnea, people
experiencing an apnea event stop breathing for a period of time.
The cessation of breathing may occur repeatedly during sleep,
sometimes hundreds of times a night and occasionally for a minute
or longer.
[0006] In addition to apnea, other types of disordered respiration
have been identified, including, for example, hypopnea (shallow
breathing), dyspnea (labored breathing), hyperpnea (deep
breathing), and tachypnea (rapid breathing). Combinations of the
disordered respiratory events described above have also been
observed. For example, Cheyne-Stokes respiration (CSR) is
associated with rhythmic increases and decreases in tidal volume
caused by alternating periods of hyperpnea followed by apnea and/or
hypopnea. The breathing interruptions of CSR may be associated with
central apnea, or may be obstructive in nature. CSR is frequently
observed in patients with congestive heart failure (CHF) and is
associated with an increased risk of accelerated CHF
progression.
[0007] An adequate duration and quality of sleep is required to
maintain physiological homeostasis. Untreated, sleep disorders may
have a number of adverse health and quality of life consequences
ranging from high blood pressure and other cardiovascular disorders
to cognitive impairment, headaches, degradation of social and
work-related activities, and increased risk of automobile and other
accidents.
SUMMARY OF THE INVENTION
[0008] The present invention is directed to systems and methods for
evaluating breathing disorders and, more particularly, to
determining the presence of periodic disordered breathing.
Embodiments of the invention are directed to methods that involve
developing a signal representative of patient respiration and
providing an envelope of the signal. Methods further involve
detecting periodicity of the envelope, and determining presence of
periodic disordered breathing based on the periodicity of the
envelope. One, some, or all of these processes may be performed
patient-internally, patient-externally, or a combination
thereof.
[0009] Providing the envelope of the signal may involve removing a
trend or DC component of the signal and rectifying the signal.
Providing the envelope of the signal may alternatively involve
squaring and low pass filtering the signal.
[0010] Detecting periodicity of the envelope may involve
determining regularity of envelope periodicity. According to one
approach, determining regularity of envelope periodicity involves
computing a standard deviation (K.sub.SD) of duration for n
envelope cycles occurring within a time window having a
predetermined duration. Envelope periodicity may be determined if
the standard deviation (K.sub.SD) is less than a first threshold
and n is greater than a second threshold.
[0011] Determining presence of periodic disordered breathing may
involve determining regularity of envelope periodicity and a
duration of envelope cycles occurring within a time window of
predetermined duration. Determining presence of periodic disordered
breathing may involve computing, within a time window of
predetermined duration, a mean (K.sub.MEAN) indicative of average
envelope cycle length and a standard deviation (K.sub.SD) of the
mean (K.sub.MEAN) computed for n envelope cycles occurring within
the time window. Presence of periodic disordered breathing may be
determined if the standard deviation (K.sub.SD) is less than a
first threshold, n is greater than a second threshold, and
K.sub.MEAN falls within a third threshold range.
[0012] Methods of the present invention may involve computing a
number of periodic disordered breathing events occurring within a
time window of predetermined duration by dividing the predetermined
duration by a mean (K.sub.MEAN) indicative of average envelope
cycle length. Methods may further involve computing an estimated
apnea-hypopnea index based on the number of periodic disordered
breathing events occurring within each of a plurality of the time
windows, wherein a total duration of the plurality of time windows
defines a duration of patient sleep.
[0013] Methods of the present invention may involve determining
severity of the periodic disordered breathing. For example,
determining the severity of the patient's periodic disordered
breathing may involve distinguishing between central sleep apnea
and obstructive sleep apnea (as well as considering other signals
such as blood pressure and oxygen concentration, for example).
Determining the severity or progression of congestive heart failure
(CHF) may involve determining the presence of periodic disordered
breathing in each of a plurality of physiological states, including
sleep, wakefulness with exercise, and wakefulness without exercise.
Determining the severity of the periodic disordered breathing may
also involve determining a frequency of the periodicity and/or a
stability of the periodicity. Determining the severity of the
periodic disordered breathing may involve determining a depth of a
change in peaks of the envelope (e.g., a depth of modulation of the
envelope profile or a change of modulation depth).
[0014] The signal representative of patient respiration typically
comprises a respiratory-modulated physiological signal. For
example, the signal representative of patient respiration may be a
respiratory-modulated cardiac electrical signal or a
respiratory-modulated mechanical signal.
[0015] In accordance with other embodiments, systems of the present
invention may include a housing and detection circuitry provided in
the housing and configured to detect a signal representative of
patient respiration. A processor is configured to detect
periodicity of an envelope of the signal and determine presence of
periodic disordered breathing based on the periodicity of the
envelope. In some configurations, the detection circuitry and the
processor are disposed in an implantable housing. In other
configurations, the detection circuitry is disposed in an
implantable housing and the processor is disposed in a
patient-external system. In some configurations, the detection
circuitry and processor are configured for patient-external
implementation.
[0016] The processor is configured to detect regularity of envelope
periodicity. Typically, the processor is also configured to
determining a duration of envelope periodicity. In some
configurations, the processor may be configured to compute an
estimated apnea-hypopnea index based on the periodicity of the
envelope. The processor may also be configured to determine
severity of the periodic disordered breathing.
[0017] The above summary of the present invention is not intended
to describe each embodiment or every implementation of the present
invention. Advantages and attainments, together with a more
complete understanding of the invention, will become apparent and
appreciated by referring to the following detailed description and
claims taken in conjunction with the accompanying drawings.
BRIEF DESCRIPTION OF THE DRAWINGS
[0018] FIG. 1 illustrates a method for detecting the presence of
periodic disordered breathing in accordance with embodiments of the
present invention;
[0019] FIG. 2 illustrates a method for detecting the presence of
periodic disordered breathing in accordance with embodiments of the
present invention;
[0020] FIG. 3 illustrates a method for detecting the presence of
periodic disordered breathing and computing an estimate of the
patient's apnea-hypopnea index in accordance with embodiments of
the present invention;
[0021] FIG. 4 illustrates a method for detecting the presence of
periodic disordered breathing and computing the number of apnea
events occurring within a predefined time period in accordance with
embodiments of the present invention;
[0022] FIG. 5 illustrates a method for detecting the presence of
periodic disordered breathing and computing an estimate of the
patient's apnea-hypopnea index in accordance with embodiments of
the present invention;
[0023] FIG. 6A illustrates the development of a signal envelope via
rectification and filtering of a respiratory-modulated signal in
accordance with embodiments of the present invention;
[0024] FIG. 6B illustrates a signal envelope from which periodicity
attributes are derived via analyses in accordance with embodiments
of the present invention;
[0025] FIG. 6C illustrates various processes of a periodic
disordered breathing detection methodology in accordance with
embodiments of the present invention;
[0026] FIGS. 7A-7D show raw respiration waveforms and envelopes of
same for normal and periodic breathing developed in accordance with
embodiments of the present invention;
[0027] FIGS. 7E-7F show calculated respiration envelopes for normal
and periodic breathing based on peak detection of a trans-thoracic
impedance signal;
[0028] FIG. 8 is a block diagram of a diagnostic system configured
to detect presence of periodic disordered breathing in accordance
with embodiments of the present invention; and
[0029] FIG. 9 is an illustration of a cardiac rhythm management
system that implements periodic disordered breathing diagnostics in
accordance with embodiments of the present invention.
[0030] While the invention is amenable to various modifications and
alternative forms, specifics thereof have been shown by way of
example in the drawings and will be described in detail below. It
is to be understood, however, that the intention is not to limit
the invention to the particular embodiments described. On the
contrary, the invention is intended to cover all modifications,
equivalents, and alternatives falling within the scope of the
invention as defined by the appended claims.
DETAILED DESCRIPTION OF VARIOUS EMBODIMENTS
[0031] In the following description of the illustrated embodiments,
references are made to the accompanying drawings, which form a part
hereof, and in which are shown by way of illustration, various
embodiments by which the invention may be practiced. It is to be
understood that other embodiments may be utilized, and structural
and functional changes may be made without departing from the scope
of the present invention.
[0032] An adequate quality and quantity of sleep is required to
maintain physiological homeostasis. Prolonged sleep deprivation or
periods of highly fragmented sleep ultimately will have serious
health consequences. Chronic fragmented sleep may be associated
with various cardiac or respiratory disorders affecting a patient's
health and quality of life.
[0033] By way of example, a significant percentage of patients
between 30 and 60 years experience some symptoms of disordered
breathing, primarily during periods of sleep. Sleep disordered
breathing is associated with excessive daytime sleepiness, systemic
hypertension, increased risk of stroke, angina and myocardial
infarction. Disturbed respiration can be particularly serious for
patients concurrently suffering from cardiovascular deficiencies.
Disordered breathing is particularly prevalent among congestive
heart failure patients, and may contribute to the progression of
heart failure.
[0034] Assessment of sleep is traditionally performed in a
polysomnographic sleep study at a dedicated sleep facility.
Polysomnographic studies involve acquiring sleep-related data,
including the patient's typical sleep patterns and the
physiological, environmental, contextual, emotional, and other
conditions affecting the patient during sleep. However, such
studies are costly, inconvenient to the patient, and may not
accurately represent the patient's typical sleep behavior.
[0035] Sleep assessment in a laboratory setting presents a number
of obstacles in acquiring an accurate picture of a patient's
typical sleep patterns including arousals and sleep disorders. For
example, spending a night in a sleep laboratory typically causes a
patient to experience a condition known as "first night syndrome,"
involving disrupted sleep during the first few nights in an
unfamiliar location. In addition, sleeping while instrumented and
observed may not result in a realistic perspective of the patient's
normal sleep patterns.
[0036] Among the various parameters for assessing sleep disordered
breathing (SDB), the pattern of apnea, for example, yields
important information as well as an apnea-hypopnea index (AHI)
and/or oxygen desaturation indication. For cardiovascular
consequences due to severe apnea, this pattern information may be
more relevant than the AHI value itself. Periodicity of disordered
breathing represents a pattern that, when discerned in a manner
consistent with the principles of the present invention, can be
useful for detecting apnea/hypopnea events, computing an AHI value,
discriminating between types of disordered breathing, and
determining the severity of a patient's heart failure status.
[0037] Determining the severity of a patient's heart fail status
based on periodic disordered breathing (PDB) may involve, for
example, determining presence of the PDB in each of several
physiological states, including sleep, wakefulness without
exercise, and wakefulness with exercise. Detection of periodic
disordered breathing during such physiological states can be an
indication of the relative severity of the patient's heart failure
condition. For example, detection of periodic disordered breathing
only during sleep is of concern. Detection of periodic disordered
breathing during both sleep and exercise is of greater concern.
Detection of periodic disordered breathing during sleep, exercise,
and wakefulness without exercise is of greatest concern, in
particular within the context of heart failure. In this context,
detecting the presence of periodic breathing relative to patient
state (e.g., physiological state) is a prognostic marker for heart
failure severity. For example, detecting the present of periodic
breathing during the day and in the absence of patient exercise is
indicative of a severely compromised patient condition, particular
in heart failure patients.
[0038] Severity of a patient's periodic disordered breathing can
also be assessed by determining the percentage of time (i.e.,
burden) the patient is experiencing periodic disordered breathing.
Severity may also be determined by discriminating the type of
periodic disordered breathing. For example, the envelope of the
respiration-modulated signal may be analyzed to discriminate
between obstructive sleep apnea (OSA), central sleep apnea (CSA),
and mix of OSA and CSA. Envelope amplitude and duration of envelope
fluctuation may be evaluated for discriminating between OSA and
CSA, such as in the manner described in U.S. Pat. No. 6,856,829,
which is hereby incorporated herein by reference. Severity of a
patient's periodic disordered breathing may also be determined by
determining a depth of a change in peaks of the envelope or the
frequency of envelope modulation.
[0039] Embodiments of the present invention are directed to methods
and systems for detecting the presence of periodic disordered
breathing, such as apnea, hypopnea, and Cheyne-Stokes respiration,
among others. Embodiments of the present invention employ an
implantable or partially implantable device or sensor that is
implemented to sense a respiration-modulated signal of the patient.
As is shown in FIG. 1, a signal representative of patient
respiration is developed 102 by use of such a device or sensor.
This signal is processed such that an envelope of the signal is
provided 104. The signal envelope is analyzed to detect periodicity
106, if any. Presence or absence of periodic disordered breathing
is determined 108 based on the periodicity of the envelope.
[0040] According to one approach, a raw signal of block 102 in FIG.
1 is removed from its trend and rectified to produce an envelope of
the raw signal. The envelope may also be generated by performing
peak detection of the raw signal or downsampling the signal. The
envelope, rather than the raw signal itself, is preferably used in
the analysis to determine presence or absence of periodic
disordered breathing. The envelope may be provided using analog or,
more preferably, digital signal processing. The envelope may also
be provided using an algorithmic approach as is known in the
art.
[0041] In this envelope signal, only periodic disordered breathing
will exhibit a periodic pattern, while various forms of
non-periodic breathing, such as normal respiration during rest or
exercise, single apnea events or noise, will have either a random
pattern or, theoretically, a flat envelope. Detection of envelope
periodicity may thus be used to determine the presence or absence
of periodic disordered breathing, such as various forms of apnea.
Detecting periodic disordered breathing according to the present
invention can be made robust against "respiratory noise" (i.e.,
normal breathing or electrical noise).
[0042] Further analysis of the signal envelope may reveal other
aspects of a patient's periodic disordered breathing. For example,
the total duration of the detected periodic portions of the signal
envelope having a frequency range below normal respiration
frequency can be used to estimate the patient's AHI. Also, the
frequency of the periodicity and the stability of the detected
periodic disordered breathing may also be provided as measures for
periodic disordered breathing severity. According to various
approaches, once a periodic region of the signal envelope has been
identified, respiration signal morphology and/or timings can be
applied to further differentiate whether the periodic disordered
breathing is obstructive, central or hypopnea in type.
[0043] Embodiments of the present invention may use any of a number
of different physiological signals that are modulated by patient
respiration. Suitable signals include respiratory-modulated cardiac
electrical signals and respiratory-modulated mechanical signals. By
way of example, suitable signals include ECG signals (surface,
intrathoracic, or subcutaneous non-intrathoracic), R-R intervals
(e.g., peak R modulation), P-R intervals, other conduction
intervals, QRS vector shifts as a function of respiration, systolic
time interval (STI), pulse transit time (PTT), blood pressure,
intrathoracic pressure, plural pressure, left ventricular
transmural pressure, transthoracic impedance, intra-cardiac
pressures, minute ventilation, pulse oximetery signals,
plethysmography signals, signals indicative of diaphragmatic
movement, heart movement or acceleration due to lung movement,
heart sounds, among other physiological signals that may be used as
a surrogate for respiration.
[0044] Turning now to FIG. 2, there is shown various processes for
detecting a patient's periodic disordered breathing according to
embodiments of the present invention. A signal representative of
patient respiration is developed 202, from which an envelope of the
signal is provided 204. An adjustable window having a predetermined
duration is applied 206 to the envelope. Cyclic portions of the
envelope falling within the window are detected 208, if
present.
[0045] A duration or frequency of the cyclic portions of the
envelope is determined 210. Regularity of the cyclic portions of
the envelope is determined 212. Periodic disordered breathing is
detected 214 based on the duration and regularity of the cyclic
portions of the envelope. Evaluating regularity of the patient's
disordered breathing facilitates the determination of whether or
not the disordered breathing is periodic within the context of the
adjustable window. Evaluating the duration or frequency of the
cyclic portions facilitates the determination of whether or not the
patient's respiration is characterizable as disordered breathing,
such as sleep apnea.
[0046] FIG. 3 shows various processes for detecting periodic
disordered breathing of a patient according to further embodiments
of the present invention. As in the previous figure, a signal
representative of patient respiration is developed 302, from which
an envelope of the signal is provided 304. An adjustable window
having a predetermined duration is applied 306 to the envelope, and
cyclic portions of the envelope falling within the window are
detected 308, if present. A duration/frequency and regularity of
the cyclic portions of the envelope are determined 310. Periodic
disordered breathing is detected 312 based on the duration and
regularity of the cyclic portions of the envelope.
[0047] The number of periodic disordered breathing events occurring
within the window that meet predetermined criteria is computed 314.
The window is advanced 316 and processes 302-314 are repeated 316,
thus producing a number of periodic disordered breathing events
occurring within each of a number of windows. The patient's
estimated AHI is computed 318 based on the total number of PDB
events occurring during the aggregate window duration.
[0048] According to one approach, a patient's AHI may be estimated
using a respiration-modulated signal envelope based on the
following equation:
TotalApneaDuration ( m ) 60 TST ( H ) regularity MEAN ( s ) [ 1 ]
##EQU00001##
wherein, Total Apnea Duration is measured in minutes, TST
represents the total duration of patient testing/evaluation
measured in hours, and the regularity.sub.MEAN is measured in
seconds and represents the mean duration of an apnea event, such as
about 50 seconds.
[0049] FIG. 4 shows various processes for detecting periodic
disordered breathing of a patient according to other embodiments of
the present invention. According to the embodiment of FIG. 4, and
with reference to FIG. 6A, a signal representative of patient
respiration 602, such as a trans-thoracic impedance signal (e.g.,
minute ventilation signal), is rectified 402. The signal may be
rectified using full wave rectification. The signal may
alternatively be squared and low pass filtered.
[0050] A filter window 604 of predetermined duration (e.g., 5
seconds) is applied 404 to the rectified/squared signal 606 to
produce a median value of the signal 608 within the filter window
604. The mean of the median value signal is subtracted 406 to
produce a waveform (e.g., envelope) that fluctuates around zero or
DC, such as that shown in FIG. 6B. FIG. 6C is a generalized showing
of processes that are implemented on the waveform, including
analysis 622 of the signal envelope 620 within a window 624 of
predetermined size, determination of regularity of periodic
portions of the envelope, and deciding 628 whether or not periodic
disordered breathing (e.g., apnea) has been detected.
[0051] Returning to FIG. 4, the zero-crossing points of the
waveform (e.g., envelope) are detected 408. As is discussed below,
envelope periodicity may alternatively be determined using peak
detection instead of zero-crossing detection. As is further shown
in FIG. 6B, the cycle length (k) of the waveform is determined 410
as the duration between adjacent zero-crossing points with the same
direction. This determination 410 results in the production of the
series of k(i) cycles, where i=1, 2, 3, . . . M. An adjustable
window of predetermined duration, such as 300 seconds, is applied
412 to the waveform. The duration (or frequency as the inverse of
duration) is calculated 414 as the average cycle length,
K.sub.MEAN:
K MEAN = 1 M i = 1 M K i [ 2 ] ##EQU00002##
where The regularity of the k(i) cycles is calculated as the
standard deviation, K.sub.SD:
K SD = i = 1 M ( K i - K MEAN ) 2 M - 1 [ 3 ] ##EQU00003##
where
[0052] The regularity of waveform/envelope periodicity is
determined 418 based on K.sub.MEAN, K.sub.SD, and the number of
cycles, M, in the adjustable window. For example, when M>4 and
if K.sub.SD<3 seconds, then regularity is considered high. Then,
if K.sub.MEAN is around 50 seconds, then this duration/frequency
falls within the duration/frequency range of periodic disordered
breathing, which typically ranges from about 0.02 Hz to about 0.1
Hz. A periodic pattern within the adjustable window can be
determined with 100% confidence.
[0053] Periodic disordered breathing events, such as apnea events,
can be estimated 420 by dividing the duration of the adjustable
window by the value of K.sub.MEAN. By way of example, for a 300
second adjustable window, the number of apnea events for this
window is computed as 300 sec/K.sub.MEAN.
[0054] It is noted that envelope periodicity may be determined
using peak detection instead of zero-crossing detection, which is
particularly useful for non-respiratory waveforms, such as ECG
signals. For example, and with reference to FIG. 4, a change in
slope from the negative to the positive peak of the signal envelope
is representative of respiration may be detected, and this change
would be indicative periodicity. Use of such a peak detection
approach would eliminate the need for the processes depicted in
boxes 404-408 in FIG. 4.
[0055] According to one peak detection approach, an ECG signal
modulated by respiration is detected. Peak detection is performed
on the QRS complex as the peak of the QRS complex is modulated by
respiration. An envelope may be produced based on the detected
peaks of the respiration-modulated QRS complexes in a known manner.
Changes in the slope of this envelope can be detected, from which
periodicity determinations may be made.
[0056] FIG. 5 shows various processes for computing a patient's
estimated AHI in accordance with the principles of the present
invention. In FIG. 5, it is assumed that the patient is asleep when
the analysis is conducted. Confirmation that the patient is asleep
can be accomplished in a number of ways, including use of an
activity sensor, posture sensor, REM-modulated condition sensor,
EEG sensor, or muscle atonia sensor, for example. Useful methods
and devices for detecting sleep and sleep state are described in
commonly owned U.S. Pat. No. 7,189,204 and U.S. Publication No.
2005/0043652, which are hereby incorporated herein by reference. It
is noted that methodology for calculating AHI in accordance with
the present invention is not limited to use during sleep, by may be
used at anytime, including during the day (i.e., non-sleep
times).
[0057] In a manner previously described with reference to FIG. 4, a
waveform that fluctuates around zero is produced and zero-crossing
points are determined 502. The cycle length (k) of the waveform is
determined 504 as the duration between adjacent zero-crossing
points with the same direction, thereby producing a series of k(i)
cycles, where i=1, 2, 3, . . . M.
[0058] Processing continues for the duration 506 of patient sleep.
An adjustable window of predetermined duration is applied 512 to
the waveform. The duration/frequency and regularity are calculated
514, 516 in a manner previously described. Regularity of the
envelope periodicity is determined and number of sleep disordered
breathing events is computed 518 in a manner previously described.
The adjustable window is advanced 522 by the predetermined
duration, and processes 512-522 are repeated for the duration of
patient sleep, expiration of a timer, occurrence of a predetermined
event, or reception of a termination signal. After such terminating
event, the sum of sleep disordered breathing events over the test
duration is computed 508. The patient's estimated AHI can be
computed using the sum of SDB events and total sleep duration as
follows:
SumofSDBevents 60 TotalSleepDuration ( min ) [ 4 ] ##EQU00004##
[0059] FIGS. 7A-7F are waveforms that demonstrate the efficacy of
the detection methodology of the present invention. FIG. 7A
represents a raw respiratory-modulated signal obtained from a
patient that is representative of normal breathing. In this case,
the signal shown in FIG. 7A is a respiration signal, and FIG. 7B is
a respiration signal representative of periodic disordered
breathing.
[0060] FIG. 7C is the envelope of the signal shown in FIG. 7A
developed in a manner described above. The signal envelope shown in
FIG. 7C is predominately random in character, which is indicative
of non-periodic breathing (i.e., normal breathing). FIG. 7D is the
envelope of the signal shown in FIG. 7B developed in a manner
described above.
[0061] FIGS. 7E-7F show calculated respiration envelopes for normal
and periodic breathing based on peak detection of a trans-thoracic
impedance signal. According to one peak detection approach, a
trans-thoracic impedance signal (e.g., a minute ventilation or MV
signal) is bandpassed filtered and subject to
zero-cross/peak/valley detection to produce one peak point per
breadth, which forms the envelope shown in FIG. 7E. Since apneas of
periodic disordered breathing result in a lack of respiration, to
maintain a reasonably stable sampling frequency (at .about.0.3 Hz,
the respiratory rate), zero tidal volume breaths can be added
during apneic periods at a rate similar to the preceding section of
normal respiration. This is shown in FIG. 7F.
[0062] The signal envelopes shown in FIGS. 7D and 7F exhibit
periodicity, which is the characteristic pattern of periodic
disordered breathing, such as apnea. As is discussed above,
regularity and duration/frequency analyses performed on the signal
envelopes of FIGS. 7D and 7F in accordance with the present
invention can be used to determine if the waveform is indeed
representative of periodic (i.e., regular) disordered breathing
(i.e., of a duration/frequency consistent with apnea).
[0063] According to embodiments of the present invention, a
disordered breathing diagnostic may be implemented with use of an
implantable medical device or sensor. FIG. 8 is a block diagram of
a diagnostic system 700 according to an embodiment of the present
invention. According to the embodiment shown in FIG. 8, a disorder
breathing diagnostic system 700 includes one or more implantable
sensors disposed in a bio-compatible enclosure or housing 704. The
sensor is configured to sense a physiologic parameter useful in
detecting patient respiration. Although described generally as
being implantable, it is understood that all or some of the
sensor/housing 704 may be patient-external in certain embodiments,
such that the system 700 includes no patient-internal components.
The sensor 704 is communicatively coupled to detection circuitry
702.
[0064] The detection circuitry 702 may be implantable or
patient-external. For example, the detection circuitry 702 may be
incorporated in a cardiac rhythm management or monitoring system
that incorporates a disordered breathing diagnostic. A device that
incorporates detection circuitry 702 may also be a nerve
stimulation device or a positive airway pressure device, for
example.
[0065] In one configuration, detection circuitry 702 may be
disposed in implantable housing 704 and configured to simply detect
patient respiration and telemeter respiration signals to a
patient-external system 710 for further processing. In this
embodiment, a processor 713 of the patient-external system 710
analyzes the respiration signal in a manner described herein. In a
variant implementation, the respiration signal may be processed by
a processor of a patient management network/server 718 (e.g.,
advanced patient management (APM) system) in a manner described
herein. The results of the analyses performed by the
patient-external system 710 and/or patient management network/sever
718 may be provided to a clinician (and/or the patient) via an
output device, such as a display 714 (or an output device of the
patient management network/sever 718). Features and functionality
of a patient management network/server particularly well-suited for
use in the context of the present invention are disclosed in U.S.
Pat. Nos. 6,221,011; 6,270,457; 6,277,072; 6,280,380; 6,312,378;
6,336,903; 6,358,203; 6,368,284; 6,398,728; and 6,440,066, which
are hereby incorporated herein by reference.
[0066] In another configuration, the detection circuitry 702 and
processor 712 are disposed in implantable housing 704. In this
embodiment, processor 712 of the implantable system analyzes the
respiration signal in a manner described herein. The processor 712
may determine the presence of periodic disordered breathing and
telemeter data associated with such analyses to a patient-external
system 710 (e.g., programmer, portable communicator, or bed-side
system) and/or a patient management network/system 718.
[0067] The detection circuitry 702 may further be used in
combination with therapy delivery circuitry configured to deliver
therapy to treat a patient's disordered breathing. The sensor 704
may include one or more of transthoracic impedance sensors, EEG
sensors, cardiac electrogram sensors, nerve activity sensors,
accelerometers, posture sensors, proximity sensors,
electrooculogram (EOG) sensors, photoplethysmography sensors, blood
pressure sensors, peripheral arterial tonography sensors, and/or
other sensors useful in sensing conditions associated with
respiration, sleep, and breathing disorders.
[0068] As was briefly described above, detection circuitry 702 or
processor 712 is configured to communicate with patient-external
system 710, which may be a programmer, home/bed-side system,
portable communicator or interface to a patient management
network/sever 718, such as an advanced patient management system.
The disordered breathing diagnostic system 700 shown in FIG. 8 may
be implemented in a variety of implantable or patient-external
devices and systems, including cardiac monitoring or energy
delivery devices, nerve stimulation devices, and positive airway
pressure devices, among others.
[0069] FIG. 9 is an illustration of a cardiac rhythm management
system that implements disordered breathing diagnostics in
accordance with an embodiment of the present invention. The system
800 shown in FIG. 9 may be configured to include circuitry and
functionality for periodic disordered breathing detection in
accordance with embodiments of the invention. In this illustrative
example, disordered breathing diagnostic circuitry 835 is
configured as a component of a pulse generator 805 of a cardiac
rhythm management device 800. The implantable pulse generator 805
is electrically and physically coupled to an intracardiac lead
system 810. The disordered breathing diagnostic circuitry 835 may
alternatively be implemented in a variety of implantable
monitoring, diagnostic, and/or therapeutic devices, such as an
implantable cardiac monitoring device, an implantable drug delivery
device, or an implantable neurostimulation device, for example.
[0070] Portions of the intracardiac lead system 810 are shown
inserted into the patient's heart 890. The intracardiac lead system
810 includes one or more electrodes configured to sense electrical
cardiac activity of the heart, deliver electrical stimulation to
the heart, sense the patient's transthoracic impedance, and/or
sense other physiological parameters indicative of patient
respiration. Portions of the housing 801 of the pulse generator 805
may optionally serve as a can electrode.
[0071] Communications circuitry is disposed within the housing 801,
facilitating communication between the pulse generator 805, which
includes the disordered breathing diagnostic circuitry 835, and an
external device, such as a sleep disordered breathing therapy
device, programmer, and/or APM system. The communications circuitry
can also facilitate unidirectional or bidirectional communication
with one or more implanted, external, cutaneous, or subcutaneous
physiologic or non-physiologic sensors, patient-input devices
and/or information systems.
[0072] The pulse generator 805 may optionally incorporate an
activity sensor 820 disposed in or on the housing 801 of the pulse
generator 805. The activity sensor 820 may be configured to sense
patient motion and/or posture for purposes of determining the
physiological state of the patient, such as whether the patient is
sleeping, awake but not exerting/exercising, or awake and
exerting/exercising. In one configuration, the activity sensor 820
may include an accelerometer positioned in or on the housing 801 of
the pulse generator 805. If the activity sensor 820 incorporates an
accelerometer, the accelerometer may also provide acoustic
information, e.g. rales, coughing, S1-S4 heart sounds, cardiac
murmurs, and other acoustic information.
[0073] The lead system 810 of the CRM device 800 may incorporate a
transthoracic impedance sensor that may be used to acquire the
patient's cardiac output or other physiological conditions related
to the patient's sleep disorder(s). The transthoracic impedance
sensor may include, for example, one or more intracardiac
electrodes 840, 842, 851-855, 863 positioned in one or more
chambers of the heart 890. The intracardiac electrodes 841, 842,
851-855, 861, 863 may be coupled to impedance drive/sense circuitry
830 positioned within the housing of the pulse generator 805.
[0074] The impedance signal may also be used to detect the
patient's respiration waveform and/or other physiological changes
that produce a change in impedance, including pulmonary edema,
heart size, cardiac pump function, etc. The respiratory and/or
pacemaker therapy may be altered on the basis of the patient's
heart condition as sensed by impedance.
[0075] In one implementation, the transthoracic impedance is used
to detect the patient's respiratory waveform. A voltage signal
developed at the impedance sense electrode 852 is proportional to
the patient's transthoracic impedance and represents the patient's
respiration waveform. The transthoracic impedance increases during
respiratory inspiration and decreases during respiratory
expiration. The transthoracic impedance may be used to determine
the amount of air moved in one breath, denoted the tidal volume
and/or the amount of air moved per minute, denoted the minute
ventilation.
[0076] The lead system 810 may include one or more cardiac
pace/sense electrodes 851-855 positioned in, on, or about one or
more heart chambers for sensing electrical signals from the
patient's heart 890 and/or delivering pacing pulses to the heart
890. The intracardiac sense/pace electrodes 851-855, such as those
illustrated in FIG. 8, may be used to sense and/or pace one or more
chambers of the heart, including the left ventricle, the right
ventricle, the left atrium and/or the right atrium. The lead system
810 may include one or more defibrillation electrodes 841, 842 for
delivering defibrillation/cardioversion shocks to the heart.
[0077] The pulse generator 805 may include circuitry for detecting
cardiac arrhythmias and/or for controlling pacing or defibrillation
therapy in the form of electrical stimulation pulses or shocks
delivered to the heart through the lead system 810. Disordered
breathing diagnostic circuitry 835 may be housed within the housing
801 of the pulse generator 805. The disordered breathing diagnostic
circuitry 835 may be coupled to various sensors, including the
transthoracic impedance sensor 830, activity sensor 820, EEG
sensors, cardiac electrogram sensors, nerve activity sensors,
and/or other sensors capable of sensing physiological signals
useful for sleep disorder detection.
[0078] Detection methods and systems of the present invention may
be used for diagnostic purposes and/or to alert a patient or a
clinician that periodic disordered breathing is present.
Alternatively or additionally, the detection methods and systems
may be used to form sleep disorder therapy decisions, such as by
allowing clinicians to modify or initiate sleep disorder treatment
in order to mitigate detected sleep disorders. Further, the
detection of periodic disordered breathing may also be used to
automatically initiate disordered breathing therapy to prevent or
mitigate a sleep disorder. Also, detection and measurement of
periodic breathing severity in accordance with the principles of
the present invention may be used to measure heart failure status,
such as in the manners disclosed in commonly owned U.S. Pat. No.
7,766,840, which is hereby incorporated herein by reference.
[0079] Various modifications and additions may be made to the
embodiments discussed herein without departing from the scope of
the present invention. In some configurations, for example,
implantable or partially implantable devices that sense patient
respiration and determine presence of periodic disordered breathing
may be used in combination with a patient-implantable medical
device or a patient-external medical device. In other
configurations, patient-external devices that sense patient
respiration and determine presence of periodic disordered breathing
may be used in combination with a patient-implantable medical
device or a patient-external medical device. A wide variety of
sensor and medical device configurations that provide for the
development and analysis of periodic disordered breathing data are
contemplated. Accordingly, the scope of the present invention
should not be limited by the particular embodiments described
above, but should be defined only by the claims set forth below and
equivalents thereof.
* * * * *