USRE47218E1 - Adaptive alarm system - Google Patents

Abstract

Systems and electronic processes for reducing electronic alarms in a medical patient monitoring system. For example, a system for reducing electronic alarms can include an optical sensor and one or more hardware processors in electronic communication with the optical sensor. The one or more hardware processors can be programmed to measure oxygen saturation values of a patient over a first period of time, determine if at least one oxygen saturation value obtained over the first period of time exceeds a first alarm threshold, determine whether a first alarm should be triggered based on the determination that the at least one oxygen saturation value obtained over the first period of time exceeds the first alarm threshold, determine a second alarm threshold to be applied during a second period of time subsequent to the first period of time, the second alarm threshold replacing the first alarm threshold.

Description

PRIORITY CLAIM TO RELATED PROVISIONAL APPLICATIONS

The present application claims priority benefit under 35 U.S.C. §119(e) to This is an application for reissue of U.S. Pat. No. 9,775,570, issued on Oct. 3, 2017 and titled “Adaptive Alarm System,” which is a continuation of U.S. patent application Ser. No. 13/037,184, filed Feb. 18, 2011 titled Adaptive Alarm System; which claims priority benefit under 35 U.S.C. § 119(e) to Provisional Patent Application Ser. No. 61/309,419, filed Mar. 1, 2010 titled Adaptive Threshold Alarm System; and U.S. Provisional Patent Application Ser. No. 61/328,630, filed Apr. 27, 2010 titled Adaptive Alarm System; all of the above-cited provisional patent applications are hereby incorporated by reference herein. More than one reissue application has been filed for the reissue of Pat. No. 9,775,570. The reissue applications are application Nos. 15/881,602 (the present application) and 16/184,908.

BACKGROUND OF THE INVENTION

Pulse oximetry systems for measuring constituents of circulating blood have gained rapid acceptance in a wide variety of medical applications, including surgical wards, intensive care and neonatal units, general wards, home care, physical training, and virtually all types of monitoring scenarios. A pulse oximetry system generally includes an optical sensor applied to a patient, a monitor for processing sensor signals and displaying results and a patient cable electrically interconnecting the sensor and the monitor. A pulse oximetry sensor has light emitting diodes (LEDs), typically one emitting a red wavelength and one emitting an infrared (IR) wavelength, and a photodiode detector. The emitters and detector are typically attached to a finger, and the patient cable transmits drive signals to these emitters from the monitor. The emitters respond to the drive signals to transmit light into the fleshy fingertip tissue. The detector generates a signal responsive to the emitted light after attenuation by pulsatile blood flow within the fingertip. The patient cable transmits the detector signal to the monitor, which processes the signal to provide a numerical readout of physiological parameters such as oxygen saturation (SpO₂) and pulse rate.

SUMMARY OF THE INVENTION

Conventional pulse oximetry assumes that arterial blood is the only pulsatile blood flow in the measurement site. During patient motion, venous blood also moves, which causes errors in conventional pulse oximetry. Advanced pulse oximetry processes the venous blood signal so as to report true arterial oxygen saturation and pulse rate under conditions of patient movement. Advanced pulse oximetry also functions under conditions of low perfusion (small signal amplitude), intense ambient light (artificial or sunlight) and electrosurgical instrument interference, which are scenarios where conventional pulse oximetry tends to fail.

Advanced pulse oximetry is described in at least U.S. Pat. Nos. 6,770,028; 6,658,276; 6,157,850; 6,002,952; 5,769,785 and 5,758,644, which are assigned to Masimo Corporation (“Masimo”) of Irvine, Calif. and are incorporated by reference herein. Corresponding low noise optical sensors are disclosed in at least U.S. Pat. Nos. 6,985,764; 6,813,511; 6,792,300; 6,256,523; 6,088,607; 5,782,757 and 5,638,818, which are also assigned to Masimo and are also incorporated by reference herein. Advanced pulse oximetry systems including Masimo SET® low noise optical sensors and read through motion pulse oximetry monitors for measuring SpO₂, pulse rate (PR) and perfusion index (PI) are available from Masimo. Optical sensors include any of Masimo LNOP®, LNCS®, SofTouch™ and Blue™ adhesive or reusable sensors. Pulse oximetry monitors include any of Masimo Rad-8®, Rad-5®, Rad®-5v or SatShare® monitors.

Advanced blood parameter measurement systems are described in at least U.S. Pat. No. 7,647,083, filed Mar. 1, 2006, titled Multiple Wavelength Sensor Equalization; U.S. Pat. No. 7,729,733, filed Mar. 1, 2006, titled Configurable Physiological Measurement System; U.S. Pat. Pub. No. 2006/0211925, filed Mar. 1, 2006, titled Physiological Parameter Confidence Measure and U.S. Pat. Pub. No. 2006/0238358, filed Mar. 1, 2006, titled Noninvasive Multi-Parameter Patient Monitor, all assigned to Masimo Laboratories, Irvine, Calif. (Masimo Labs) and all incorporated by reference herein. An advanced parameter measurement system that includes acoustic monitoring is described in U.S. Pat. Pub. No. 2010/0274099, filed Dec. 21, 2009, titled Acoustic Sensor Assembly, assigned to Masimo and incorporated by reference herein.

Advanced blood parameter measurement systems include Masimo Rainbow® SET, which provides measurements in addition to SpO₂, such as total hemoglobin (SpHb™) oxygen content (SpOC™), methemoglobin (SpMet®), carboxyhemoglobin (SpCO®) and PVI®. Advanced blood parameter sensors include Masimo Rainbow® adhesive, ReSposable™ and reusable sensors. Advanced blood parameter monitors include Masimo Radical-7™, Rad-87™ and Rad-57™ monitors, all available from Masimo. Advanced parameter measurement systems may also include acoustic monitoring such as acoustic respiration rate (RRa™) using a Rainbow Acoustic Sensor™ and Rad-87™ monitor, available from Masimo. Such advanced pulse oximeters, low noise sensors and advanced physiological parameter measurement systems have also gained rapid acceptance in a wide variety of medical applications, including surgical wards, intensive care and neonatal units, general wards, home care, physical training, and virtually all types of monitoring scenarios.

FIGS. 1-3 illustrate problems and issues associated with physiological parameter measurement systems having fixed threshold alarm schemas.FIG. 1 illustrates a lower-limit, fixed-threshold alarm schema with respect to an oxygen saturation (SpO₂) parameter. Two alarm thresholds, D_L(delay) and ND_L(no delay), are defined. If oxygen saturation falls below D_Lfor a time delay greater than TD, an alarm is triggered. If oxygen saturation falls below ND_Lan alarm is immediately triggered.D_L120 is typically set around or somewhat above 90% oxygen saturation andND_L130 is typically set at 5% to 10% below D_L. For example, say a person'soxygen saturation110 drops belowD_L120 at t=t₁162 and stays below D_Lfor at least atime delay TD163. This triggers adelayed alarm140 at t=t₂164, where t₂=t₁+TD. Thealarm140 remains active untiloxygen saturation110 rises aboveD_L120 at t=t₃166. As another example, say thatoxygen saturation110 then drops belowND_L130, which triggers animmediate alarm150 at t=t4168. Thealarm150 remains active untiloxygen saturation110 rises aboveD_L120 at t=t₅169.

FIG. 2 illustrates an upper-limit, fixed-threshold alarm schema with respect to an oxygen saturation (SpO₂) parameter. This alarm scenario is particularly applicable to the avoidance of ROP (retinopathy of prematurity). Again, two alarm thresholds, D_U(delay) and ND_U(no delay), are defined.D_U220 might be set at or around 85% oxygen saturation andND_U230 might be set at or around 90% oxygen saturation. For example, a neonate'soxygen saturation210 rises aboveD_U220 at t=t₁262 and stays above D_Ufor at least atime delay TD263. This triggers adelayed alarm240 at t=t₂264, where t₂=t₁+TD. Thealarm240 remains active untiloxygen saturation210 falls belowD_U220 at t=t₃166.Oxygen saturation210 then rises aboveND_U230, which triggers animmediate alarm250 at t=t₄268. Thealarm250 remains active untiloxygen saturation210 falls belowD_U220 at t=t₅269.

FIG. 3 illustrates a baseline drift problem with the fixed threshold alarm schema described above. A person's oxygen saturation is plotted on an oxygen saturation (SpO₂) versustime graph300. In particular, during a firsttime interval T₁362, a person has anoxygen saturation310 with a relatively stable “baseline”312 punctuated by a shallow,transient desaturation event314. This scenario may occur after the person has been on oxygen so that baseline oxygen saturation is near 100%. Accordingly, with a fixedthreshold alarm330 set at, say, 90%, thetransient event314 does not trigger a nuisance alarm. However, the effects of oxygen treatments wear off over time and oxygen saturation levels drift downward350. In particular, during a secondtime interval T₂364, a person has anoxygen saturation320 with a relativelystable baseline322. Thelater baseline322 is established at a substantially lower oxygen saturation than theearlier baseline312. In this scenario, a shallow,transient desaturation event324 now exceeds thealarm threshold330 and results in a nuisance alarm. After many such nuisance alarms, a caregiver may lower thealarm threshold330 to unsafe levels or turn off alarms altogether, significantly hampering the effectiveness of monitoring oxygen saturation.

A fixed threshold alarm schema is described above with respect to an oxygen saturation parameter, such as derived from a pulse oximeter. However, problematic fixed threshold alarm behavior may be exhibited in a variety of parameter measurement systems that calculate physiological parameters related to circulatory, respiratory, neurological, gastrointestinal, urinary, immune, musculoskeletal, endocrine or reproductive systems, such as the circulatory and respiratory parameters cited above, as but a few examples.

An adaptive alarm system, as described in detail below, advantageously provides an adaptive threshold alarm to solve false alarm and missed true alarm problems associated with baseline drift among other issues. For example, for a lower limit embodiment, an adaptive alarm system adjusts an alarm threshold downwards when a parameter baseline is established at lower values. Likewise, for an upper limit embodiment, the adaptive alarm system adjusts an alarm threshold upwards in accordance with baseline drift so as to avoid nuisance alarms. In an embodiment, the rate of baseline movement is limited so as to avoid masking of transients. In an embodiment, the baseline is established along upper or lower portions of a parameter envelop so as to provide a margin of safety in lower limit or upper limit systems, respectively.

One aspect of an adaptive alarm system is responsive to a physiological parameter so as to generate an alarm threshold that adapts to baseline drift in the parameter and reduce false alarms without a corresponding increase in missed true alarms. The adaptive alarm system has a parameter derived from a physiological measurement system using a sensor in communication with a living being. A baseline processor calculates a parameter baseline from an average value of the parameter. Parameter limits specify an allowable range of the parameter. An adaptive threshold processor calculates an adaptive threshold from the parameter baseline and the parameter limits. An alarm generator is responsive to the parameter and the adaptive threshold so as to trigger an alarm indicative of the parameter crossing the adaptive threshold. The adaptive threshold is responsive to the parameter baseline so as to increase in value as the parameter baseline drifts to a higher parameter value and to decrease in value as the parameter baseline drifts to a lower parameter value.

In various embodiments, the baseline processor has a sliding window that identifies a time slice of parameter values. A trend calculator determines a trend from an average of the parameter values in the time slice. A response limiter tracks only the relatively long-term transitions of the trend. A bias calculator deletes the highest parameter values in the time slice or the lowest parameter values in the time slice so as to adjust the baseline to either a lower value or a higher value, respectively. The adaptive threshold becomes less response to baseline drift as the baseline approaches a predefined parameter limit. A first adaptive threshold is responsive to lower parameter limits and a second adaptive threshold is responsive to upper parameter limits. The alarm generator is responsive to both positive and negative transients from the baseline according to the first adaptive threshold and the second adaptive threshold. The first adaptive threshold is increasingly responsive to negative transients and the second adaptive threshold is decreasingly responsive to positive transients as the baseline trends toward lower parameter values.

Another aspect of an adaptive alarm system measures a physiological parameter, establishes a baseline for the parameter, adjusts an alarm threshold according to drift of the baseline and triggers an alarm in response to the parameter measurement crossing the alarm threshold. In various embodiments, the baseline is established by biasing a segment of the parameter, calculating a biased trend from the biased segment and restricting the transient response of the biased trend. The alarm threshold is adjusted by setting a parameter limit and calculating a delta difference between the alarm threshold and the baseline as a linear function of the baseline according to the parameter limit. The delta difference is calculated by decreasing delta as the baseline drifts toward the parameter limit and increasing delta as the baseline drifts away from the parameter limit. A parameter limit is set by selecting a first parameter limit in relation to a delayed alarm and selecting a second parameter limit in relation to an un-delayed alarm. A segment of the parameter is biased by windowing the parameter measurements, removing a lower value portion of the windowed parameter measurements and averaging a remaining portion of the windowed parameter measurements. An upper delta difference between an upper alarm threshold and the baseline is calculated and a lower delta difference between a lower alarm threshold and the baseline is calculated.

A further aspect of an adaptive alarm system has a baseline processor that inputs a parameter and outputs a baseline according to a trend of the parameter. An adaptive threshold processor establishes an alarm threshold at a delta difference from the baseline. An alarm generator triggers an alarm based upon a parameter transient from the baseline crossing the alarm threshold. In various embodiments, a trend calculator outputs a biased trend and the baseline is responsive to the biased trend so as to reduce the size of a transient that triggers the alarm. A response limiter reduces baseline movement due to parameter transients. The adaptive threshold processor establishes a lower alarm threshold below the baseline and an upper alarm threshold above the baseline so that the alarm generator is responsive to both positive and negative transients from the baseline. The baseline processor establishes a lower baseline biased above the parameter trend and an upper baseline biased below the parameter trend. The lower alarm threshold is increasingly responsive to negative transients and the upper alarm threshold is decreasingly responsive to positive transients as the baseline trends toward lower parameter values.

DESCRIPTION OF THE DRAWINGS

FIGS. 1-3 are exemplar graphs illustrating problems and issues associated with physiological parameter measurement systems having fixed threshold alarm schemas;

FIGS. 4A-B are general block diagrams of an adaptive alarm system having lower parameter limits;

FIGS. 5A-B are a graph of a physiological parameter versus delta space and a graph of delta versus baseline, respectively, illustrating the relationship between a baseline, a lower-limit adaptive threshold and a variable difference delta between the baseline and the adaptive threshold;

FIG. 6 is an exemplar graph of a physiological parameter versus time illustrating an adaptive alarm system having a lower-limit adaptive threshold;

FIG. 7 is a graph of oxygen saturation versus time illustrating a baseline for determining an adaptive threshold;

FIG. 8 is a graph of oxygen saturation versus time comparing adaptive-threshold alarm performance with fixed-threshold alarm performance;

FIGS. 9A-B are general block diagrams of an adaptive alarm system having upper parameter limits;

FIGS. 10A-B are a graph of a physiological parameter versus delta space and a graph of delta versus baseline, respectively, illustrating the relationship between a baseline, an upper-limit adaptive threshold and a variable delta difference between the baseline and the adaptive threshold;

FIG. 11 is an exemplar graph of a physiological parameter versus time illustrating an adaptive alarm system having an upper-limit adaptive threshold;

FIGS. 12A-B are general block diagrams of an adaptive alarm system having both lower alarm limits and upper alarm limits;

FIGS. 13A-E are physiological parameter versus delta space graphs illustrating a lower-limit adaptive threshold, an upper-limit adaptive threshold, and a combined lower- and upper-limit adaptive threshold in various delta spaces; and

FIG. 14 is an exemplar graph of a physiological parameter versus time illustrating an adaptive alarm system having both lower and upper alarm limits.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

FIGS. 4A-B illustrate anadaptive alarm system400 embodiment having lower parameter limits L₁and L₂. As shown inFIG. 4A, theadaptive alarm system400 hasparameter401, first limit (L₁)403, second limit (L₂)405 and maximum parameter value (Max)406 inputs and generates acorresponding alarm412 output. Theparameter401 input is generated by a physiological parameter processor, such as a pulse oximeter or an advanced blood parameter processor described above, as examples. Theadaptive alarm system400 has analarm generator410, abaseline processor420, and anadaptive threshold processor440. Thealarm generator410 hasparameter401 and adaptive threshold (AT)442 inputs and generates thealarm412 output accordingly. Abaseline processor420 has theparameter401 input and generates a parameter baseline (B)422 output. Thebaseline processor420, is described in detail with respect toFIG. 4B, below. Anadaptive threshold processor440 has parameter baseline (B)422,L₁403,L₂405 andMax406 inputs and generates the adaptive threshold (AT)442. Theadaptive threshold processor440 is described in detail with respect toFIGS. 5A-B, below.

As shown inFIG. 4A, in anembodiment L₁403 andL₂405 may correspond to conventional fixed alarm thresholds with and without an alarm time delay, respectively. For an adaptive threshold schema, however,L₁403 andL₂405 do not determine an alarm threshold per se, but are reference levels for determining an adaptive threshold (AT)442. In an embodiment,L₁403 is an upper limit of the adaptive alarm threshold AT when the baseline is near the maximum parameter value (Max), andL₂405 is a lower limit of the adaptive alarm threshold, as described in detail with respect toFIGS. 5A-B, below. In an exemplar embodiment when the parameter is oxygen saturation,L₁403 is set at or around 90% andL₂405 is set at 5 to 10% below L₁, i.e. at 85% to 80% oxygen saturation. Many other L₁and L₂values may be used for an adaptive threshold schema as described herein.

Also shown inFIG. 4A, in an embodiment thealarm412 output is triggered when theparameter401 input falls belowAT442 and ends when theparameter401 input rises aboveAT442 or is otherwise cancelled. In an embodiment, thealarm412 output is triggered after a time delay (TD), which may be fixed or variable. In an embodiment, the time delay (TD) is a function of the adaptive threshold (AT)442. In an embodiment, the time delay (TD) is zero when the adaptive threshold (AT) is at the second lower limit (L₂)405.

As shown inFIG. 4B, abaseline processor420 embodiment has a slidingwindow450, abias calculator460, atrend calculator470 and aresponse limiter480. The slidingwindow450 inputs theparameter401 and outputs atime segment452 of theparameter401. In an embodiment, each window incorporates a five minute span of parameter values. Thebias calculator460 advantageously provides an upward shift in the baseline (B)422 for an additional margin of error over missed true alarms. That is, abaseline422 is generated that tracks a higher-than-average range of parameter values, effectively raising the adaptive threshold AT slightly above a threshold calculated based upon a true parameter average, as shown and described in detail with respect toFIGS. 7-8, below. In an embodiment, thebias calculator460 rejects a lower range of parameter values from eachtime segment452 from the sliding window so as to generate abiased time segment462.

Also shown inFIG. 4B, thetrend calculator470 outputs abiased trend472 of the remaining higher range of parameter values in eachbiased segment462. In an embodiment, thebiased trend462 is an average of the values in thebiased time segment462. In other embodiments, thebiased trend462 is a median or mode of the values in thebiased time segment462. Theresponse limiter480 advantageously limits the extent to which thebaseline422 output tracks thebiased trend472. Accordingly, thebaseline422 tracks only relatively longer-lived transitions of the parameter, but does not track (and hence mask) physiologically significant parameter events, such as oxygen desaturations for a SpO₂parameter to name but one example. In an embodiment, theresponse limiter480 has a low pass transfer function. In an embodiment, theresponse limiter480 is a slew rate limiter.

FIGS. 5A-B further illustrate an adaptive threshold processor440 (FIG. 4A) having a baseline (B)422 input and generating an adaptive threshold (AT)442 output and a delta (Δ)444 ancillary output according toparameter limits L₁403,L₂405 andMax406, as described above. As shown inFIG. 5A, as the baseline (B)422 decreases (increases) the adaptive threshold (AT)444 monotonically decreases (increases) betweenL₁403 andL₂405. Further, as the baseline (B)422 decreases (increases) the delta (Δ)444 difference between the baseline (B)422 and the adaptive threshold (AT)442 monotonically decreases (increases) between Max−L₁and zero.

As shown inFIG. 5B, the relationship between the delta (Δ)444 and the baseline (B)444 may be linear550 (solid line), non-linear560 (small-dash lines) or piecewise-linear (large-dash lines), to name a few. In an embodiment, the adaptive threshold processor440 (FIG. 4A) calculates an adaptive threshold (AT)442 output in response to the baseline (B)422 input according to a linear relationship. In a linear embodiment, the adaptive threshold processor440 (FIG. 4A) calculates the adaptive threshold (AT)442 according to EQS. 1-2:

$\begin{array}{cc}\Delta =-\left(\frac{\mathrm{Max}-{\mathrm{<figure-callout\; label="L"\; filenames="USRE047218-20190205-D00001.png"\; state="\{\{state\}\}">L</figure-callout>}}_1}{\mathrm{Max}-L_2}\right)\left(\mathrm{Max}-B\right)+\left(\mathrm{Max}-L_1\right)& \left(1\right)\end{array}$
AT=B−Δ  (2)

where Δ=Max−L₁@ B=Max; Δ=0 @ B=L₂

and where AT=L₁@ B=Max; AT=L₂@ B=L₂, accordingly.

FIG. 6 illustrates the operational characteristics an adaptive alarm system400 (FIG. 4A) havingparameter limits Max612,L₁614 andL₂616 and an alarm responsive to a baseline (B)622,632,642; an adaptive threshold (AT)628,638,648; and acorresponding Δ626,636,646 according to EQS. 1-2, above. In particular, aphysiological parameter610 is graphed versustime690 for various time segments t₁, t₂, t₃692-696. The parameter range (PR)650 is:
PR=Max−L₂  (3)
and the adaptive threshold range (ATR)660 is:
ATR=L₁−L₂  (4)

As shown inFIG. 6, during a firsttime period t₁692, aparameter segment620 has a baseline (B)622 at aboutMax612. As such,Δ626=Max−L₁and the adaptive threshold (AT)628 is at about L₁614. Accordingly, a transient624 having a size less thanΔ626 does not trigger the alarm412 (FIG. 4A).

Also shown inFIG. 6, during a secondtime period t₂694, aparameter segment630 has a baseline (B)632 at about L₁614. As such,Δ636 is less than Max−L₁and the adaptive threshold (AT)638 is between L₁and L₂. Accordingly, a smaller transient634 will trigger the alarm as compared to a transient624 in the first time segment.

Further shown inFIG. 6, during a thirdtime period t₃696, aparameter segment640 has a baseline (B)642 at about L₂616. As such,Δ646 is about zero and the adaptive threshold (AT)648 is at about L₂. Accordingly, even a small negative transient will trigger the alarm. As such, the behavior of the alarm threshold AT628,638,648 advantageously adapts to higher or lower baseline values so as to increase or decrease the size of negative transients that trigger or do not trigger the alarm412 (FIG. 4A).

FIG. 7 is a parameter versustime graph700 illustrating the characteristics of an adaptive alarm system400 (FIGS. 4A-B), as described with respect toFIGS. 4-6, above, where the parameter is oxygen saturation (SpO₂). Thegraph700 has a SpO₂trace710 and asuperimposed baseline trace720. Thegraph700 also delineates trackingperiods730, where thebaseline720 follows the upper portions of SpO₂values, and laggingperiods740, where thebaseline720 does not follow transient SpO₂events. Thetracking time periods730 illustrate that thebaseline720 advantageously tracks at the higher range of SpO₂values710 during relatively stable (flat) periods, as described above. Laggingtime periods740 illustrate that thebaseline720 is advantageously limited in response to transient desaturation events so that significant desaturations fall below an adaptive threshold (not shown) and trigger an alarm accordingly.

FIG. 8 is a parameter versustime graph800 illustrating characteristics of an adaptive alarm system400 (FIGS. 4A-B), as described with respect toFIGS. 4-6, above, where the parameter is oxygen saturation (SpO₂). Vertical axis (SpO₂) resolution is 1%. Thetime interval801 between vertical hash marks is five minutes. Thegraph800 has a SpO₂trace810 and abaseline trace820. Thegraph800 also has a fixedthreshold trace830, a first adaptive threshold (AT)trace840 and asecond AT trace850. Thegraph800 further has a fixedthreshold alarm trace860, a first adaptivethreshold alarm trace870 and a second adaptivethreshold alarm trace880. In this example, L₁is 90% and L₂is 85% for thefirst AT trace840 and firstAT alarm trace870. L₂is 80% for asecond AT trace850 and a secondAT alarm trace880. The fixedthreshold830 results in many nuisance alarms860. By comparison, the adaptive threshold alarm with L₂=85% has just one time interval ofalarms872 during a roughly 6% desaturation period (from 92% to 86%). The adaptive threshold alarm with L₂=80%, has no alarms during the 1 hour 25 minute monitoring period.

FIGS. 9A-B illustrate anadaptive alarm system900 embodiment having upper parameter limits U₁and U₂. As shown inFIG. 9A, theadaptive alarm system900 hasparameter901, first limit (U₁)903, second limit (U₂)905 and minimum parameter value (Min)906 inputs and generates acorresponding alarm912 output. Theparameter901 input is generated by a physiological parameter processor, such as a pulse oximeter or an advanced blood parameter processor described above, as examples. Theadaptive alarm system900 has analarm generator910, abaseline processor920, and anadaptive threshold processor940. Thealarm generator910 hasparameter901 and adaptive threshold (AT)942 inputs and generates thealarm912 output accordingly. Abaseline processor920 has theparameter901 input and generates a parameter baseline (B)922 output. Thebaseline processor920, is described in detail with respect toFIG. 9B, below. Anadaptive threshold processor940 has parameter baseline (B)922,U₁903,U₂905 andMin906 inputs and generates the adaptive threshold (AT)942. Theadaptive threshold processor940 is described in detail with respect toFIGS. 10A-B, below.

As shown inFIG. 9A, in anembodiment U₁903 andU₂905 may correspond to conventional fixed alarm thresholds with and without an alarm time delay, respectively. For an adaptive threshold schema, however,U₁903 andU₂905 do not determine an alarm threshold per se, but are reference levels for determining an adaptive threshold (AT)942. In an embodiment,U₁903 is a lower limit of the adaptive alarm threshold AT when the baseline is near the minimum parameter value (Min), andU₂905 is an upper limit of the adaptive alarm threshold, as described in detail with respect toFIGS. 10A-B, below. In an exemplar embodiment when the parameter is oxygen saturation,U₁903 is set at or around 85% andU₂905 is set at or around 90% oxygen saturation. Many other U₁and U₂values may be used for an adaptive threshold schema as described herein.

Also shown inFIG. 9A, in an embodiment thealarm912 output is triggered when theparameter901 input rises aboveAT942 and ends when theparameter901 input falls belowAT942 or is otherwise cancelled. In an embodiment, thealarm912 output is triggered after a time delay (TD), which may be fixed or variable. In an embodiment, the time delay (TD) is a function of the adaptive threshold (AT)942. In an embodiment, the time delay (TD) is zero when the adaptive threshold (AT) is at the second upper limit (U₂)905.

As shown inFIG. 9B, abaseline processor920 embodiment has a slidingwindow950, abias calculator960, atrend calculator970 and aresponse limiter980. The slidingwindow950 inputs theparameter901 and outputs atime segment952 of theparameter901. In an embodiment, each window incorporates a five minute span of parameter values. Thebias calculator960 advantageously provides a downward shift in the baseline (B)922 for an additional margin of error over missed true alarms. That is, abaseline922 is generated that tracks a lower-than-average range of parameter values, effectively lowering the adaptive threshold AT slightly below a threshold calculated based upon a true parameter average. In an embodiment, thebias calculator960 rejects an upper range of parameter values from eachtime segment952 from the sliding window so as to generate abiased time segment962.

Also shown inFIG. 9B, thetrend calculator970 outputs abiased trend972 of the remaining lower range of parameter values in eachbiased segment962. In an embodiment, thebiased trend962 is an average of the values in thebiased time segment962. In other embodiments, thebiased trend962 is a median or mode of the values in thebiased time segment962. Theresponse limiter980 advantageously limits the extent to which thebaseline922 output tracks thebiased trend972. Accordingly, thebaseline922 tracks only relatively longer-lived transitions of the parameter, but does not track (and hence mask) physiologically significant parameter events, such as oxygen desaturations for a SpO₂parameter to name but one example. In an embodiment, theresponse limiter980 has a low pass transfer function. In an embodiment, theresponse limiter980 is a slew rate limiter.

FIGS. 10A-B further illustrate an adaptive threshold processor940 (FIG. 9A) having a baseline (B)922 input and generating an adaptive threshold (AT)942 output and a delta (Δ)944 ancillary output according toparameter limits U₁903,U₂905 andMin906, as described above. As shown inFIG. 10A, as the baseline (B)922 decreases (increases) the adaptive threshold (AT)944 monotonically decreases (increases) betweenU₁903 andU₂905. Further, as the baseline (B)922 decreases (increases) the delta (Δ)944 difference between the baseline (B)922 and the adaptive threshold (AT)942 monotonically decreases (increases) between Min−U₁and zero.

As shown inFIG. 10B, the relationship between the delta (Δ)944 and the baseline (B)944 may be linear550 (solid line), non-linear560 (small-dash lines) or piecewise-linear (large-dash lines), to name a few. In an embodiment, the adaptive threshold processor940 (FIG. 9A) calculates an adaptive threshold (AT)942 output in response to the baseline (B)922 input according to a linear relationship. In a linear embodiment, the adaptive threshold processor940 (FIG. 9A) calculates the adaptive threshold (AT)942 according to EQS. 5-6:

$\begin{array}{cc}\Delta =-\left(\frac{U_1-\mathrm{Min}}{U_2-\mathrm{Min}}\right)\left(B-\mathrm{Min}\right)+\left(U_1-\mathrm{Min}\right)& \left(5\right)\end{array}$
AT=B+Δ  (6)

where Δ=U₁−Min @ B=Min; Δ=0 @ B=U₂

and where AT=U₁@ B=Min; AT=U₂@ B=U₂, accordingly.

FIG. 11 illustrates the operational characteristics an adaptive alarm system900 (FIG. 9A) havingparameter limits Min1112,U₁1114 andU₂1116 and an alarm responsive to a baseline (B)1122,1132,1142; an adaptive threshold (AT)1128,1138,1148; and acorresponding Δ1126,1136,1146 according to EQS. 5-6, above. In particular, aphysiological parameter1110 is graphed versustime1190 for various time segments t₁, t₂, t₃1192-1196. The parameter range (PR)1150 is:
PR=U₂−Min   (7)
and the adaptive threshold range (ATR)1160 is:
ATR=U₂−U₁  (8)

As shown inFIG. 11, during a firsttime period t₁1192, aparameter segment1120 has a baseline (B)1122 at aboutMin1112. As such,Δ1126=U₁−Min and the adaptive threshold (AT)1128 is at aboutU₁1114. Accordingly, a transient1124 having a size less thanΔ1126 does not trigger the alarm912 (FIG. 9A).

Also shown inFIG. 11, during a secondtime period t₂1194, aparameter segment1130 has a baseline (B)1132 at aboutU₁1114. As such,Δ1136 is less than U₁−Min and the adaptive threshold (AT)1138 is between U₁and U₂. Accordingly, a smaller transient1134 will trigger the alarm as compared to a transient1124 in the first time segment.

Further shown inFIG. 11, during a thirdtime period t₃1196, aparameter segment1140 has a baseline (B)1142 at aboutU₂1116. As such,Δ1146 is about zero and the adaptive threshold (AT)1148 is at about U₂. Accordingly, even a small positive transient will trigger the alarm. As such, the behavior of the alarm threshold AT1128,1138,1148 advantageously adapts to higher or lower baseline values so as to increase or decrease the size of positive transients that trigger or do not trigger the alarm912 (FIG. 9A).

FIGS. 12A-B illustrate anadaptive alarm system1200 embodiment having lower limits L₁,L₂1203, such as described with respect toFIGS. 4A-B above, or upper limits U₁,U₂1205 such as described with respect toFIGS. 9A-B above, or both. As shown inFIG. 12A, theadaptive alarm system1200 hasparameter1201,lower limit1203 andupper limit1205 inputs and generates acorresponding alarm1212 output. Theparameter1201 input is generated by a physiological parameter processor, such as a pulse oximeter or an advanced blood parameter processor described above, as examples. Theadaptive alarm system1200 has analarm generator1210, abaseline processor1220 and anadaptive threshold processor1240. Thealarm generator1210 hasparameter1201 and adaptive threshold (AT)1242 inputs and generates thealarm1212 output accordingly. Abaseline processor1220 has theparameter1201 input and generates one ormore parameter baseline1222 outputs. Thebaseline processor1220, is described in detail with respect toFIG. 12B, below. Anadaptive threshold processor1240 hasparameter baseline1222, lower limit L₁,L₂1203 and upper limit U₁,U₂1205 inputs and generates lower and upper adaptive threshold AT_l, AT_u1242 outputs. Theadaptive threshold processor1240 also generates ancillary upper andlower delta1244 outputs. Theadaptive threshold processor1240 is described in detail with respect toFIGS. 13A-E, below.

As shown inFIG. 12A, in an embodiment L₁,L₂1203 and U₁,U₂1205 may correspond to conventional fixed alarm thresholds with an alarm delay (L₁, U₁) and without an alarm delay (L₂, U₂). For an adaptive threshold schema, however, theselimits1203,1205 do not determine an alarm threshold per se, but are reference levels for determining lower and upper adaptive thresholds AT_l, AT_u1242.

Also shown inFIG. 12A, in an embodiment thealarm1212 output is triggered when theparameter1201 input falls below AT_l1242 and ends when theparameter1201 input rises aboveAT_l1242 or the alarm is otherwise cancelled. Further, thealarm1212 output is triggered when theparameter1201 input rises above AT_u1242 and ends when theparameter1201 input falls below AT_u1242 or the alarm is otherwise cancelled. In an embodiment, thealarm1212 output is triggered after a time delay (TD), which may be fixed or variable. In an embodiment, the time delay (TD) is a function of the adaptive thresholds (AT_l, AT_u)1242. In an embodiment, the time delay (TD) is zero when the lower adaptive threshold (AT_l)1242 is at the second lower limit (L₂)1203 or when the upper adaptive alarm threshold AT_u1242 is at the second upper limit (U₂)1205.

As shown inFIG. 12B, abaseline processor1220 embodiment has a slidingwindow1250, anover-bias calculator1260, an under-bias calculator1265,trend calculators1270 andresponse limiters1280. The slidingwindow1250 inputs theparameter1201 and outputs atime segment1252 of theparameter1201. In an embodiment, each window incorporates a five minute span ofparameter1201 values.

Also shown inFIG. 12B, theover-bias calculator1260 advantageously provides an upward shift in the lower baseline (B_l)1282 for an additional margin of error over missed lower true alarms. That is, a lower baseline (B_l)1282 is generated that tracks a higher-than-average range of parameter values, effectively raising the lower adaptive threshold AT_lslightly above a threshold calculated based upon a true parameter average. In an embodiment, theover-bias calculator1260 rejects a lower range of parameter values from eachtime segment1252 of the slidingwindow1250 so as to generate anover-biased time segment1262.

Further shown inFIG. 12B, the under-bias calculator1265 advantageously provides a downward shift in the upper baseline (B_u)1287 for an additional margin of error over missed upper true alarms. That is, an upper baseline (B_u)1287 is generated that tracks a lower-than-average range of parameter values, effectively lowering the upper adaptive threshold AT_uslightly below a threshold calculated based upon a true parameter average. In an embodiment, the under-bias calculator1267 rejects an upper range of parameter values from eachtime segment1252 of the slidingwindow1250 so as to generate an under-biasedtime segment1267.

Additionally shown inFIG. 12B, thetrend calculator1270 outputs anover-biased trend1272 of the remaining higher range of parameter values in eachover-biased segment1262. Further, thetrend calculator1270 outputs an under-biasedtrend1277 of the remaining lower range of parameter values in each under-biasedsegment1267. In an embodiment, thebiased trends1272,1277 are each an average of the values in the correspondingbiased time segments1262,1267. In other embodiments, thebiased trends1272,1277 are each a median or mode of the values in the correspondingbiased time segments1262,1267. Theresponse limiter1280 advantageously limits the extent to which thebaseline1222 outputs track thebiased trends1272,1277. Accordingly, thebaseline1222 outputs track only relatively longer-lived transitions of theparameter1201, but do not track (and hence mask) physiologically significant parameter events. In an embodiment, theresponse limiter1280 has a low pass transfer function. In an embodiment, theresponse limiter1280 is a slew rate limiter.

FIGS. 13A-E illustrate parameter (P) operating ranges and ideal ranges in view of both lower and upper parameter limits. As shown inFIG. 13A, as the baseline (B_l)1317 decreases (increases) the adaptive threshold (AT_l)1318 monotonically decreases (increases) between L₁and L₂. Further, as the baseline (B_l)1317 decreases (increases) the delta (Δ_l)1319 difference between the baseline (B_l)1317 and the adaptive threshold (AT_l)1318 monotonically decreases (increases) between Max−L₁and 0.

As shown inFIG. 13B, as the baseline (B_u)1327 increases (decreases) the adaptive threshold (AT_u)1328 monotonically increases (decreases) between U₁and U₂. Further, as the baseline (B_u)1327 increases (decreases) the delta (Δ_u)1329 difference between the adaptive threshold (AT_u)1328 and the baseline (B_u)1327 monotonically decreases (increases) between Min−U₁and 0.

As shown inFIG. 13C, combiningFIGS. 13A-B, the parameter (P) operating range is bounded by the overlapping regions of13A and13B1330 having an upper bound of U₂and a lower bound of L₂. In particular, L₁, L₂are the upper and lower limits of the lower adaptive alarm threshold AT_l; and U₂, U₁are the upper and lower limits of the upper adaptive alarm threshold AT_u.

FIG. 13D illustrates parameter (P) versus the overlapping independent delta domains F_u, F_lfor upper and lower baselines B_u, B_l; adaptive thresholds AT_u, AT_land deltas Δ_u, Δ_l, based uponFIGS. 13A-C.FIG. 13E illustrates parameter (P) versus the overlapping independent delta domains F_u, F_l(reversed); for upper and lower baselines B_u, B_l; adaptive thresholds AT_u, AT_land deltas Δ_u, Δ_l,

As shown inFIG. 13E, the equations for bi-lateral adaptive thresholds are:

$\begin{array}{cc}{\Delta }_u=-\left(\frac{U_1-L_2}{U_2-L_2}\right)\left(B-L_2\right)+\left(U_1-L_2\right)& \left(9\right)\end{array}$
AT_u=B+Δ_u  (10)

where Δ_u=U₁−L₂@ B=L₂; and Δ_u=0 @ B=U₂; and

where AT_u=U₁@ B=L₂; and AT_u=U₂@ B=U₂.

Further:

$\begin{array}{cc}{\Delta }_l=\left(\frac{U_2-L_1}{U_2-L_2}\right)\left(B-L_2\right)& \left(11\right)\end{array}$
AT_l=B−Δ_l  (12)

where Δ_l=U₂−L₁@ B=U₂; and Δ_l=0 @ B=L₂; and

where AT_l=L₁@ B=U₂; AT_l=L₂@ B=L₂.

Although shown as a linear relationship, in general:
Δ_l=f₁(B);Δ_u=f₂(B)
That is, Δ_land Δ_ucan each be a linear function of B, a non-linear function of B or a piecewise linear function of B, to name a few, in a manner similar to that described with respect toFIGS. 5B and 10B, above.

FIGS. 14A-B illustrate the operational characteristics an adaptive alarm system1200 (FIGS. 12A-B) having upper limits U₁,U₂1412,1414 and lower limits L₁,L₂1422,1424. An alarm1212 (FIG. 12A) output is responsive to a baseline (B)1432,1442,1452,1462; an upper delta (Δ_u)1437,1447,1457,1467; and a corresponding upper adaptive threshold (AT_u)1439,1449,1459,1469, according to EQS. 9-10, above. Further, the alarm1212 (FIG. 12A) output is responsive to a lower delta (Δ_l)1436,1446,1456,1466 and a corresponding lower adaptive threshold (AT_l)1438,1448,1458,1468, according to EQS. 11-12, above.

As shown inFIGS. 14A-B, aphysiological parameter1410 is graphed versustime1490 for various time segments t₁, t₂, t₃, t₄1492-1498. The parameter range (PR)1480 is:
PR=U₂−L₂  (13)
the lower adaptive threshold AT_lrange is:
ATR_l=L₁−L₂  (14)
the upper adaptive threshold AT_Urange is:
ATR_l=U₂−U₁  (15)

As shown inFIG. 14A, during a firsttime period t₁1492, aparameter segment1430 has a baseline (B)1432 at aboutU₂1414. As such,Δ_l1436=U₂−L₁;Δ_u1437=0; AT_l1438=L₁; AT_u1439=U₂. Accordingly, a negative transient1434 having a size less than U₂−L₁does not trigger an alarm.

Also shown inFIG. 14A, during a secondtime period t₂1494, aparameter segment1440 has a baseline (B)1442 less than U₂. As such,Δ_l1446 is less than U₁−L₁and the adaptive threshold (AT_u)1447 is between U₁and U₂. Accordingly, a smaller negative transient1444 will trigger the alarm as compared to the negative transient1434 in thefirst time segment1430.

Further shown inFIG. 14A, during a thirdtime period t₃1496, aparameter segment1450 has a baseline (B)1452 less than U₁1412. As such, a smaller negative transient1454 will trigger the alarm as compared to the negative transient1444 in thesecond time segment1440. However, a larger positive transient1455 is needed to trigger the alarm as compared to the positive transient1445 in thesecond time segment1440.

Additionally shown inFIG. 14A, during a fourthtime period t₄1460, aparameter segment1460 has a baseline (B)1462 at about L₂1424. As such,Δ_l1466=0; Δ_u1467=U₁−L₂; AT_l1468=L₂; AT_u1469=U₁. Accordingly, a positive transient1465 having a size less than U₁−L₂does not trigger an alarm.

An adaptive alarm system has been disclosed in detail in connection with various embodiments. These embodiments are disclosed by way of examples only and are not to limit the scope of the claims that follow. One of ordinary skill in the art will appreciate many variations and modifications.

Claims (18)

What is claimed is:

1. A system for reducing electronic alarms in a medical patient monitoring system, the system comprising:

an optical sensor configured to transmit optical radiation into a tissue site of a patient and detect attenuated optical radiation indicative of at least one physiological parameter of a patient; and

one or more hardware processors in electronic communication with the optical sensor, the one or more hardware processors configured to:

measuredetermine oxygen saturation values of athe patient over a first period of time;

determine ifwhen at least one oxygen saturation value obtained over the first period of time exceeds a first alarm threshold;, determine whether a first alarm should be triggered based on the determination that the at least one oxygen saturation value obtained over the first period of time exceeds the first alarm threshold;

determineaccess a second alarm threshold to be applied during a second period of time subsequent to the first period of time, the second alarm threshold replacing the first alarm threshold, wherein the second alarm threshold being determined by:

comparing at least a first oxygen saturation value obtained during the first time period with a lower limit associated with oxygen saturation; and

computing a second alarm threshold based on the comparison where the second alarm threshold is computed to be at has a value less than the at least first one oxygen saturation value and greater than the a lower limit and at an offset from the first at least one oxygen saturation value, wherein the offset is configured to diminish is diminished as a difference between the at least first oxygen saturation value and the lower limit diminishes;

measuredetermine oxygen saturation values of athe patient over the second period of time to determine at least a second oxygen saturation value; and

determine whethertrigger a second alarm should be triggered by determining ifbased on at least one value of the oxygen saturation valuevalues obtained duringover the second period of time exceedsexceeding the second alarm threshold and triggering an alarm if it is determined the second alarm should be triggered.

2. The system ofclaim 1, wherein the one or more hardware processors are configured to calculate a first baseline measurement from the measured oxygen saturation values over the first period of time and wherein the at least one oxygen saturation value obtained during the first period of time corresponds to the first baseline measurement.

3. The system ofclaim 2, wherein the one or more hardware processors are configured to calculate a second baseline measurement from the measured oxygen saturation values over the second period of time and wherein the at least one oxygen saturation value obtained during the second period of time corresponds to the second baseline measurement.

4. The system ofclaim 1, wherein the lower limit is predefined predetermined and corresponds to a minimum parameter value for oxygen saturation.

5. The system ofclaim 1, wherein the one or more hardware processors are further configured to wait for a time delay prior to the triggering of the second alarm, and wherein the time delay is a function of the second alarm threshold.

6. The system ofclaim 5, wherein the time delay decreases as the difference between the at least first oxygen saturation one value and the lower limit diminishes.

7. The system ofclaim 1, wherein the first alarm threshold is predetermined.

8. A system for reducing electronic alarms in a medical patient monitoring system including a pulse oximeter in communication with an optical sensor, the system comprising one or more hardware processors configured to:

measuredetermine oxygen saturation values of a patient over a first period of time;

determine if at least one oxygen saturation value obtained over the first period of time exceeds a first alarm threshold;

determine whether a first alarm should be triggered based on the determination that the at least one oxygen saturation value obtained over the first period of time exceeds the first alarm threshold;

compare at least a first oxygen saturation value obtained during the first time period with a lower limit associated with oxygen saturation;

compute access a second alarm threshold based on the comparison;

determineapply a time delay based on the computed second alarm threshold, wherein the time delay approaches zero as the first at least one oxygen saturation value obtained over the first period of time approaches the lower limit;

measuredetermine oxygen saturation values of athe patient over thea second period of time to determine at least a second oxygen saturation valuedifferent from the first period; and

determine whethertrigger a second alarm should be triggered by determining ifbased on the at least one oxygen saturation value obtained during the second period of time exceedsexceeding the second alarm threshold for the time delay and triggering an alarm if it is determined the second alarm should be triggered,

where the second alarm threshold is at a value less than the at least one oxygen saturation value and greater than the lower limit and at an offset from the at least one oxygen saturation value, wherein the offset is diminished as a difference between the at least one oxygen saturation value and the lower limit diminishes.

9. The system ofclaim 8, wherein the first alarm threshold is predetermined.

10. The system ofclaim 8, wherein the lower limit is predefined predetermined and corresponds to a minimum parameter value for oxygen saturation.

11. The system ofclaim 8, where the second alarm threshold is computed to be at a value less than the at least first oxygen saturation value and greater than the lower limit and at an offset from the first oxygen saturation value, wherein the offset is configured to diminish as a difference between the at least first oxygen saturation value and the lower limit diminishes.

12. An electronic method for of reducing electronic alarms in a medical patient monitoring system, the electronic method comprising:

measuring, with a pulse oximeter including a light source, an optical detector and one or more hardware processors configured to receive signals responsive to light attenuated by tissue of a patient, oxygen saturation values of a the patient over a first period of time;

determining, using the one or more hardware processors, if at least one oxygen saturation value determined measured over the first period of time exceeds a first alarm threshold;

determining whether a first alarm should be triggered based on the determination that at least one oxygen saturation value obtained during the first period of time exceeds the first alarm threshold;

comparing at least a first oxygen saturation value obtained during the first time period with a lower limit associated with oxygen saturation;

computing the applying, using the one or more hardware processors, a second alarm threshold based on the comparison where the second alarm threshold is computed to be at a value (i) less than the at least first an oxygen saturation value and of the patient, (ii) greater than the a lower limit, (iii) and at an offset from the first oxygen saturation value of the patient, wherein the offset is configured to diminish is diminished as a difference between the at least first oxygen saturation value and the lower limit diminishes and wherein the second alarm threshold is configured to be applied during a second period of time subsequent to the first period of time, the second alarm threshold replacing replaces the first alarm threshold;

measuring, using the pulse oximeter, oxygen saturation values of a the patient over the second period of time to determine at least a second oxygen saturation value; and

determining, using the one or more hardware processors, whether to trigger a second alarm should be triggered by at least determining if at least one oxygen saturation value obtained during the second period of time exceeds the second alarm threshold and triggering an alarm if it is determined the second alarm should be triggered.

13. The electronic method ofclaim 12, wherein the one or more hardware processors are configured to calculate the electronic method further comprises, using the one or more hardware processors, calculating a first baseline measurement from the measured oxygen saturation values over the first period of time and wherein the at least one oxygen saturation value obtained during the first period of time corresponds to the first baseline measurement.

14. The electronic method ofclaim 13, wherein the one or more hardware processors are configured to calculate the electronic method further comprises, using the one or more hardware processors, calculating a second baseline measurement from the measured oxygen saturation values over the second period of time and wherein the at least one oxygen saturation value obtained during the second period of time corresponds to the second baseline measurement.

15. The electronic method ofclaim 12, wherein the lower limit is predefined predetermined and corresponds to a minimum parameter value for oxygen saturation.

16. The electronic method ofclaim 12, wherein the one or more hardware processors are further configured to wait the electronic method further comprises, using the one or more hardware processors, waiting for a time delay prior to the triggering of the second alarm, and wherein the time delay is a function of the second alarm threshold.

17. The electronic method ofclaim 16, wherein the time delay decreases as the difference between the at least first one oxygen saturation value and the lower limit diminishes.

18. The electronic method ofclaim 12, wherein the first alarm threshold is predetermined.

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