`(12) Patent Application Publication (10) Pub. No.: US 2007/0208240A1
`(43) Pub. Date:
`Sep. 6, 2007
`Nordstrom et al.
`
`US 20070208240A1
`
`(54) TECHNIQUES FOR DETECTING HEART
`PULSES AND REDUCING POWER
`CONSUMPTION IN SENSORS
`
`(75) Inventors: Brad Nordstrom, Alameda, CA (US);
`William Shea, Livermore, CA (US);
`Ethan Petersen, Castro Valley, CA
`(US)
`Correspondence Address:
`Nellcor Puritan Bennett LLC
`c/o Fletcher Yoder PC
`P.O. BOX 692.289
`HOUSTON, TX 77269-2289 (US)
`(73) Assignee: Nellcor Puritan Bennett Inc., Pleasan
`ton, CA
`(21) Appl. No.:
`11/650,861
`
`(22) Filed:
`
`Jan. 8, 2007
`Related U.S. Application Data
`(63) Continuation of application No. 10/787,851, filed on
`Feb. 25, 2004, now Pat. No. 7,162,288.
`
`Publication Classification
`
`(51) Int. Cl.
`(2006.01)
`A6IB 5/00
`(52) U.S. Cl. ............................................ 600/323; 600/336
`
`(57)
`
`ABSTRACT
`
`Low power techniques for sensing cardiac pulses in a signal
`from a sensor are provided. A pulse detection block senses
`the sensor signal and determines its signal-to-noise ratio.
`After comparing the signal-to-noise ratio to a threshold, the
`drive current of light emitting elements in the sensor is
`dynamically adjusted to reduce power consumption while
`maintaining the signal-to-noise ratio at an adequate level.
`The signal component of the sensor signal can be measured
`by identifying systolic transitions. The systolic transitions
`are detected using a maximum and minimum derivative
`averaging scheme. The moving minimum and the moving
`maximum are compared to the scaled Sum of the moving
`minimum and moving maximum to identify the systolic
`transitions. Once the signal component has been identified,
`the signal component is compared to a noise component to
`calculate the signal-to-noise ratio.
`
`
`
`101
`
`104
`
`Threshold
`Comparison
`Block
`
`Pulse Detection
`Block
`
`APL1111
`Apple v. Valencell
`IPR2017-00318
`
`001
`
`
`
`Patent Application Publication Sep. 6, 2007 Sheet 1 of 3
`
`US 2007/0208240A1
`
`Threshold
`Comparison
`Block
`
`
`
`
`
`
`
`
`
`
`
`Calculate he moving average
`of the derivative of the pulse
`Oximeter signal
`
`202
`
`
`
`Calculate moving average of the
`output of step 201
`
`Calculate moving average of
`the output of step 202
`
`204
`identify the movingminimum
`and the moving maximum of
`the output of step 203
`
`
`
`
`
`
`
`
`
`Compare the moving minimum and the moving
`maximum from step 204 to a scaled sum of these
`minimum and maximum values in order to detect
`potential systolic-diastolic cardiac transitions.
`
`
`
`
`
`Filter out false positive
`transitions using pulse
`qualification routines
`
`FIG.2
`
`002
`
`
`
`Patent Application Publication Sep. 6, 2007 Sheet 2 of 3
`
`US 2007/0208240 A1
`
`72
`as
`al
`NSZIN
`""""""""""""N
`N
`N
`I NY 304
`N302
`IY302
`IN
`
`2
`
`g/ 301
`
`
`
`
`
`1OOO so I-A as I-4
`27","e", "g"g", 2N2's
`to SH-4 YN.
`312
`Entering Systole
`312 Exiting systole
`SSF
`
`-2OOO
`-2500
`-3000
`-3500
`
`320
`
`1
`
`1N
`Entering systole
`
`
`
`25OOO
`2000
`15000
`
`1OOOO
`5000
`
`-5000
`
`-10000
`-15OOO
`
`003
`
`
`
`Patent Application Publication Sep. 6, 2007 Sheet 3 of 3
`
`US 2007/0208240 A1
`
`
`
`Digital-to-
`Analog
`Converter
`
`Sigma
`Delta
`Modulator
`
`Gain Control
`Feedback Loop
`
`- Y - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
`
`004
`
`
`
`US 2007/0208240 A1
`
`Sep. 6, 2007
`
`TECHNIQUES FOR DETECTING HEART PULSES
`AND REDUCING POWER CONSUMPTION IN
`SENSORS
`
`BACKGROUND OF THE INVENTION
`0001. The present invention relates to techniques for
`detecting heart pulses and reducing power consumption in
`sensors and oximeter systems, and more particularly, to
`techniques for distinguishing heart pulses in a sensor signal
`from noise and adjusting drive current provided to light
`emitting elements in response to a signal-to-noise ratio of
`the pulse in order to reduce power consumption.
`0002 Pulse oximetry is a technology that is typically
`used to measure various blood chemistry characteristics
`including, but not limited to, the blood-oxygen Saturation of
`hemoglobin in arterial blood, the volume of individual blood
`pulsations Supplying the tissue, and the rate of blood pull
`sations corresponding to each heartbeat of a patient.
`0003. Measurement of these characteristics has been
`accomplished by use of a non-invasive sensor. The sensor
`has a light source Such as a light emitting diode (LED) that
`scatters light through a portion of the patient's tissue where
`blood perfuses the tissue. The sensor also has a photodetec
`tor that photoelectrically senses the absorption of light at
`various wavelengths in the tissue. The photodetector gen
`erates a pulse oximeter signal that indicates the amount of
`light absorbed by the blood. The amount of light absorbed is
`then used to calculate the amount of blood constituent being
`measured.
`0004 The light scattered through the tissue is selected to
`be of one or more wavelengths that are absorbed by the
`blood in an amount representative of the amount of the blood
`constituent present in the blood. The amount of transmitted
`light scattered through the tissue will vary in accordance
`with the changing amount of blood constituent in the tissue
`and the related light absorption.
`0005 For measuring blood oxygen level, oximeter sen
`sors typically have a light source that is adapted to generate
`light of at least two different wavelengths, and with photo
`detectors sensitive to these wavelengths, in accordance with
`known techniques for measuring blood oxygen Saturation. A
`typical pulse oximeter will alternately illuminate the patient
`with red and infrared light using two LEDs to obtain two
`different detector signals.
`0006 The pulse oximeter signal generated by the photo
`detector usually contains components of noise introduced by
`the electronics of the oximeter, by the patient, and by the
`environment. Noisy signals have a low signal-to-noise ratio.
`A pulse oximeter cannot accurately identify the blood oxy
`gen Saturation when the signal-to-noise ratio of the pulse
`Oximeter signal is too low.
`0007 To improve the signal-to-noise ratio of the pulse
`Oximeter signal, a pulse oximeter system will typically drive
`the LEDs with a large amount of current. A servo in the pulse
`oximeter will typically drive as much current as possible
`through the LEDs without causing the oximeter to be
`over-ranged (i.e., driven to full rail). The large drive current
`causes the LEDs to generate more light and to consume
`more power. Because the photodetector is able to sense more
`of the light from the LEDs, the signal-to-noise ratio of the
`pulse Oximeter signal is higher.
`
`0008 Increasing the drive current of the LEDs to
`improve the signal-to-noise ratio of the pulse oximeter
`signal causes the system to consume an undesirably large
`amount of power. The large amount of power consumption
`can be a problem for oximeter systems that are battery
`operated.
`0009. It would therefore be desirable to provide pulse
`Oximeter systems that consume less power without nega
`tively compromising the signal-to-noise ratio of the pulse
`Oximeter signal.
`BRIEF SUMMARY OF THE INVENTION
`0010) The present invention provides CPU cycle efficient
`techniques for sensing heart pulses in a signal from a sensor.
`The sensor signal can be, for example, a pulse oximeter
`signal generated by a photodetector in a pulse oximeter
`sensor. The signal component of the sensor signal is mea
`Sured by identifying potential systolic transitions of the
`cardiac cycle. The systolic transitions are detected using a
`derivative averaging scheme. The moving minimum and the
`moving maximum of the average derivative are compared to
`a scaled sum of the minimum and maximum to identify the
`systolic transitions. The systolic transitions correspond to a
`signal component of the sensor signal. The signal compo
`nent is compared to a noise component to determine the
`signal-to-noise ratio of the signal.
`0011. The present invention also provides techniques for
`reducing power consumption in a sensor. After the signal
`to-noise ratio of the pulse oximeter has been determined, the
`signal-to-noise ratio is compared to a threshold. In response
`to the output of the comparison, the drive current of light
`emitting elements in the sensor is dynamically adjusted to
`reduce power consumption and to maintain the signal-to
`noise ratio at an adequate level for signal processing.
`0012. The present invention also provides techniques for
`sensing and adjusting the gain of a transimpedance amplifier
`to reduce the effect of ambient noise in a sensor. A gain
`control feedback loop senses the magnitude of the sensor
`signal when the light emitting elements are off. The gain
`control loop can include this information to effectively
`control the gain of the transimpedance amplifier.
`0013 For a further understanding of the nature and
`advantages of the invention, reference should be made to the
`following description taken in conjunction with the accom
`panying drawings.
`BRIEF DESCRIPTION OF THE DRAWINGS
`0014 FIG. 1 illustrates a block diagram of a pulse
`Oximeter system with reduced power consumption accord
`ing to an embodiment of the present invention;
`0015 FIG. 2 is a flow chart that illustrates a process for
`identifying the systolic period of a pulse Oximeter signal
`according to an embodiment of the present invention;
`0016 FIGS. 3A-3C are graphs that illustrates how sys
`tolic transitions are identified in pulse oximeter signals
`according to embodiments of the present invention; and
`0017 FIG. 4 illustrates a portion of a pulse oximeter
`system with a transimpedance amplifier, a sigma-delta
`modulator, an analog-to-digital converter, and again control
`feedback loop according to an embodiment of the present
`invention.
`
`005
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`
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`US 2007/0208240 A1
`
`Sep. 6, 2007
`
`DETAILED DESCRIPTION OF THE
`INVENTION
`0018. The techniques of the present invention can be used
`in the context of a pulse oximeter system. A pulse oximeter
`system receives a pulse oximeter signal from a photodetec
`tor in a pulse oximeter sensor. FIG. 1 illustrates a block
`diagram of pulse oximeter system according to an embodi
`ment of the present invention. The pulse oximeter system
`includes an oximeter sensor 101.
`0019. An oximeter sensor of the present invention can
`utilize any suitable number of light emitting elements. For
`example, a sensor of the present invention can have 1, 2, 3,
`or 4 light emitting elements. In the example of FIG. 1, sensor
`101 has two LEDs 110 and 111 that emit two different
`wavelengths of light.
`0020 Sensor 101 also includes photodetector 112 that
`senses light from LEDs 110 and 111 after the light has
`passed through the patient’s tissue. The pulse oximeter
`system also includes feedback loop circuitry 110 and LED
`drive interface 104. Feedback loop circuitry 110 includes
`pulse detection block 102 and threshold comparison block
`103.
`Photodetector 112 transmits the pulse oximeter
`0021
`signal to pulse detection block 102. Pulse detection block
`102 has a servo that measures the signal component of the
`pulse oximeter signal by identifying the systolic transitions.
`The pulse detection block 102 and the threshold comparison
`block 103 form a feedback loop 110 around the sensor to
`control the drive current of the LEDs and the signal-to-noise
`ratio of the pulse oximeter signal, as will be discussed in
`detail below.
`0022. A cardiac pulse can be divided into a diastolic and
`systolic period. The systolic period is typically characterized
`by a rapid change in value due to the contraction of the heart.
`The diastolic period is typically characterized by a gradual
`change in value, due to the relaxation and refilling of the
`heart chambers.
`0023 Systolic transitions in the pulse oximeter signal are
`detected using a three step maximum and minimum deriva
`tive averaging scheme, which is discussed in further detail
`below. Qualification routines are then used to filter out false
`positives. The resulting data contains the systolic transitions
`separated from the non-systolic periods in the pulse oXime
`ter signal.
`0024 Pulse detection block 102 then compares the ampli
`tude of the systolic portion of the pulse oximeter signal to a
`noise component to generate a value for the signal-to-noise
`ratio of the pulse oximeter signal. Subsequently, threshold
`comparison block 103 compares this signal-to-noise ratio to
`a threshold level to determine whether the signal-to-noise
`ratio is high enough Such that the pulse oximeter signal can
`be used to accurately calculate pulse rate and oxygen
`saturation. Too much noise obscures the pulse rate and
`oxygen Saturation information in the signal. Noise can
`degrade the signal to the point that it cannot be used to
`accurately calculate pulse rate or oxygen Saturation.
`0.025 Threshold comparison block 103 preferably con
`tains two hysteretic threshold levels. In this embodiment,
`threshold comparison block 103 senses whether the signal
`to-noise ratio is greater than a maximum threshold level or
`
`less than a minimum threshold level. As an example, the
`maximum threshold level can represent a signal-to-noise
`ratio of 128:1, and the minimum threshold level can repre
`sent a signal-to-noise ratio of 8:1. These are merely two
`examples of thresholds levels. They are not intended to limit
`the scope of the present invention. Prior art oximeter sys
`tems, for example, operate at a signal-to-noise ratio of
`10,000:1 or higher, because they drive the LEDs as bright as
`possible.
`0026.
`If the signal-to-noise ratio is greater than the maxi
`mum threshold level, threshold comparison block 103 sends
`a signal to LED drive interface 104 to reduce the LED
`current. Based on the value of the signal-to-noise ratio,
`threshold comparison block 103 can determine how much
`the LED drive current needs to be reduced to decrease the
`signal-to-noise ratio while maintaining the signal level
`within the minimum and maximum threshold levels. LED
`drive interface 104 responds by decreasing the LED drive
`current to the value indicated by threshold comparison block
`103.
`0027. The feedback loop continuously monitors the sig
`nal-to-noise ratio of the pulse oximeter signal and dynami
`cally adjusts the LED drive current and Subsequent system
`gain until the signal-to-noise ratio is less than the maximum
`threshold. The oximeter system saves power by substantially
`reducing the LED drive current (relative to prior art sys
`tems), while maintaining the signal-to-noise ratio of the
`pulse oximeter signal within an acceptable range.
`0028. The signal-to-noise ratio can also drop too low for
`a number of reasons. For example, the noise in the pulse
`Oximeter may increase, or the strength of the signal com
`ponent may decrease if the blood oxygen saturation of the
`patient decreases. In any event, the system of FIG. 1 senses
`when the magnitude of the pulse oximeter signal is too low
`and increases the LED drive current accordingly.
`0029. If the signal-to-noise ratio is less than the minimum
`threshold level, threshold comparison block 103 sends a
`signal to LED drive interface 104 to increase the LED
`current. Based on the value of the signal-to-noise ratio, the
`threshold comparison can determine how much the LED
`drive current needs to be increased to increase the signal
`to-noise ratio while maintaining the signal within the mini
`mum and maximum threshold levels. LED drive interface
`104 responds by increasing the LED drive current to the
`value indicated by the threshold comparison system.
`0030 The feedback loop continuously monitors the sig
`nal-to-noise ratio of the pulse oximeter signal and dynami
`cally adjusts the LED drive current until the signal-to-noise
`ratio is greater than the minimum threshold level. The
`minimum threshold indicates a minimum allowable value
`for the signal-to-noise ratio for which the pulse rate and the
`oxygen Saturation can be accurately calculated.
`0031) If the signal-to-noise ratio falls between the maxi
`mum and minimum threshold levels, the oXimeter system
`maintains the LED drive current at a stable value. The
`Oximeter system maintains equilibrium until the signal-to
`noise ratio of the pulse oximeter signal moves outside the
`range of the thresholds. Thus, an oximeter system of the
`present invention contains a dynamic feedback loop as
`shown in FIG. 1. The dynamic feedback loop automatically
`adjusts the drive current of the LEDs to reduce power
`
`006
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`US 2007/0208240 A1
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`Sep. 6, 2007
`
`consumption in the sensor and to maintain the signal-to
`noise ratio at an acceptable level for the purpose of accu
`rately calculating blood oxygen Saturation levels.
`0032. According to a preferred embodiment of the
`present invention, the hardware for the servo in pulse
`detection block 102 maintains a predictable relationship
`between the power that LED drive 104 attempts to the drive
`the LEDs at and the radiated output power actually gener
`ated by the LEDs. By providing a predictable relationship
`between the input and output power, the feedback loop is
`more likely to acquire the oxygen Saturation from the pulse
`Oximeter signal in significantly less time, requiring less
`executions of the servo.
`0033. As the gain of the pulse oximeter signal is
`increased, the signal component generally increases faster
`than the noise component (at least to a point below the
`highest gain settings). The effect that increasing the gain of
`the pulse Oximeter signal has on the signal-to-noise ratio in
`a particular system should be understood. Certain combina
`tions of gain may cause more noise to be present in the pulse
`Oximeter signal. Therefore, the gain stages in the pulse
`detection block preferably take advantage of characteristics
`of the gain-to-noise variability.
`0034) For example, the signal from the photodetector that
`is sampled using an analog-to-digital converter is fed into a
`gain block. The gain block includes several gain stages to
`achieve a known response. The noise is measured at each of
`the gain stages, and then stored for later use to calculate the
`signal-to-noise ratio.
`0035 Techniques for identifying the systolic portions of
`a pulse oximeter signal generated by an oximeter sensor are
`now discussed. The systole identification of the present
`invention uses a three step maximum and minimum deriva
`tive averaging scheme in order to detect cardiac systolic
`eVentS.
`FIG. 2 illustrates one method for identifying the
`0.036
`systolic period of a pulse oximeter signal. In the first step
`201, the moving average of the derivative of the pulse
`Oximeter signal is found. In the second step 202, the moving
`average of the output of the first step 201 is found. In the
`third step 203, the moving average of the output of the
`second step 202 is found.
`0037 Next, the moving maximum and the moving mini
`mum of the output of the third step is found at step 204. At
`step 205, systole transitions are detected by comparing this
`moving minimum and moving maximum to a scaled sum of
`the moving minimum and maximum. For example, the
`scaled Sum of the moving minimum and maximum values
`can be a fractional Sum of the minimum and maximum
`moving averages.
`0038. When the minimum output of step 204 becomes
`less than a fractional sum of the maximum and minimum
`moving averages, the system determines that the pulse
`Oximeter signal is entering systole. When the minimum
`output of step 204 becomes more than a fractional sum of the
`maximum and minimum moving averages, the system deter
`mines that pulse oximeter signal is exiting systole.
`0.039 The two predetermined fractional sums can be
`selected to be any suitable values. As a specific example, the
`system can determine that the pulse oximeter signal is
`
`entering systole when the minimum derivative output
`becomes less than /16 the Sum of the minimum and maxi
`mum moving averages of the third stage. As another
`example, the system can determine that the pulse oximeter
`signal is exiting systole when the minimum derivative
`output becomes more than /8 the sum of the maximum and
`minimum moving averages of the third stage. These two
`examples are not intended to limit the scope of the present
`invention. Many other fractional values can also be used to
`identify systole transitions.
`0040. These techniques of the present invention can
`detect and qualify pulses using CPU, RAM, and ROM
`efficient algorithms. Minimal processor resources are
`required to perform oximetry calculations with a comparable
`level of Saturation and pulse rate performance as prior art
`Oximeter technology.
`0041
`Example waveforms for the results of these calcu
`lations are shown in FIG. 3A. Waveform 303 is an example
`of the derivative of a pulse oximeter signal. Waveforms 301
`and 304 are examples of the minimum and maximum
`moving average of the pulse oximeter signal, respectively.
`Waveform 302 is an example of the output signal of the
`three-step moving average.
`0042. The output of the moving average is a smoothed
`and delayed version of the derivative of the pulse oximeter
`signal. The minimum output tracks the negative-going
`trends and lags the positive-going trends. The maximum
`output tracks the positive-going trends and lags the negative
`going trends. These relationships are key to detecting poten
`tial systolic cardiac periods.
`0043 FIG. 3B shows examples of the minimum moving
`average 301 with a waveform 313 that represents /16 of the
`Sum of the minimum and maximum moving averages of the
`third stage. FIG. 3B also shows an example of waveform
`312 that represents /s of the sum of the minimum and
`maximum moving averages of the third stage.
`0044 According to one embodiment of the present inven
`tion, waveforms 312 and 313 are compared to the minimum
`moving average waveform 301 at step 205 to identify the
`systolic period of the pulse oximeter signal. Alternatively,
`other scaled Sums for the minimum and/or maximum mov
`ing averages can be used to identify systolic periods in the
`pulse oximeter signal. The beginning and the end of a systole
`in signal 301 are identified in FIG. 3B. The period between
`crossing points of signal 301 and signals 312/313 defines the
`systolic period.
`0045 When applied to the original pulse oximeter signal
`320, the systolic period identification is shown in FIG. 3C.
`The systolic period includes the time between the peak (i.e.
`maximum value) and the Subsequent valley (i.e. minimum
`value) of pulse oximeter signal 320. The actual systolic
`period is identified in FIG. 3C as well as the dichrotic notch
`of the next pulse.
`0046.
`After the systolic period has been identified, unique
`pulse qualification tests based upon typical physiological
`pulse characteristics are applied to the systole pulse at Step
`206. The full pulse qualification tests remove false positive
`systolic detections (e.g., the dichrotic notch) and pulses that
`have an inadequate signal-to-noise ratio. False positives are
`portions of the signal that are falsely identified as systolic
`transitions in step 205. Pulse qualifications are used in step
`
`007
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`206 to filter out false positives identified in step 205. The
`steps of FIG. 2 can be implemented in software or hardware.
`0047 Pulse qualification tests qualify cardiac pulses in
`the pulse oximeter signal. The pulse qualification tests are
`designed to identify cardiac pulses that have adequate sig
`nal-to-noise ratio for use in measuring pulse rate and blood
`oxygen Saturation. The pulse qualification tests can include
`any number techniques including traditional pulse qualifi
`cation techniques.
`0.048. Some examples of pulse qualification tests accord
`ing to particular embodiments of the present invention are
`now discussed. The qualifications are comparisons of spe
`cial pulse characteristics to determined threshold values. For
`example, the pulse qualifications compare systolic area,
`width, and number of sub-peaks to fixed thresholds. Dias
`tolic area, width, and number of Sub-peaks are compared to
`thresholds. Systolic area and width are compared to diastolic
`area and width. Pulse area and width are compared to
`thresholds. All of the above individually are compared to the
`last N pulses detected.
`0049 Pulses that pass these qualifications can be used to
`measure pulse rate. To qualify the systolic periods for
`oxygen Saturation calculations, the following additional
`qualifications are used. The lag/lead time between the infra
`red and red pulse detection are compared. The pulse size is
`compared to the N pulses qualified. The statistically signifi
`cant coefficient of the best-fit line plot of the moving average
`between the infrared and the red signals is compared to fixed
`thresholds. The Saturation rate-of-change is compared to
`fixed thresholds. Pulses that pass these additional qualifica
`tions can be used to measure oxygen Saturation.
`0050. After the pulse qualification tests have filtered out
`false positives, the systolic periods are identified. The sys
`tolic periods represent a signal component of the pulse
`Oximeter signal. The signal-to-noise ratio of the pulse
`Oximeter signal is calculated by comparing the strength of
`the systolic period to the noise component of the pulse
`Oximeter signal.
`0051. According to one embodiment, the noise compo
`nent of a pulse oximeter sensor is calculated in advance
`using a separate instrument that measures noise in the pulse
`Oximeter signal at various gain values. The measured noise
`component is then stored in memory for later use. The stored
`noise component is Subsequently compared to the size of the
`systolic pulse for a particular gain value to determine the
`signal-to-noise ratio of the pulse oximeter signal.
`0.052 According to another embodiment, dynamic mea
`Surements of the noise of the pulse oximeter system are
`made. These noise measurements can include electrical
`noise, ambient noise caused by ambient light, and/or noise
`(e.g. motion) caused by the patient. The dynamic noise
`measurement is updated continuously throughout the opera
`tion of the pulse oximeter sensor. An updated noise com
`ponent is continuously compared to the pulse to calculate a
`more accurate signal-to-noise ratio of the pulse oximeter
`signal.
`0053) Once the signal-to-noise ratio of the pulse oximeter
`signal has been calculated, a determination is made as
`whether the signal-to-noise ratio falls within an acceptable
`range. The acceptable range is selected based on the relative
`noise component for accurately calculating oxygen Satura
`
`tion and pulse rate. If the ratio is outside the acceptable
`range, the feedback loop discussed above with respect to
`FIG. 1 adjusts the LED drive current to bring the signal-to
`noise ratio within the acceptable range.
`0054 The present invention has the advantage of requir
`ing fewer servo executions to acquire and maintain the
`oxygen Saturation of the signal than many prior art tech
`niques, particularly in the presence of patient motion inter
`ference. In many prior art oximeter systems, the LEDs are
`driven with a large current, and the pulse oximeter signal
`fills up its entire system dynamic range. The oximeter signal
`exceeds the system’s current dynamic range as soon as the
`patient starts moving, and the signal is effectively lost (i.e.,
`flat-line, invalid signal). Additional servo executions are
`required to re-acquire the signal. While the servo is execut
`ing, the sensor signal is not available; therefore, the oximeter
`cannot calculate pulse rate or oxygen Saturation data from
`the pulse Oximeter signal.
`0055. On the other hand, the LED drive current is sub
`stantially reduced in the present invention. The dynamic
`range is greatly increased relative to the size of the pulse
`Oximeter signal, because the signal has been greatly reduced
`by cutting back on the LED drive current. The oximeter
`signal can now move around more within the dynamic range
`without requiring additional servo executions or changes to
`the LED settings. In the present invention, the patient can
`move around vigorously without causing the servo to
`execute in an attempt to re-acquire the signal. The tech
`niques of the present invention can allow an oximeter
`system to be much more tolerant of patient motion.
`0056 Pulse detection block 102 can include a transim
`pedance (I-V) amplifier or converter 401 that converts a
`current signal from photodetector 112 to a Voltage signal as
`shown in FIG. 4. Ambient light in the environment adds a
`component of DC bias into the pulse oximeter signal. This
`DC bias shifts the pulse oximeter signal higher, closer to the
`rail of the dynamic range of the transimpedance amplifier.
`0057 According to an embodiment of the present inven
`tion, an analog-to-digital (A-to-D) converter 402 Samples
`the output signal of transimpedance amplifier 401 during a
`time when either LED 110-111 is on or off to provide a
`continuous, real-time measurement of the ambient light and
`or noise that gets into sensor 101. This feature can also be
`used to provide information on the magnitude of the signal
`at the output of A-to-D converter 402.
`0058. The information about the signal magnitude from
`A-to-D converter 402 is fed back through gain control
`feedback loop 403 and used to choose an appropriate gain
`for transimpedance amplifier 401. For example, gain control
`feedback loop 403 causes the transimpedance gain of tran
`simpedance amplifier 401 to increase or decrease to reduce
`and/or accommodate the effect of the environmental DC bias
`on the signal. This real-time measurement can also be used
`for determining a sensor-off condition, measuring electrical
`and optical noise, detecting transients in the signal, and
`detecting patient motion.
`0059. During the normal operation of the sensor, the
`LEDs can be pulsed on and off in any desired manner to
`provide the continuous (multiplexed), real-time measure
`ment of the ambient light and other noise sources. For
`example, one red and one infrared LED can be alternately
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`turned on and off in the following manner: red LED on and
`infrared LED off, then red LED off and infrared LED on,
`then both LEDs off, then red LED on and infrared LED off,
`etc., repeating in this sequence. As another example, one red
`and one infrared LED can be alternately turned on and off as
`follows: red LED on and infrared LED off, then both LEDs
`off, then red LED off and infrared LED on, then both LEDs
`off, then red LED on and infrared LED off, etc. repeating in
`this sequence. These patterns are examples that are not
`intended to limit the scope of the present invention.
`0060 Sigma-delta modulator 410 also receives the output
`signal of the transimpedance amplifier 402. Modulator 410
`demodulates the signal from the photodetector into separate
`red and infrared components. The demodulation function
`can be performed in the digital domain using a Software or
`firmware program run by a microcontroller. Further details
`of a Multi-Bit ADC With Sigma-Delta Modulation are
`discussed in commonly assigned, co-pending U.S. patent
`application Ser. No.
`to Ethan Petersen et al., filed
`concurrently herewith, (Attorney Docket Number 009103
`020300US), which is incorporated by reference herein.
`0061 As will be understood by those of skill in the art,
`the present invention could be embodied in other specific
`forms without departing from the essential characteristic
`thereof. Accordingly, the foregoing description is intended
`to be illustrative, but not limiting, on the scope of the
`invention which is set forth in the following claims.
`0062 For example, the components in pulse detection
`block 102 that are shown in FIG. 4 can be implemented in
`systems other than pulse Oximeter systems. These compo
`nents can reduce the effect of noise in signals from other
`types of sensors as well.
`1. A pulse oximeter system comprising:
`a drive interface that controls drive current of light
`emitting elements in a pulse Oximeter sensor; and
`a feedback loop coupled around the pulse oximeter sensor
`and the drive interface that dynamically adjusts the
`drive current of the light emitting elements based on
`results of a comparison between a signal-to-noise ratio
`of a pulse oximeter signal and a threshold,
`wherein the pulse oximeter signal is generated by a
`photodetector in the pulse oximeter sensor.
`2. The pulse oximeter system as defined in claim 1
`wherein the feedback loop causes the drive current of the
`Light emitting elements to decrease if the signal