US20150351697A1 - Variable indication estimator - Google Patents

Variable indication estimator Download PDF

Info

Publication number
US20150351697A1
US20150351697A1 US14/830,211 US201514830211A US2015351697A1 US 20150351697 A1 US20150351697 A1 US 20150351697A1 US 201514830211 A US201514830211 A US 201514830211A US 2015351697 A1 US2015351697 A1 US 2015351697A1
Authority
US
United States
Prior art keywords
signal
time
value
values
mode
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Abandoned
Application number
US14/830,211
Inventor
Walter M. Weber
Ammar Al-Ali
Lorenzo Cazzoli
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Masimo Corp
Original Assignee
Masimo Corp
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Priority to US09/586,845 priority Critical patent/US6430525B1/en
Priority to US10/213,270 priority patent/US6999904B2/en
Priority to US11/375,662 priority patent/US7499835B2/en
Priority to US12/362,463 priority patent/US7873497B2/en
Priority to US13/007,109 priority patent/US8260577B2/en
Priority to US13/601,930 priority patent/US8489364B2/en
Priority to US13/942,562 priority patent/US9138192B2/en
Application filed by Masimo Corp filed Critical Masimo Corp
Priority to US14/830,211 priority patent/US20150351697A1/en
Publication of US20150351697A1 publication Critical patent/US20150351697A1/en
Application status is Abandoned legal-status Critical

Links

Images

Classifications

    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/72Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7271Specific aspects of physiological measurement analysis
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/0002Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/02Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
    • A61B5/021Measuring pressure in heart or blood vessels
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/145Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue
    • A61B5/1455Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue using optical sensors, e.g. spectral photometrical oximeters
    • A61B5/14551Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue using optical sensors, e.g. spectral photometrical oximeters for measuring blood gases
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/68Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient
    • A61B5/6801Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient specially adapted to be attached to or worn on the body surface
    • A61B5/6813Specially adapted to be attached to a specific body part
    • A61B5/6825Hand
    • A61B5/6826Finger
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/68Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient
    • A61B5/6801Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient specially adapted to be attached to or worn on the body surface
    • A61B5/6813Specially adapted to be attached to a specific body part
    • A61B5/6829Foot or ankle
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/68Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient
    • A61B5/6801Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient specially adapted to be attached to or worn on the body surface
    • A61B5/683Means for maintaining contact with the body
    • A61B5/6838Clamps or clips
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/72Signal processing specially adapted for physiological signals or for diagnostic purposes
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/00496Recognising patterns in signals and combinations thereof
    • G06K9/00503Preprocessing, e.g. filtering
    • G06K9/0051Denoising
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/145Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue
    • A61B5/1455Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue using optical sensors, e.g. spectral photometrical oximeters
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/72Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7203Signal processing specially adapted for physiological signals or for diagnostic purposes for noise prevention, reduction or removal
    • A61B5/7207Signal processing specially adapted for physiological signals or for diagnostic purposes for noise prevention, reduction or removal of noise induced by motion artifacts
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/72Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7235Details of waveform analysis
    • A61B5/7239Details of waveform analysis using differentiation including higher order derivatives

Abstract

A variable indication estimator which determines an output value representative of a set of input data. For example, the estimator can reduce input data to estimates of a desired signal, select a time, and determine an output value from the estimates and the time. In one embodiment, the time is selected using one or more adjustable signal confidence parameters determine where along the estimates the output value will be computed. By varying the parameters, the characteristics of the output value are variable. For example, when input signal confidence is low, the parameters are adjusted so that the output value is a smoothed representation of the input signal. When input signal confidence is high, the parameters are adjusted so that the output value has a faster and more accurate response to the input signal.

Description

    INCORPORATION BY REFERENCE TO ANY PRIORITY APPLICATIONS
  • Any and all applications, if any, for which a foreign or domestic priority claim can be identified in the Application Data Sheet of the present application is hereby incorporated by reference under 37 CFR 1.57.
  • FIELD OF THE INVENTION
  • The present invention is directed to the field of signal processing, and, more particularly, is directed to systems and methods for determining a representative estimate output value for a window of input data.
  • BACKGROUND OF THE INVENTION
  • Digital signal processing techniques are frequently employed to enhance a desired signal in a wide variety of applications, such as health care, communications and avionics, to name a few. Signal enhancement includes smoothing, filtering and prediction. These processing techniques each operate on a block of input signal values, such as, for example, a window of input signal values, in order to estimate the signal at a specific point in time. FIG. 1 illustrates that smoothing, filtering and prediction can be distinguished by the time at which an output value is generated relative to input values. Shown in FIG. 1 is a time axis 100 and a block 101 of input signal values depicted in this example as occurring within a time window between points tmin and tmax. Specifically, the block 101 includes a set of discrete input values {vi; i=1, 2, . . . n} occurring at a corresponding set of time points {ti; i=1, 2, . . . n}. A smoother operates on the block 101 of input values to estimate the signal at a time point, ts 102 between tmin and tmax. That is, a smoother generates an output value based upon input values occurring before and after the output value. A filter operates on the block 101 of input values to estimate the signal at a time tf 104, corresponding to the most recently occurring input value in the block 101. That is, a filter generates a forward filtered output value at the time tf based upon input values occurring at, and immediately before, the output value. A filter also operates on the block 101 to estimate the signal at a time tb 105 at the beginning of the block 101 to generate a backward filtered value. A forward predictor operates on the block of input values 101 to estimate the signal at time tpf 106, which is beyond the most recently occurring value in the block 101. That is, a forward predictor generates a forward predicted output value based upon input values occurring prior to the output value. A backward predictor operates on the block 101 of input values to estimate the signal at time tpb 108, which is before the earliest occurring value in the block 101. That is, a backward predictor generates a backward predicted output value based upon input values occurring after the output value.
  • SUMMARY OF THE INVENTION
  • A common smoothing technique uses an average to fit a constant, vA, to a set of data values, {vi; i=1, 2, . . . , n}:
  • v A = 1 n · i = 1 n v i ( 1 )
  • A generalized form of equation (1) is the weighted average
  • v WA = i = 1 n w i · v i i = 1 n w i ( 2 )
  • Here, each value, vi, is scaled by a weight, wi, before averaging. This allows data values to be emphasized and de-emphasized relative to each other. If the data relates to an input signal, for example, values occurring during periods of low signal confidence can be given a lower weight and values occurring during periods of high signal confidence can be given a higher weight.
  • FIG. 2A illustrates the output of a constant mode averager, which utilizes the weighted average of equation (2) to process a discrete input signal, {vi; i an integer} 110. The input signal 110 may be, for example, a desired signal corrupted by noise or a signal having superfluous features. The constant mode averager suppresses the noise and unwanted features, as described with respect to FIG. 5, below. A first time-window 132 defines a first set, {vi; i=1, 2, . . . , n}, of signal values, which are averaged together to produce a first output value, z1 122. A second time-window 134, shifted from the previous window 132, defines a second set {vi; i=2, 3, . . ., n+1}of signal values, which are also averaged together to produce a second output value z2 124. In this manner, a discrete output signal, {zj; j an integer} 120 is generated from a moving weighted average of a discrete input signal {vi; i an integer} 110, where:
  • z j = i = j n + j - 1 w i v i / i = j n + j - 1 w i ( 3 )
  • A common filtering technique computes a linear fit to a set of data values, {vi; i=1, 2, . . . , n}:

  • {circumflex over (v)} i =α·t i+β  (4)
  • where α and β are constants and ti is the time of occurrence of the ith value. FIG. 2B illustrates the output of a linear mode averager, which uses the linear fit of equation (4) to process a discrete input signal, {vi; i an integer} 110. The input signal 110 may be, for example, a desired signal with important features corrupted by noise. The linear mode averager reduces the noise but tracks the important features, as described with respect to FIG. 6 below. A first time-window 132 defines a first set, {vi; i=1, 2, . . . , n}, of signal values. A linear fit to these n values is a first line 240, and the value along this line at max{t1, t2, . . . , tn} is equal to a first output value, z1 222. A second time-window 134 shifted from the previous window 132 defines a second set, {vi; i=2, 3, . . . , n+1}, of signal values. A linear fit to these n values is a second line 250, and the value along this line at max{t2, t3, . . . , tn+1} is equal to a second output value, z2 224. In this manner, a discrete output signal, {zj; j an integer} 220 is generated from a moving linear fit of a discrete input signal {vi; i an integer}, where:
  • z j = α j · t n + j - 1 MAX + β j ( 5 a ) t n + j - 1 MAX = max { t j , t j + 1 , , t n + j - 1 } ( 5 b )
  • In general, the time windows shown in FIGS. 2A-2B may be shifted from each other by more than one input value, and values within each time window may be skipped, i.e., not included in the average. Further, the ti's may not be in increasing or decreasing order or uniformly distributed, and successive time windows may be of different sizes. Also, although the discussion herein refers to signal values as the dependent variable and to time as the independent variable to facilitate disclosure of the present invention, the concepts involved are equally applicable where the variables are other than signal values and time. For example, an independent variable could be a spatial dimension and a dependent variable could be an image value.
  • The linear mode averager described with respect to FIG. 2B can utilize a “best” linear fit to the input signal, calculated by minimizing the mean-squared error between the linear fit and the input signal. A weighted mean-squared error can be described utilizing equation (4) as:
  • ɛ ( α , β ) = i = 1 n w i ( v i - v ^ i ) 2 / i = 1 n w i ( 6 a ) ɛ ( α , β ) = i = 1 n w i [ v i - ( α · t i + β ) ] 2 / i = 1 n w i ( 6 b )
  • Conventionally, the least-mean-squared (LMS) error is calculated by setting the partial derivatives of equation (6b) with respect to α and β to zero:
  • α ɛ ( α , β ) = 0 ( 7 a ) β ɛ ( α , β ) = 0 ( 7 b )
  • Substituting equation (6b) into equation (7b) and taking the derivative yields:
  • - 2 i = 1 n w i [ v i - ( α · t i + β ) ] / i = 1 n w i = 0 ( 8 )
  • Solving equation (8) for β and substituting the expression of equation (2) yields:
  • β = i = 1 n w i · v i i = 1 n w i - α i = 1 n w i · t i i = 1 n w i ( 9 a ) β = v WA - α · t WA ( 9 b )
  • where the weighted average time, tWA, is defined as:
  • t WA = i = 1 n w i · t i i = 1 n w i ( 10 )
  • Substituting equation (9b) into equation (4) gives:

  • {circumflex over (v)} i=α(t i −t WA)+v WA   (11)
  • Substituting equation (11) into equation (6a) and rearranging terms results in:
  • ɛ ( α , β ) = i = 1 n w i [ ( v i - v WA ) - α · ( t i - t WA ) ] 2 / i = 1 n w i ( 12 )
  • Changing variables in equation (12) gives:
  • ɛ ( α , β ) = i = 1 n w i ( v i - α · t i ) 2 / i = 1 n w i ( 13 )
  • where:

  • v′ i =v i −v WA   (14a)

  • t′ i =t i −t WA   (14b)
  • Substituting equation (13) into equation (7a) and taking the derivative yields
  • - 2 i = 1 n w i t i ( v i - α · t i ) / i = 1 n w i = 0 ( 15 )
  • Solving equation (15) for a gives:
  • α = i = 1 n w i v i t i / i = 1 n w i i = 1 n w i t i 2 / i = 1 n w i ( 16 )
  • Substituting equations (14a, b) into equation (16) results in:
  • α = i = 1 n w i ( v i - v WA ) ( t i - t WA ) / i = 1 n w i i = 1 n w i ( t i - t WA ) 2 / i = 1 n w i ( 17 a ) α = σ vt 2 σ tt 2 ( 17 b )
  • where:
  • σ vt 2 = i = 1 n w i ( v i - v WA ) ( t i - t WA ) / i = 1 n w i ( 18 a ) σ tt 2 = i = 1 n w i ( t i - t WA ) 2 / i = 1 n w i ( 18 b )
  • Finally, substituting equation (17b) into equation (11) provides the equation for the least-mean-square (LMS) linear fit to {vi, i=1, 2, . . . , n}:
  • v ^ i = σ vt 2 σ tt 2 ( t i - t WA ) + v WA ( 19 )
  • FIG. 3 provides one comparison between the constant mode averager, described above with respect to FIG. 2A and equation (2), and the linear mode averager, described above with respect to FIG. 2B and equation (19). Shown in FIG. 3 are input signal values {vi=1, 2, . . . , n} 310. The constant mode averager calculates a constant 320 for these values 310, which is equal to vWA, the weighted average of the input values vi. Thus, the constant mode averager output 340 has a value VWA. For comparison to the linear mode averager, the constant mode averager output can be conceptualized as an estimate of the input values 310 along a linear fit 350, evaluated at time tWA. The linear mode averager may be thought of as calculating a LMS linear fit, {circumflex over (v)}i 330 to the input signal values, vi 310. The linear mode averager output 350 has a value, The linear mode averager output is an estimate of the input values 310 along the linear fit 330, described by equation (19), evaluated at an index i such that ti=tMAX.
  • v WLA = σ vt 2 σ tt 2 ( t MAX - t WA ) + v WA ( 20 )
  • where:

  • t MAX =max {t 1 , t 2 , . . . , t n}  (21)
  • As illustrated by FIG. 3, unlike the constant mode averager, the linear mode averager is sensitive to the input signal trend. That is, the constant mode averager provides a constant fit to the input values, whereas the linear mode averager provides a linear fit to the input values that corresponds to the input value trend. As a result, the output of the linear mode averager output responds faster to changes in the input signal than does the output of the constant mode averager. The time lag or delay between the output of the constant mode averager and the output of the linear mode averager can be visualized by comparing the time difference 360 between the constant mode averager output value 340 and the linear mode averager output value 350.
  • FIGS. 4-6 illustrate further comparisons between the constant mode averager and the linear mode averager. FIG. 4 depicts a noise-corrupted input signal 410, which increases in frequency with time. FIGS. 5-6 depict the corresponding noise-free signal 400. FIG. 5 also depicts the constant mode averager output 500 in response to the input signal 410, with the noise-free signal 400 shown for reference. FIG. 6 depicts the linear mode averager output 600 in response to the input signal 410, with the noise-free signal 400 also shown for reference. As shown in FIG. 5, the constant mode averager output 500 suppresses noise from the input signal 410 (FIG. 4) but displays increasing time lag and amplitude deviation from the input signal 400 as frequency increases. As shown in FIG. 6, the linear mode averager output 600 tends to track the input signal 400 but also tracks a portion of the noise on the input signal 410.
  • FIGS. 4-6 suggest that it would be advantageous to have an averager that has variable characteristics between those of the linear mode averager and those of the constant mode averager, depending on signal confidence. Specifically, it would be advantageous to have a variable mode averager that can be adjusted to track input signal features with a minimal output time lag when signal confidence is high and yet adjusted to smooth an input signal when signal confidence is low. Further, it would be advantageous to have a variable mode averager that can be adjusted so as not to track superfluous input signal features regardless of signal confidence.
  • One aspect of the present invention is a variable mode averager having a buffer that stores weighted input values. A mode input specifies a time value relative to the input values. A processor is coupled to the buffer, and the processor is configured to provide an estimate of the input values that corresponds to the time value. In a particular embodiment, the mode input is adjustable so that the estimate varies between that of a smoother and that of a forward predictor of the input values. In another embodiment, the mode input is adjustable so that the estimate varies between that of a smoother and that of a filter of the input values. In yet another embodiment, the mode input is adjustable so that the estimate varies between that of an average of the input values and that of a filter of the input values. The mode input may be adjustable based upon a characteristic associated with the input values, such as a confidence level. In one variation of that embodiment, the estimate can be that of a smoother when the confidence level is low and that of a filter when the confidence level is high. The estimate may occur along a curve-fit of the input values at the time value. In one embodiment, the curve-fit is a linear LMS fit to the input values.
  • Another aspect of the present invention is a signal averaging method. The method includes identifying signal values and determining weights corresponding to the signal values. The method also includes computing a trend of the signal values adjusted by the weights. Further, the method includes specifying a time value relative to the signal values based upon a characteristic associated with the signal values and estimating the signal values based upon the trend evaluated at the time value. The method may also incorporate the steps of determining a confidence level associated with the signal values and specifying the time value based upon the confidence level. In one embodiment, the trend is a linear LMS fit to the signal values adjusted by the weights. In that case, the time value may generally correspond to the maximum time of the signal values when the confidence level is high and generally correspond to the weighted average time of the signal values when the confidence level is low.
  • Yet another aspect of the present invention is a signal averaging method having the steps of providing an input signal, setting a mode between a first mode value and a second mode value and generating an output signal from an estimate of the input signal as a function of said mode. The output signal generally smoothes the input signal when the mode is proximate the first mode value, and the output signal generally tracks the input signal when the mode is proximate the second mode value. The method may also include determining a characteristic of the input signal, where the setting step is a function of the characteristic. In one embodiment, the characteristic is a confidence level relating to the input signal. In another embodiment, the setting step incorporates the substeps of setting the mode proximate the first mode value when the confidence level is low and setting the mode proximate the second mode value when the confidence level is high. In another embodiment, the input signal is a physiological measurement and the setting step comprises setting the mode proximate the first mode value when the measurement is corrupted with noise or signal artifacts and otherwise setting the mode proximate the second mode value so that the output signal has a fast response to physiological events.
  • A further aspect of the present invention is a signal averager having an input means for storing signal values, an adjustment means for modifying the signal values with corresponding weights, a curve fitting means for determining a trend of the signal values, and an estimate means for generating an output value along the trend. The signal averager may further have a mode means coupled to the estimate means for variably determining a time value at which to generate the output value.
  • For purposes of summarizing the invention, certain aspects, advantages and novel features of the invention have been described herein. Of course, it is to be understood that not necessarily all such aspects, advantages or features will be embodied in any particular embodiment of the invention.
  • BRIEF DESCRIPTION OF THE DRAWINGS
  • A general architecture that implements the various features of the invention will now be described with reference to the drawings. The drawings and the associated descriptions are provided to illustrate embodiments of the invention and not to limit the scope of the invention. Throughout the drawings, reference numbers are re-used to indicate correspondence between referenced elements. In addition, the first digit of each reference number indicates the figure in which the element first appears.
  • FIG. 1 is a time graph depicting the output of conventional smoother, filter and predictor signal processors;
  • FIG. 2A is an amplitude versus time graph depicting the output of a conventional constant mode averager;
  • FIG. 2B is an amplitude versus time graph depicting the output of a conventional linear mode averager;
  • FIG. 3 is an amplitude versus time graph comparing the outputs of a constant mode averager and a linear mode averager;
  • FIG. 4 is an amplitude versus time graph depicting a noisy input signal;
  • FIG. 5 is an amplitude versus time graph depicting a constant mode averager output signal corresponding to the input signal of FIG. 4;
  • FIG. 6 is an amplitude versus time graph depicting a linear mode averager output signal corresponding to the input signal of FIG. 4;
  • FIG. 7 is an amplitude versus time graph illustrating the characteristics of one embodiment of the variable mode averager;
  • FIG. 8 is a flow chart of a variable mode averager embodiment;
  • FIG. 9 is a block diagram illustrating a variable mode averager applied to a pulse oximeter; and
  • FIG. 10 is an oxygen saturation output versus time graph for a pulse oximeter utilizing a variable mode averager.
  • FIG. 11 is a flow chart of an output value selection process of a signal processor, according to an embodiment of the invention.
  • FIG. 12 is an amplitude versus time graph depicting exemplary potential output values of the output value selection process of FIG. 11, according to an embodiment of the invention.
  • DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS
  • FIG. 7 illustrates the output characteristics of a variable mode averager according to the present invention. The output of the variable mode averager is a mode-dependent weighted linear average (MWLA) defined as
  • v MWLA = mode · σ vt 2 σ tt 2 ( t MAX - t WA ) + v WA ( 22 )
  • Equation (22) is a modified form of equation (20), which is motivated by equations (2) and (19) along with recognition of the relationships in Table 1.
  • TABLE 1
    VARIABLE MODE AVERAGER OUTPUT
    mode = 0 mode = 1 any mode ∃ 0
    Processing Constant Mode Linear Mode Variable Mode
    Function Averager Averager Averager
    Output vWA vWLA vMWLA
    Defining Formula Equation (2) Equation (20) Equation (22)
    Processing Method Weighted LMS Linear Fit FIG. 8
    Average
  • As shown in Table 1, the Variable Mode Averager in accordance with the present invention includes the constant mode averager processing function and the linear mode averager processing function, which are known processing functions. As further shown in Table 1, the Variable Mode Averager of the present invention also includes a variable mode averager processing function, which will be described below.
  • As shown in Table 1, if mode=0, the variable mode averager output is vWA, the output of the constant mode averager function, which utilizes a weighted average of the input signal values. If mode=1, the variable mode averager output is VWLA, the output of the linear mode averager function, which utilizes a LMS linear fit to the input signal values. If 0<mode<1, then the variable mode averager output is VMWLA and has output characteristics that are between that of the constant mode averager and the linear mode averager. In addition, if mode>1, then the variable mode averager behaves as a forward predictor.
  • As shown in FIG. 7, the variable mode averager output 720 is an estimate of the input values at a selected time along the linear fit 710, which indicates a trend of the input values. Assuming 0<mode<1, the mode variable determines the equivalent time 730 between tWA and tMAX for which the estimate is evaluated, yielding an output value 740 between VWA and VWLA. Thus, the mode variable acts to parametrically vary the time delay between the input and output signals of the variable mode averager, along with associated output characteristics. If mode=0, the time delay 360 (FIG. 3) is that of the constant mode averager. If mode=1, there is no time delay. If mode>1, the variable mode averager is predicting a future input value based on n past values. In this manner, the variable mode averager can be used to advantageously adjust between the smoothing characteristics of the constant mode averager and the tracking characteristics of the linear mode averager, as described above with respect to FIGS. 4-6. The variable mode control determines how much of each particular characteristic to use for a particular input signal and application. For example, for time periods when the input signal has low confidence, mode can be set further towards zero, although with a time lag penalty. For time periods when the input signal has high confidence or when minimum time lag is required, mode can be set further towards one, or even to a value greater than one.
  • The variable mode averager has been described in terms of weighted input values. One of ordinary skill, however, will recognize that the present invention includes the case where all of the weights are the same, i.e., where the input values are equally weighted or unweighted. Further, although the variable mode averager has been described in terms of a linear mode averager, one of ordinary skill in the art will recognize that a variable mode averager could also be based on non-linear curve fits, such as exponential or quadratic curves indicating a non-linear trend of the input signal. In addition, one of ordinary skill will understand that the variable mode averager can be implemented to operate on continuous data as well as infinitely long data. Also, a variable mode averager based upon a linear fit by some criteria other than LMS; a variable mode averager using any mode value, including negative values; and a variable mode averager based upon a linear fit where tmin=min {t1, t2, . . . tn} is substituted for tMAX in equation (22) are all contemplated as within the scope of the present invention.
  • FIG. 8 illustrates one embodiment 800 of a variable mode signal averager. After an entry point 802, variables are initialized to zero in a block 808. Next, in a block 812, the sums of various parameters are calculated by summing the products of corresponding values in each of three buffers: an input data buffer, value[i]; a weight buffer, weight[i]; and a time value buffer, time[i]. In addition, the weight[i] values are summed. These sums are calculated over the entire length of each buffer, representing a single time window of n values. The calculations are performed by incrementing a loop counter i in a block 810 and reentering the block 812. The loop counter i specifies a particular value in each buffer. Each time through the block 812, the variable mode signal averager generates products of buffer values and adds the results to partial sums. After completing the partial sums, the variable mode signal averager then determines if the ends of the buffers have been reached in a decision block 814 by comparing the incremented value of i to the size of the buffer. If the ends of the buffers have not been reached, the variable mode averager increments the loop counter i and reenters the block 812; otherwise, the variable mode averager continues to a decision block 816.
  • In the decision block 816, a check is made whether the sum of the weights, sumw, is greater than zero. If so, each of the sums of the products from the block 812 is divided by sumw in a block 820. In the block 820, the parameters computed are:
  • sumwv, the weighted average value of equation (2);
  • sumwt, the weighted average time of equation (10);
  • sumwvt, the weighted average product of value and time; and
  • sumwt2, the weighted average product of time squared.
  • The sumwt2 parameter from the block 820 is then used in a block 822 to calculate an autovariance sigma2tt in accordance with equation (18b). If, in a decision block 824, a determination is made that the autovariance is not greater than zero, then in a decision block 825, a determination is made whether the sum of the weights is greater than zero. If, in the decision block 825, the sum of the weights is not greater than zero, then an output value, out, which was initialized to zero in the block 808, is returned as a zero value at a termination point 804. Otherwise, if, in the decision block 825, a determination is made that the sum of the weights is greater than zero, then in a block 826, the value of the sum of the weights is assigned to the output value, out, and the output value is then returned at the termination point 804.
  • If, in the decision block 824, the autovariance is determined to be greater than zero, then in a block 827, the sumwvt parameter from the block 820 is used to calculate a crossvariance signal sigma2vt in accordance with equation (18a). Thereafter, the maximum time, tMAX, as defined in equation (21), is determined by finding the largest time value in the time buffer, time[i]. In particular, in a block 829, the loop counter, i, is reinitialized to zero and the value of tMAX is initialized to zero. Next, in a decision block 832, the current value of tMAX is compared to the current value of the time buffer indexed by the loop counter, i. If the current value of tMAX is not less than the current value of the time buffer or if the current weight value indexed by i is not greater than zero, then tMAX is not changed and a block 834 is bypassed. On the other hand, if the current value of tMAX is less than the current time value and if the current weight value is greater than zero, then the block 834 is entered, and the value of tMAX is replaced with the current time value time[i]. In either case, in a decision block 838, the loop counter, i, is compared to the buffer size, and, if the loop counter, i, is less than the buffer size, the loop counter, i, is incremented in a block 830, and the comparisons are again made in the decision block 832.
  • When, in the decision block 838, it is determined that the loop counter, i, has reached the buffer size, the variable mode averager proceeds to a block 840 with the largest value of time[i] saved as the value of tMAX. In the block 840, a single output value, out, is computed in accordance with equation (22). Thereafter, the output value, out, is limited to the range of values in the input data buffer, value[i]. This is accomplished by comparing out to the maximum and minimum values in the data buffer. First, in a block 850, the maximum of the value buffer is determined. Then, in a decision block 852, the maximum of the value buffer is compared to out. If out is bigger than the maximum of the value buffer, then, in a block 854, out is limited to the maximum value in the buffer. Otherwise, the block 854 is bypassed, and out remains as previously calculated in the block 840. Thereafter, in a block 860, the minimum of the value buffer is determined. The minimum of the value buffer is compared to out in a decision block 862. If out is smaller than the minimum of the value buffer, then, in a block 864, out is set to the minimum value in the buffer. Otherwise, the block 864 is bypassed, and out is not changed. The value of out determined by the block 840, the block 852 or the block 864 is then returned from the routine via the termination point 804.
  • In one embodiment, the process described with respect to FIG. 8 is implemented as firmware executing on a digital signal processor. One of ordinary skill in the art will recognize that the variable mode averager can also be implemented as a digital circuit. Further, a variable mode averager implemented as an analog circuit with analog inputs and outputs is also contemplated to be within the scope of the present invention.
  • Pulse oximetry is one application that can effectively use signal processing techniques to provide caregivers with improved physiological measurements. Pulse oximetry is a widely accepted noninvasive procedure for measuring the oxygen saturation level of arterial blood, an indicator of oxygen supply. Early detection of low blood oxygen is critical in the medical field, for example in critical care and surgical applications, because an insufficient supply of oxygen can result in brain damage and death in a matter of minutes. Pulse oximeter systems are described in detail in U.S. Pat. No. 5,632,272, U.S. Pat. No. 5,769,785, and U.S. Pat. No. 6,002,952, which are assigned to the assignee of the present invention and which are incorporated by reference herein.
  • FIG. 9 depicts a general block diagram of a pulse oximetry system 900 utilizing a variable mode averager 960. A pulse oximetry system 900 consists of a sensor 902 attached to a patient and a monitor 904 that outputs desired parameters 982 to a display 980, including blood oxygen saturation, heart rate and a plethysmographic waveform. Conventionally, a pulse oximetry sensor 902 has both red (RED) and infrared (IR) light-emitting diode (LED) emitters (not shown) and a photodiode detector (not shown). The sensor 902 is typically attached to a patient's finger or toe, or to a very young patient's foot. For a finger, the sensor 902 is configured so that the emitters project light through the fingernail and into the blood vessels and capillaries underneath. The photodiode is positioned at the fingertip opposite the fingernail so as to detect the LED transmitted light as it emerges from the finger tissues, producing a sensor output 922 that indicates arterial blood absorption of the red and infrared LED wavelengths.
  • As shown in FIG. 9, the sensor output 922 is coupled to analog signal conditioning and an analog-to-digital conversion (ADC) circuit 920. The signal conditioning filters and amplifies the analog sensor output 922, and the ADC provides discrete signal values to the digital signal processor 950. The signal processor 950 provides a gain control 952 to amplifiers in the signal conditioning circuit 920. The signal processor 950 also provides an emitter control 954 to a digital-to-analog conversion (DAC) circuit 930. The DAC 930 provides control signals for the emitter current drivers 940. The emitter drivers 940 couple to the red and infrared LEDs in the sensor 902. In this manner, the signal processor 950 can alternately activate the sensor LED emitters and read the resulting output 922 generated by the photodiode detector.
  • The digital signal processor 950 determines oxygen saturation by computing the differential absorption by arterial blood of the red and infrared wavelengths emitted by the sensor 902. Specifically, the ADC 920 provides the processor 950 with a digitized input 924 derived from the sensor output 922. Based on this input 924, the processor 950 calculates ratios of detected red and infrared intensities. Oxygen saturation values, vi, are empirically determined based on the calculated red and infrared ratios. These values are an input signal 962 to the variable mode averager 960. Each of the input values, vi, are associated with weights, wi, which form a second input 964 to the averager 960. The individual weights, wi, are indicative of the confidence in particular ones of the corresponding saturation values, vi. A third input 974 sets the mode of the averager 960. The variable mode averager 960 processes the values, vi, weights, wi, and mode as described above with respect to FIGS. 7-8 to generate values, zi. The values zi are the averager output 968, from which is derived the saturation output 982 to the display 980.
  • The mode signal may be generated by an external source (not shown) or it may be generated by another function within the digital signal processor. For example, mode may be generated from the confidence level of the input signal as illustrated in FIG. 9. FIG. 9 illustrates a signal confidence input 972 to a mode control process 970. The mode control process 970 maps the signal confidence input 972 to the mode input 974 of the variable mode averager 960. When the signal confidence is low, the mode control 970 sets mode to a relatively small value. Depending on the application, mode may be set close to zero. When the signal confidence is high, the mode control 970 sets mode to a relatively large value. Some applications may prefer a mode of one for a high signal confidence, but this is not a requirement. When the signal confidence is neither high nor low, mode is set to an intermediate value (in some applications, mode may be set to a value between zero and one) empirically to achieve a reasonable tradeoff between a fast saturation output response and saturation accuracy.
  • The signal quality of pulse oximetry measurements is adversely affected by patients with low perfusion of blood, causing a relatively small detected signal, ambient noise, and artifacts caused by patient motion. The signal confidence input 972 is an indication of the useful range of the pulse oximetry algorithms used by the digital signal processor 950 as a function of signal quality. This useful range is extended by signal extraction techniques that reduce the effects of patient motion, as described in U.S. Pat. No. 5,632,272, U.S. Pat. No. No. 5,769,785, and U.S. Pat. No. 6,002,952, referenced above. Signal confidence is a function of how well the sensor signal matches pulse oximetry algorithm signal models. For example, the red and infrared signals should be highly correlated and the pulse shapes in the pulsatile red and infrared signals should conform to the shape of physiological pulses, as described in U.S. patent application Ser. No. 09/471,510 filed Dec. 23, 1999, entitled Plethysmograph Pulse Recognition Processor, which is assigned to the assignee of the present invention and which is incorporated by reference herein. As a particular example, signal confidence can be determined by measuring pulse rate and signal strength. If the measured signal strength is within an expected range for the measured pulse rate, then the confidence level will be high. On the other hand, if the measured signal strength is outside the expected range (e.g., too high for the measured pulse rate), then the confidence level will be low. Other measured or calculated parameters can be advantageously used to set the confidence level.
  • FIG. 10 illustrates the oxygen saturation output of a pulse oximeter utilizing a variable mode averager, as described above with respect to FIG. 9. A first output 1010 illustrates oxygen saturation versus time for input oxygen saturation values processed by a conventional weighted averager or, equivalently, by a variable mode averager 960 with mode≈0. A second output 1020 illustrates oxygen saturation versus time for the variable mode averager 960 with mode≈1. Each output 1010, 1020 indicates exemplary desaturation events occurring around a first time 1030 and a second time 1040. The desaturation events correspond to a patient experiencing a potentially critical oxygen supply shortage due to a myriad of possible physiological problems. With mode≈1, the variable mode averager responds to the onset of the desaturation events with less lag time 1050 than that of the conventional weighted average. Further, the variable mode averager responds to the full extent of the desaturations 1060 whereas the conventional weighted average does not. When signal confidence is low, the variable mode averager is adjusted to provide similar smoothing features to those of a conventional weighted average. When signal confidence is high, however, the variable mode averager is advantageously adjusted to respond faster and more accurately to a critical physiological event. The fast response advantage of the variable mode averager has other physiological measurement applications, such as blood-pressure monitoring and ECG.
  • The variable mode averager has been disclosed in detail in connection with various embodiments of the present invention. One of ordinary skill in the art will appreciate many variations and modifications within the scope of this invention.
  • Thus, the variable mode averager disclosed in the foregoing advantageously allows a signal processor the ability to reduce a window of input values of, for example, a noisy signal, to a linear fit of estimates of the desired signal, where a selected output value from the estimates corresponds at least in part to the selection of a time or mode. The mode can correspond, for example, to a degree of confidence that the most recently received input signal is an accurate representation of the desired signal. However, a skilled artisan will recognize from the disclosure herein that other mechanisms can be used to reduce a set of input values to one or more appropriate output values.
  • For example, FIG. 11 illustrates a flow chart of an output value selection process 1100 of a signal processor, according to an embodiment of the invention. As shown in FIG. 11, the process 1100 includes BLOCK 1110, where the signal processor reduces a set or window of input values to one or more or a set of estimates such as the foregoing linear fit of the variable mode averager, or the like. The process 1100 then moves to BLOCK 1112, where the processor selects a time based, for example, on an indication of confidence that the set of input values represents a desired signal. The process 1100 in BLOCK 1114 then determines the output value from the one or more, or set of estimates, which corresponds to the selected time.
  • As will be appreciated by an artisan from the disclosure herein, a wide variety of processes or mechanisms can be used to reduce a set or window of input data to a set of estimates. For example, the processor can execute the foregoing variable mode averager, or other more conventional signal processing techniques, such as, for example, simple averaging, weighted averaging, linear averaging, filtering, prediction, or the like to reduce the set of input data before selecting an appropriate time using the mode or signal confidence.
  • According to one embodiment, the processor can reduce input data through segmentation of a window of input values. For example, FIG. 12 illustrates an amplitude versus time graph depicting an input signal 1210, including a window 1212 of input values. According to one embodiment, the input signal 1210 comprises, for example, a desired signal corrupted by noise or a signal having superfluous features. FIG. 12 shows an example of reduction of the input values corresponding to the window 1212 to the linear fit 1214 of estimates using the foregoing variable mode averager. As disclosed in the foregoing, when 0<mode<1, the mode variable determines the equivalent time along the linear fit of estimates for which an output estimate can be evaluated, thereby yielding an output value between vWA and vWLA.
  • However, FIG. 12 also shows reduction of the input values using segmentation. For example, a signal processor can segment the window 1212 of input values into a plurality of segments, e.g., Segments A1, A2, A3, and A4. A artisan will recognize from the disclosure herein that the use of four segments in FIG. 12 is for illustration only, and the number of segments can be selected based on a number of factors, such as, for example, the number of input values in the window, signal processing speed and capacity, experimental results, or the like.
  • According to one embodiment, the signal processor then determines one or more or a set of estimates corresponding to each segment. For example, in a straightforward implementation, the signal processor may select simple weighted averages 1216, 1218, 1220, 1222, as estimates for each of the Segments A1, A2, A3, and A4, respectively, of the window 1212 of input values. However, an artisan will recognize from the disclosure herein that the estimates for each segment may range in complexity from simple selection of one or more of the input values, to more complex calculations, such as application of the foregoing variable mode averager or the like for the input values of each segment. Moreover, the artisan will recognize from the disclosure herein that the signal confidence indicator could be used to select one, some, or all of the input values corresponding to one, some, or all, of the segments for the generation of the estimate values.
  • Once the estimates for each segment are determined, the signal processor selects a time corresponding to a degree of confidence that the input values represent a desired signal. A signal confidence indicator representative of whether the more recently received input signal values are accurate representations of a desired signal can be derived from, for example, an analysis of the amount of noise in the signal, comparing the signal to expected patterns or templates, or the like. The analysis of noise can include a measurement of the entropy of the signal, adherence of the signal to predetermined mathematical models based on a priori information about the expected or desired signal, or the like.
  • In the example illustrated in FIG. 12, the signal processor may have higher confidence that the estimates from the segmentation are representative of the desired signal, and therefore choose a time 1224 where the estimates 1216-1222 are to be evaluated. According to an embodiment using a more straightforward reduction of the segments, such as, for example, the simple weighted averaging, the signal processor may interpolate between estimates, such as, output value 1228. When more complex mechanisms are used to reduce the input data, determination of the output value 1228 may be directly calculated, such as, for example, calculation of the output value using the variable mode averager. A skilled artisan will also recognize from the disclosure herein that the output value 1228 may comprise an interpolation between more complex estimates, such as, for example, zero, first, second, etc. order interpolation.
  • Selection of the time 1224 allows the signal processor to slide the output value along, for example, the exemplary line 1214 or one of the segment estimates 1216-1222, thereby providing an output value deemed likely to indicate the value of the desired signal for the most recent input value of the time window 1212. For example, as disclosed in the foregoing, when the signal confidence indicator represents a higher confidence in the input values, the output value 1228 may slide toward the most recent input values, whereas the output value 1228 may side in the opposite direction during a time of lower signal confidence.
  • The signal processing techniques disclosed in the foregoing, which use a confidence measure to select an output value from a set of estimates of a window of input values, is particular applicable to the monitoring of critical physiological parameters in patient-care settings. When applied to pulse oximeter oxygen saturation measurements, the mode parameter can be varied in real-time to achieve a tradeoff between the suppression of false alarms and signal artifacts and the immediate detection of life threatening oxygen desaturation events. For example, during the monitoring of physiological parameters, it is often common for motion artifacts or other abnormalities to appear in the input value stream. Such abnormalities often decrease the confidence measure, or mode, being used by the signal processor. As disclosed in the foregoing, a lower signal confidence may lead to the signal processor selecting a smoothed output estimate for a specific time window, such as for example, time windows ranging from approximately 15 seconds to over 1 minute, thereby avoiding crossing over alarm-activating output thresholds. Alternatively, as discussed with reference to FIG. 10, a signal abnormality accompanied by high signal confidence leads the signal processor to the selection of an output estimate that more accurately reflects the extent of a potentially life threatening desaturation event, thereby ensuring an appropriate alarm activation.
  • Although the foregoing invention has been described in terms of certain preferred embodiments, other embodiments will be apparent to those of ordinary skill in the art from the disclosure herein. Additionally, other combinations, omissions, substitutions and modifications will be apparent to the skilled artisan in view of the disclosure herein. Accordingly, the present invention is not intended to be limited by the reaction of the preferred embodiments which disclose by way of example only, but is to be defined by reference to the appended claims.
  • Additionally, all publications, patents, and patent applications mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent, or patent application was specifically and individually indicated to be incorporated by reference.

Claims (10)

1-20. (canceled)
21. An apparatus for selecting output parameter values, the apparatus comprising:
a processor configured to:
receive an input physiological signal from a sensor coupled with a living being;
calculate parameter values from the input physiological signal;
select between a first parameter value from a trend of the parameter values and a second parameter value representing a constant average value of the parameter values within a time window, the trend having a non-zero slope in the time window; and
output the selected parameter value.
22. The apparatus of claim 21, wherein the processor is further configured to select the first parameter value from the trend of the parameter values at a most recent time in the time window.
23. The apparatus of claim 21, wherein the processor is further configured to select the first parameter value from the trend of the parameter values at a time in the time window other than a most recent time.
24. The apparatus of claim 21, wherein the processor is further configured to select the first parameter value in the time window and the second parameter value in a second time window.
25. The apparatus of claim 21, wherein the processor is further configured to calculate a signal confidence using the input physiological signal.
26. The apparatus of claim 25, wherein the processor is further configured to make said selection using the signal confidence.
27. The apparatus of claim 26, wherein the processor is further configured to select the first parameter value when the signal confidence is high and the second parameter value when the signal confidence is low.
28. The apparatus of claim 21, wherein the parameter values comprise oxygen saturation values.
29. The apparatus of claim 21, wherein the parameter values comprises blood pressure values.
US14/830,211 2000-06-05 2015-08-19 Variable indication estimator Abandoned US20150351697A1 (en)

Priority Applications (8)

Application Number Priority Date Filing Date Title
US09/586,845 US6430525B1 (en) 2000-06-05 2000-06-05 Variable mode averager
US10/213,270 US6999904B2 (en) 2000-06-05 2002-08-05 Variable indication estimator
US11/375,662 US7499835B2 (en) 2000-06-05 2006-03-14 Variable indication estimator
US12/362,463 US7873497B2 (en) 2000-06-05 2009-01-29 Variable indication estimator
US13/007,109 US8260577B2 (en) 2000-06-05 2011-01-14 Variable indication estimator
US13/601,930 US8489364B2 (en) 2000-06-05 2012-08-31 Variable indication estimator
US13/942,562 US9138192B2 (en) 2000-06-05 2013-07-15 Variable indication estimator
US14/830,211 US20150351697A1 (en) 2000-06-05 2015-08-19 Variable indication estimator

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
US14/830,211 US20150351697A1 (en) 2000-06-05 2015-08-19 Variable indication estimator
US15/913,044 US20180256113A1 (en) 2000-06-05 2018-03-06 Variable indication estimator

Related Parent Applications (1)

Application Number Title Priority Date Filing Date
US13/942,562 Continuation US9138192B2 (en) 2000-06-05 2013-07-15 Variable indication estimator

Related Child Applications (1)

Application Number Title Priority Date Filing Date
US15/913,044 Continuation US20180256113A1 (en) 2000-06-05 2018-03-06 Variable indication estimator

Publications (1)

Publication Number Publication Date
US20150351697A1 true US20150351697A1 (en) 2015-12-10

Family

ID=24347320

Family Applications (9)

Application Number Title Priority Date Filing Date
US09/586,845 Active US6430525B1 (en) 2000-06-05 2000-06-05 Variable mode averager
US10/213,270 Active US6999904B2 (en) 2000-06-05 2002-08-05 Variable indication estimator
US11/375,662 Active US7499835B2 (en) 2000-06-05 2006-03-14 Variable indication estimator
US12/362,463 Active 2020-11-17 US7873497B2 (en) 2000-06-05 2009-01-29 Variable indication estimator
US13/007,109 Active US8260577B2 (en) 2000-06-05 2011-01-14 Variable indication estimator
US13/601,930 Active US8489364B2 (en) 2000-06-05 2012-08-31 Variable indication estimator
US13/942,562 Active US9138192B2 (en) 2000-06-05 2013-07-15 Variable indication estimator
US14/830,211 Abandoned US20150351697A1 (en) 2000-06-05 2015-08-19 Variable indication estimator
US15/913,044 Pending US20180256113A1 (en) 2000-06-05 2018-03-06 Variable indication estimator

Family Applications Before (7)

Application Number Title Priority Date Filing Date
US09/586,845 Active US6430525B1 (en) 2000-06-05 2000-06-05 Variable mode averager
US10/213,270 Active US6999904B2 (en) 2000-06-05 2002-08-05 Variable indication estimator
US11/375,662 Active US7499835B2 (en) 2000-06-05 2006-03-14 Variable indication estimator
US12/362,463 Active 2020-11-17 US7873497B2 (en) 2000-06-05 2009-01-29 Variable indication estimator
US13/007,109 Active US8260577B2 (en) 2000-06-05 2011-01-14 Variable indication estimator
US13/601,930 Active US8489364B2 (en) 2000-06-05 2012-08-31 Variable indication estimator
US13/942,562 Active US9138192B2 (en) 2000-06-05 2013-07-15 Variable indication estimator

Family Applications After (1)

Application Number Title Priority Date Filing Date
US15/913,044 Pending US20180256113A1 (en) 2000-06-05 2018-03-06 Variable indication estimator

Country Status (5)

Country Link
US (9) US6430525B1 (en)
EP (1) EP1286619B1 (en)
JP (1) JP2003535417A (en)
DE (1) DE60144474D1 (en)
WO (1) WO2001093757A1 (en)

Cited By (64)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US9538949B2 (en) 2010-09-28 2017-01-10 Masimo Corporation Depth of consciousness monitor including oximeter
US9560996B2 (en) 2012-10-30 2017-02-07 Masimo Corporation Universal medical system
US9579039B2 (en) 2011-01-10 2017-02-28 Masimo Corporation Non-invasive intravascular volume index monitor
US9591975B2 (en) 2008-07-03 2017-03-14 Masimo Corporation Contoured protrusion for improving spectroscopic measurement of blood constituents
USD788312S1 (en) 2012-02-09 2017-05-30 Masimo Corporation Wireless patient monitoring device
US9668680B2 (en) 2009-09-03 2017-06-06 Masimo Corporation Emitter driver for noninvasive patient monitor
US9675286B2 (en) 1998-12-30 2017-06-13 Masimo Corporation Plethysmograph pulse recognition processor
US9687160B2 (en) 2006-09-20 2017-06-27 Masimo Corporation Congenital heart disease monitor
US9717458B2 (en) 2012-10-20 2017-08-01 Masimo Corporation Magnetic-flap optical sensor
US9750442B2 (en) 2013-03-09 2017-09-05 Masimo Corporation Physiological status monitor
US9750461B1 (en) 2013-01-02 2017-09-05 Masimo Corporation Acoustic respiratory monitoring sensor with probe-off detection
US9750443B2 (en) 2005-03-01 2017-09-05 Cercacor Laboratories, Inc. Multiple wavelength sensor emitters
US9775546B2 (en) 2012-04-17 2017-10-03 Masimo Corporation Hypersaturation index
US9775545B2 (en) 2010-09-28 2017-10-03 Masimo Corporation Magnetic electrical connector for patient monitors
US9775570B2 (en) 2010-03-01 2017-10-03 Masimo Corporation Adaptive alarm system
US9787568B2 (en) 2012-11-05 2017-10-10 Cercacor Laboratories, Inc. Physiological test credit method
US9782077B2 (en) 2011-08-17 2017-10-10 Masimo Corporation Modulated physiological sensor
US9788735B2 (en) 2002-03-25 2017-10-17 Masimo Corporation Body worn mobile medical patient monitor
US9795739B2 (en) 2009-05-20 2017-10-24 Masimo Corporation Hemoglobin display and patient treatment
US9801588B2 (en) 2003-07-08 2017-10-31 Cercacor Laboratories, Inc. Method and apparatus for reducing coupling between signals in a measurement system
US9814418B2 (en) 2001-06-29 2017-11-14 Masimo Corporation Sine saturation transform
US9839379B2 (en) 2013-10-07 2017-12-12 Masimo Corporation Regional oximetry pod
US9839381B1 (en) 2009-11-24 2017-12-12 Cercacor Laboratories, Inc. Physiological measurement system with automatic wavelength adjustment
US9847002B2 (en) 2009-12-21 2017-12-19 Masimo Corporation Modular patient monitor
US9848807B2 (en) 2007-04-21 2017-12-26 Masimo Corporation Tissue profile wellness monitor
US9848806B2 (en) 2001-07-02 2017-12-26 Masimo Corporation Low power pulse oximeter
US9861305B1 (en) 2006-10-12 2018-01-09 Masimo Corporation Method and apparatus for calibration to reduce coupling between signals in a measurement system
US9876320B2 (en) 2010-05-03 2018-01-23 Masimo Corporation Sensor adapter cable
US9891079B2 (en) 2013-07-17 2018-02-13 Masimo Corporation Pulser with double-bearing position encoder for non-invasive physiological monitoring
US9913617B2 (en) 2011-10-13 2018-03-13 Masimo Corporation Medical monitoring hub
US9936917B2 (en) 2013-03-14 2018-04-10 Masimo Laboratories, Inc. Patient monitor placement indicator
US9943269B2 (en) 2011-10-13 2018-04-17 Masimo Corporation System for displaying medical monitoring data
US9949676B2 (en) 2006-10-12 2018-04-24 Masimo Corporation Patient monitor capable of monitoring the quality of attached probes and accessories
US10007758B2 (en) 2009-03-04 2018-06-26 Masimo Corporation Medical monitoring system
US10032002B2 (en) 2009-03-04 2018-07-24 Masimo Corporation Medical monitoring system
US10052037B2 (en) 2010-07-22 2018-08-21 Masimo Corporation Non-invasive blood pressure measurement system
US10058275B2 (en) 2003-07-25 2018-08-28 Masimo Corporation Multipurpose sensor port
US10064562B2 (en) 2006-10-12 2018-09-04 Masimo Corporation Variable mode pulse indicator
US10086138B1 (en) 2014-01-28 2018-10-02 Masimo Corporation Autonomous drug delivery system
US10092249B2 (en) 2005-10-14 2018-10-09 Masimo Corporation Robust alarm system
US10098591B2 (en) 2004-03-08 2018-10-16 Masimo Corporation Physiological parameter system
US10130289B2 (en) 1999-01-07 2018-11-20 Masimo Corporation Pulse and confidence indicator displayed proximate plethysmograph
US10130291B2 (en) 2004-08-11 2018-11-20 Masimo Corporation Method for data reduction and calibration of an OCT-based physiological monitor
USD835285S1 (en) 2017-04-28 2018-12-04 Masimo Corporation Medical monitoring device
USD835284S1 (en) 2017-04-28 2018-12-04 Masimo Corporation Medical monitoring device
USD835282S1 (en) 2017-04-28 2018-12-04 Masimo Corporation Medical monitoring device
USD835283S1 (en) 2017-04-28 2018-12-04 Masimo Corporation Medical monitoring device
US10154815B2 (en) 2014-10-07 2018-12-18 Masimo Corporation Modular physiological sensors
US10159412B2 (en) 2010-12-01 2018-12-25 Cercacor Laboratories, Inc. Handheld processing device including medical applications for minimally and non invasive glucose measurements
US10188348B2 (en) 2006-06-05 2019-01-29 Masimo Corporation Parameter upgrade system
US10188331B1 (en) 2009-07-29 2019-01-29 Masimo Corporation Non-invasive physiological sensor cover
US10194847B2 (en) 2006-10-12 2019-02-05 Masimo Corporation Perfusion index smoother
US10205272B2 (en) 2009-03-11 2019-02-12 Masimo Corporation Magnetic connector
US10205291B2 (en) 2015-02-06 2019-02-12 Masimo Corporation Pogo pin connector
US10201298B2 (en) 2003-01-24 2019-02-12 Masimo Corporation Noninvasive oximetry optical sensor including disposable and reusable elements
USRE47249E1 (en) 2008-07-29 2019-02-19 Masimo Corporation Alarm suspend system
US10219746B2 (en) 2006-10-12 2019-03-05 Masimo Corporation Oximeter probe off indicator defining probe off space
US10226187B2 (en) 2015-08-31 2019-03-12 Masimo Corporation Patient-worn wireless physiological sensor
US10226576B2 (en) 2006-05-15 2019-03-12 Masimo Corporation Sepsis monitor
US10231676B2 (en) 1999-01-25 2019-03-19 Masimo Corporation Dual-mode patient monitor
US10231670B2 (en) 2014-06-19 2019-03-19 Masimo Corporation Proximity sensor in pulse oximeter
US10255994B2 (en) 2009-03-04 2019-04-09 Masimo Corporation Physiological parameter alarm delay
US10258266B1 (en) 2008-07-03 2019-04-16 Masimo Corporation Multi-stream data collection system for noninvasive measurement of blood constituents
US10271748B2 (en) 2017-09-19 2019-04-30 Masimo Corporation Patient monitor for determining microcirculation state

Families Citing this family (291)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP1905352B1 (en) 1994-10-07 2014-07-16 Masimo Corporation Signal processing method
US8019400B2 (en) 1994-10-07 2011-09-13 Masimo Corporation Signal processing apparatus
US5490505A (en) 1991-03-07 1996-02-13 Masimo Corporation Signal processing apparatus
MX9702434A (en) * 1991-03-07 1998-05-31 Masimo Corp Signal processing apparatus.
EP0930045A3 (en) * 1991-03-07 1999-10-27 Masimo Corporation Signal processing apparatus and method for an oximeter
US5638818A (en) 1991-03-21 1997-06-17 Masimo Corporation Low noise optical probe
US20060155206A1 (en) * 1997-01-27 2006-07-13 Lynn Lawrence A System and method for sound and oximetry integration
US20060155207A1 (en) * 1997-01-27 2006-07-13 Lynn Lawrence A System and method for detection of incomplete reciprocation
US9521971B2 (en) 1997-07-14 2016-12-20 Lawrence A. Lynn System and method for automatic detection of a plurality of SPO2 time series pattern types
US7758503B2 (en) * 1997-01-27 2010-07-20 Lynn Lawrence A Microprocessor system for the analysis of physiologic and financial datasets
US9468378B2 (en) * 1997-01-27 2016-10-18 Lawrence A. Lynn Airway instability detection system and method
US20080287756A1 (en) * 1997-07-14 2008-11-20 Lynn Lawrence A Pulse oximetry relational alarm system for early recognition of instability and catastrophic occurrences
US9042952B2 (en) 1997-01-27 2015-05-26 Lawrence A. Lynn System and method for automatic detection of a plurality of SPO2 time series pattern types
US5758644A (en) 1995-06-07 1998-06-02 Masimo Corporation Manual and automatic probe calibration
US6931268B1 (en) 1995-06-07 2005-08-16 Masimo Laboratories, Inc. Active pulse blood constituent monitoring
US5853364A (en) * 1995-08-07 1998-12-29 Nellcor Puritan Bennett, Inc. Method and apparatus for estimating physiological parameters using model-based adaptive filtering
US6027452A (en) * 1996-06-26 2000-02-22 Vital Insite, Inc. Rapid non-invasive blood pressure measuring device
US6018673A (en) 1996-10-10 2000-01-25 Nellcor Puritan Bennett Incorporated Motion compatible sensor for non-invasive optical blood analysis
US8932227B2 (en) 2000-07-28 2015-01-13 Lawrence A. Lynn System and method for CO2 and oximetry integration
US9053222B2 (en) 2002-05-17 2015-06-09 Lawrence A. Lynn Patient safety processor
US6229856B1 (en) 1997-04-14 2001-05-08 Masimo Corporation Method and apparatus for demodulating signals in a pulse oximetry system
US6002952A (en) 1997-04-14 1999-12-14 Masimo Corporation Signal processing apparatus and method
US6525386B1 (en) * 1998-03-10 2003-02-25 Masimo Corporation Non-protruding optoelectronic lens
CA2333062A1 (en) 1998-06-03 1999-12-09 Mohamed K. Diab Stereo pulse oximeter
US6721585B1 (en) 1998-10-15 2004-04-13 Sensidyne, Inc. Universal modular pulse oximeter probe for use with reusable and disposable patient attachment devices
US7245953B1 (en) 1999-04-12 2007-07-17 Masimo Corporation Reusable pulse oximeter probe and disposable bandage apparatii
USRE41912E1 (en) 1998-10-15 2010-11-02 Masimo Corporation Reusable pulse oximeter probe and disposable bandage apparatus
US6770028B1 (en) * 1999-01-25 2004-08-03 Masimo Corporation Dual-mode pulse oximeter
US20020140675A1 (en) 1999-01-25 2002-10-03 Ali Ammar Al System and method for altering a display mode based on a gravity-responsive sensor
US6360114B1 (en) 1999-03-25 2002-03-19 Masimo Corporation Pulse oximeter probe-off detector
US6675031B1 (en) 1999-04-14 2004-01-06 Mallinckrodt Inc. Method and circuit for indicating quality and accuracy of physiological measurements
US6515273B2 (en) 1999-08-26 2003-02-04 Masimo Corporation System for indicating the expiration of the useful operating life of a pulse oximetry sensor
US6377829B1 (en) 1999-12-09 2002-04-23 Masimo Corporation Resposable pulse oximetry sensor
US6950687B2 (en) 1999-12-09 2005-09-27 Masimo Corporation Isolation and communication element for a resposable pulse oximetry sensor
US6430525B1 (en) * 2000-06-05 2002-08-06 Masimo Corporation Variable mode averager
US6640116B2 (en) * 2000-08-18 2003-10-28 Masimo Corporation Optical spectroscopy pathlength measurement system
US20020083461A1 (en) 2000-11-22 2002-06-27 Hutcheson Stewart Douglas Method and system for providing interactive services over a wireless communications network
US7729918B2 (en) * 2001-03-14 2010-06-01 At&T Intellectual Property Ii, Lp Trainable sentence planning system
JP2004532526A (en) * 2001-05-03 2004-10-21 マシモ・コーポレイション Method of making a flex circuit shields the optical sensor and the flex circuit shield optical sensor
US20060195041A1 (en) 2002-05-17 2006-08-31 Lynn Lawrence A Centralized hospital monitoring system for automatically detecting upper airway instability and for preventing and aborting adverse drug reactions
US6754516B2 (en) 2001-07-19 2004-06-22 Nellcor Puritan Bennett Incorporated Nuisance alarm reductions in a physiological monitor
US6748254B2 (en) 2001-10-12 2004-06-08 Nellcor Puritan Bennett Incorporated Stacked adhesive optical sensor
US20030212312A1 (en) * 2002-01-07 2003-11-13 Coffin James P. Low noise patient cable
US6934570B2 (en) * 2002-01-08 2005-08-23 Masimo Corporation Physiological sensor combination
US7355512B1 (en) 2002-01-24 2008-04-08 Masimo Corporation Parallel alarm processor
US6822564B2 (en) 2002-01-24 2004-11-23 Masimo Corporation Parallel measurement alarm processor
WO2003065557A2 (en) * 2002-01-25 2003-08-07 Masimo Corporation Power supply rail controller
US6961598B2 (en) * 2002-02-22 2005-11-01 Masimo Corporation Pulse and active pulse spectraphotometry
US7509494B2 (en) 2002-03-01 2009-03-24 Masimo Corporation Interface cable
US7096054B2 (en) * 2002-08-01 2006-08-22 Masimo Corporation Low noise optical housing
US7142901B2 (en) * 2002-09-25 2006-11-28 Masimo Corporation Parameter compensated physiological monitor
US7274955B2 (en) * 2002-09-25 2007-09-25 Masimo Corporation Parameter compensated pulse oximeter
US7190986B1 (en) 2002-10-18 2007-03-13 Nellcor Puritan Bennett Inc. Non-adhesive oximeter sensor for sensitive skin
US7027849B2 (en) * 2002-11-22 2006-04-11 Masimo Laboratories, Inc. Blood parameter measurement system
US6970792B1 (en) 2002-12-04 2005-11-29 Masimo Laboratories, Inc. Systems and methods for determining blood oxygen saturation values using complex number encoding
US7225006B2 (en) 2003-01-23 2007-05-29 Masimo Corporation Attachment and optical probe
US20050055276A1 (en) * 2003-06-26 2005-03-10 Kiani Massi E. Sensor incentive method
US7254431B2 (en) 2003-08-28 2007-08-07 Masimo Corporation Physiological parameter tracking system
US7254434B2 (en) * 2003-10-14 2007-08-07 Masimo Corporation Variable pressure reusable sensor
US7483729B2 (en) * 2003-11-05 2009-01-27 Masimo Corporation Pulse oximeter access apparatus and method
US7373193B2 (en) * 2003-11-07 2008-05-13 Masimo Corporation Pulse oximetry data capture system
EP1711791B1 (en) 2003-12-09 2014-10-15 DexCom, Inc. Signal processing for continuous analyte sensor
US7280858B2 (en) * 2004-01-05 2007-10-09 Masimo Corporation Pulse oximetry sensor
US7163040B2 (en) 2004-01-13 2007-01-16 Sanford L.P. Correction tape applicator tip with cylindrical projection
US7580812B2 (en) * 2004-01-28 2009-08-25 Honeywell International Inc. Trending system and method using window filtering
US7371981B2 (en) * 2004-02-20 2008-05-13 Masimo Corporation Connector switch
US7438683B2 (en) 2004-03-04 2008-10-21 Masimo Corporation Application identification sensor
US7194293B2 (en) 2004-03-08 2007-03-20 Nellcor Puritan Bennett Incorporated Selection of ensemble averaging weights for a pulse oximeter based on signal quality metrics
US20050234317A1 (en) * 2004-03-19 2005-10-20 Kiani Massi E Low power and personal pulse oximetry systems
US7292883B2 (en) * 2004-03-31 2007-11-06 Masimo Corporation Physiological assessment system
CA2464029A1 (en) 2004-04-08 2005-10-08 Valery Telfort Non-invasive ventilation monitor
US6993442B2 (en) * 2004-05-14 2006-01-31 Agilent Technologies, Inc. Adaptive data collection
US9341565B2 (en) 2004-07-07 2016-05-17 Masimo Corporation Multiple-wavelength physiological monitor
US7343186B2 (en) 2004-07-07 2008-03-11 Masimo Laboratories, Inc. Multi-wavelength physiological monitor
US7937128B2 (en) * 2004-07-09 2011-05-03 Masimo Corporation Cyanotic infant sensor
US8036727B2 (en) 2004-08-11 2011-10-11 Glt Acquisition Corp. Methods for noninvasively measuring analyte levels in a subject
US7254429B2 (en) 2004-08-11 2007-08-07 Glucolight Corporation Method and apparatus for monitoring glucose levels in a biological tissue
US7976472B2 (en) 2004-09-07 2011-07-12 Masimo Corporation Noninvasive hypovolemia monitor
US20060073719A1 (en) * 2004-09-29 2006-04-06 Kiani Massi E Multiple key position plug
US20060189871A1 (en) * 2005-02-18 2006-08-24 Ammar Al-Ali Portable patient monitor
US7392075B2 (en) 2005-03-03 2008-06-24 Nellcor Puritan Bennett Incorporated Method for enhancing pulse oximetry calculations in the presence of correlated artifacts
US7937129B2 (en) * 2005-03-21 2011-05-03 Masimo Corporation Variable aperture sensor
US7657294B2 (en) 2005-08-08 2010-02-02 Nellcor Puritan Bennett Llc Compliant diaphragm medical sensor and technique for using the same
US7657295B2 (en) 2005-08-08 2010-02-02 Nellcor Puritan Bennett Llc Medical sensor and technique for using the same
US7590439B2 (en) 2005-08-08 2009-09-15 Nellcor Puritan Bennett Llc Bi-stable medical sensor and technique for using the same
US20070073116A1 (en) * 2005-08-17 2007-03-29 Kiani Massi E Patient identification using physiological sensor
US20070060808A1 (en) 2005-09-12 2007-03-15 Carine Hoarau Medical sensor for reducing motion artifacts and technique for using the same
US8092379B2 (en) 2005-09-29 2012-01-10 Nellcor Puritan Bennett Llc Method and system for determining when to reposition a physiological sensor
US7869850B2 (en) 2005-09-29 2011-01-11 Nellcor Puritan Bennett Llc Medical sensor for reducing motion artifacts and technique for using the same
US7899510B2 (en) 2005-09-29 2011-03-01 Nellcor Puritan Bennett Llc Medical sensor and technique for using the same
US7904130B2 (en) 2005-09-29 2011-03-08 Nellcor Puritan Bennett Llc Medical sensor and technique for using the same
US7881762B2 (en) 2005-09-30 2011-02-01 Nellcor Puritan Bennett Llc Clip-style medical sensor and technique for using the same
US7486979B2 (en) 2005-09-30 2009-02-03 Nellcor Puritan Bennett Llc Optically aligned pulse oximetry sensor and technique for using the same
US8233954B2 (en) 2005-09-30 2012-07-31 Nellcor Puritan Bennett Llc Mucosal sensor for the assessment of tissue and blood constituents and technique for using the same
US7483731B2 (en) 2005-09-30 2009-01-27 Nellcor Puritan Bennett Llc Medical sensor and technique for using the same
US7555327B2 (en) 2005-09-30 2009-06-30 Nellcor Puritan Bennett Llc Folding medical sensor and technique for using the same
US8062221B2 (en) 2005-09-30 2011-11-22 Nellcor Puritan Bennett Llc Sensor for tissue gas detection and technique for using the same
US7530942B1 (en) 2005-10-18 2009-05-12 Masimo Corporation Remote sensing infant warmer
US8600467B2 (en) 2006-11-29 2013-12-03 Cercacor Laboratories, Inc. Optical sensor including disposable and reusable elements
US8233955B2 (en) 2005-11-29 2012-07-31 Cercacor Laboratories, Inc. Optical sensor including disposable and reusable elements
WO2007065015A2 (en) * 2005-12-03 2007-06-07 Masimo Corporation Physiological alarm notification system
US7990382B2 (en) 2006-01-03 2011-08-02 Masimo Corporation Virtual display
US8182443B1 (en) 2006-01-17 2012-05-22 Masimo Corporation Drug administration controller
US20070191697A1 (en) 2006-02-10 2007-08-16 Lynn Lawrence A System and method for SPO2 instability detection and quantification
US7668579B2 (en) 2006-02-10 2010-02-23 Lynn Lawrence A System and method for the detection of physiologic response to stimulation
US20070244377A1 (en) * 2006-03-14 2007-10-18 Cozad Jenny L Pulse oximeter sleeve
US8219172B2 (en) 2006-03-17 2012-07-10 Glt Acquisition Corp. System and method for creating a stable optical interface
US8073518B2 (en) 2006-05-02 2011-12-06 Nellcor Puritan Bennett Llc Clip-style medical sensor and technique for using the same
US9176141B2 (en) 2006-05-15 2015-11-03 Cercacor Laboratories, Inc. Physiological monitor calibration system
US8998809B2 (en) 2006-05-15 2015-04-07 Cercacor Laboratories, Inc. Systems and methods for calibrating minimally invasive and non-invasive physiological sensor devices
US8028701B2 (en) 2006-05-31 2011-10-04 Masimo Corporation Respiratory monitoring
JP5528801B2 (en) * 2006-06-07 2014-06-25 ガンブロ・ルンディア・エービーGambro Lundia Ab Prediction of rapid symptomatic blood pressure decrease
US8145288B2 (en) 2006-08-22 2012-03-27 Nellcor Puritan Bennett Llc Medical sensor for reducing signal artifacts and technique for using the same
US20080064965A1 (en) * 2006-09-08 2008-03-13 Jay Gregory D Devices and methods for measuring pulsus paradoxus
US8315683B2 (en) 2006-09-20 2012-11-20 Masimo Corporation Duo connector patient cable
US8219170B2 (en) 2006-09-20 2012-07-10 Nellcor Puritan Bennett Llc System and method for practicing spectrophotometry using light emitting nanostructure devices
US8840549B2 (en) 2006-09-22 2014-09-23 Masimo Corporation Modular patient monitor
US8195264B2 (en) 2006-09-22 2012-06-05 Nellcor Puritan Bennett Llc Medical sensor for reducing signal artifacts and technique for using the same
US8396527B2 (en) 2006-09-22 2013-03-12 Covidien Lp Medical sensor for reducing signal artifacts and technique for using the same
US20080103375A1 (en) * 2006-09-22 2008-05-01 Kiani Massi E Patient monitor user interface
US9161696B2 (en) 2006-09-22 2015-10-20 Masimo Corporation Modular patient monitor
US8175671B2 (en) 2006-09-22 2012-05-08 Nellcor Puritan Bennett Llc Medical sensor for reducing signal artifacts and technique for using the same
US7869849B2 (en) 2006-09-26 2011-01-11 Nellcor Puritan Bennett Llc Opaque, electrically nonconductive region on a medical sensor
US7574245B2 (en) 2006-09-27 2009-08-11 Nellcor Puritan Bennett Llc Flexible medical sensor enclosure
US7796403B2 (en) 2006-09-28 2010-09-14 Nellcor Puritan Bennett Llc Means for mechanical registration and mechanical-electrical coupling of a faraday shield to a photodetector and an electrical circuit
US7890153B2 (en) 2006-09-28 2011-02-15 Nellcor Puritan Bennett Llc System and method for mitigating interference in pulse oximetry
US8068891B2 (en) 2006-09-29 2011-11-29 Nellcor Puritan Bennett Llc Symmetric LED array for pulse oximetry
US8175667B2 (en) 2006-09-29 2012-05-08 Nellcor Puritan Bennett Llc Symmetric LED array for pulse oximetry
US7684842B2 (en) 2006-09-29 2010-03-23 Nellcor Puritan Bennett Llc System and method for preventing sensor misuse
US7476131B2 (en) 2006-09-29 2009-01-13 Nellcor Puritan Bennett Llc Device for reducing crosstalk
US7680522B2 (en) 2006-09-29 2010-03-16 Nellcor Puritan Bennett Llc Method and apparatus for detecting misapplied sensors
US20080094228A1 (en) * 2006-10-12 2008-04-24 Welch James P Patient monitor using radio frequency identification tags
US7880626B2 (en) 2006-10-12 2011-02-01 Masimo Corporation System and method for monitoring the life of a physiological sensor
JP5441707B2 (en) 2006-12-09 2014-03-12 マシモ コーポレイション Plethysmograph variability processor
US7791155B2 (en) 2006-12-22 2010-09-07 Masimo Laboratories, Inc. Detector shield
US8852094B2 (en) 2006-12-22 2014-10-07 Masimo Corporation Physiological parameter system
US8652060B2 (en) 2007-01-20 2014-02-18 Masimo Corporation Perfusion trend indicator
US20090093687A1 (en) * 2007-03-08 2009-04-09 Telfort Valery G Systems and methods for determining a physiological condition using an acoustic monitor
US20080221418A1 (en) * 2007-03-09 2008-09-11 Masimo Corporation Noninvasive multi-parameter patient monitor
US8280469B2 (en) 2007-03-09 2012-10-02 Nellcor Puritan Bennett Llc Method for detection of aberrant tissue spectra
US8265724B2 (en) 2007-03-09 2012-09-11 Nellcor Puritan Bennett Llc Cancellation of light shunting
US7894869B2 (en) 2007-03-09 2011-02-22 Nellcor Puritan Bennett Llc Multiple configuration medical sensor and technique for using the same
US8781544B2 (en) 2007-03-27 2014-07-15 Cercacor Laboratories, Inc. Multiple wavelength optical sensor
US7919713B2 (en) 2007-04-16 2011-04-05 Masimo Corporation Low noise oximetry cable including conductive cords
US8764671B2 (en) 2007-06-28 2014-07-01 Masimo Corporation Disposable active pulse sensor
US8048040B2 (en) 2007-09-13 2011-11-01 Masimo Corporation Fluid titration system
WO2009049254A2 (en) 2007-10-12 2009-04-16 Masimo Corporation Systems and methods for storing, analyzing, and retrieving medical data
EP2227843B1 (en) 2007-10-12 2019-03-06 Masimo Corporation Connector assembly
USD609193S1 (en) 2007-10-12 2010-02-02 Masimo Corporation Connector assembly
US8355766B2 (en) 2007-10-12 2013-01-15 Masimo Corporation Ceramic emitter substrate
US8310336B2 (en) 2008-10-10 2012-11-13 Masimo Corporation Systems and methods for storing, analyzing, retrieving and displaying streaming medical data
US8352004B2 (en) 2007-12-21 2013-01-08 Covidien Lp Medical sensor and technique for using the same
US8346328B2 (en) 2007-12-21 2013-01-01 Covidien Lp Medical sensor and technique for using the same
US8366613B2 (en) 2007-12-26 2013-02-05 Covidien Lp LED drive circuit for pulse oximetry and method for using same
US8577434B2 (en) 2007-12-27 2013-11-05 Covidien Lp Coaxial LED light sources
US8442608B2 (en) 2007-12-28 2013-05-14 Covidien Lp System and method for estimating physiological parameters by deconvolving artifacts
US8452364B2 (en) 2007-12-28 2013-05-28 Covidien LLP System and method for attaching a sensor to a patient's skin
US8199007B2 (en) 2007-12-31 2012-06-12 Nellcor Puritan Bennett Llc Flex circuit snap track for a biometric sensor
US8092993B2 (en) 2007-12-31 2012-01-10 Nellcor Puritan Bennett Llc Hydrogel thin film for use as a biosensor
US20090171226A1 (en) * 2007-12-31 2009-07-02 Nellcor Puritan Bennett Llc System and method for evaluating variation in the timing of physiological events
US8897850B2 (en) 2007-12-31 2014-11-25 Covidien Lp Sensor with integrated living hinge and spring
US8070508B2 (en) 2007-12-31 2011-12-06 Nellcor Puritan Bennett Llc Method and apparatus for aligning and securing a cable strain relief
USD614305S1 (en) 2008-02-29 2010-04-20 Masimo Corporation Connector assembly
WO2009111542A2 (en) 2008-03-04 2009-09-11 Glucolight Corporation Methods and systems for analyte level estimation in optical coherence tomography
US8437822B2 (en) 2008-03-28 2013-05-07 Covidien Lp System and method for estimating blood analyte concentration
US8364224B2 (en) * 2008-03-31 2013-01-29 Covidien Lp System and method for facilitating sensor and monitor communication
US8112375B2 (en) 2008-03-31 2012-02-07 Nellcor Puritan Bennett Llc Wavelength selection and outlier detection in reduced rank linear models
JP5575752B2 (en) * 2008-05-02 2014-08-20 マシモ コーポレイション Monitor configuration system
US9107625B2 (en) 2008-05-05 2015-08-18 Masimo Corporation Pulse oximetry system with electrical decoupling circuitry
USD626562S1 (en) 2008-06-30 2010-11-02 Nellcor Puritan Bennett Llc Triangular saturation pattern detection indicator for a patient monitor display panel
US7887345B2 (en) 2008-06-30 2011-02-15 Nellcor Puritan Bennett Llc Single use connector for pulse oximetry sensors
US8862194B2 (en) * 2008-06-30 2014-10-14 Covidien Lp Method for improved oxygen saturation estimation in the presence of noise
US8071935B2 (en) 2008-06-30 2011-12-06 Nellcor Puritan Bennett Llc Optical detector with an overmolded faraday shield
USD626561S1 (en) 2008-06-30 2010-11-02 Nellcor Puritan Bennett Llc Circular satseconds indicator and triangular saturation pattern detection indicator for a patient monitor display panel
US7880884B2 (en) 2008-06-30 2011-02-01 Nellcor Puritan Bennett Llc System and method for coating and shielding electronic sensor components
US8370080B2 (en) * 2008-07-15 2013-02-05 Nellcor Puritan Bennett Ireland Methods and systems for determining whether to trigger an alarm
USD621516S1 (en) 2008-08-25 2010-08-10 Masimo Laboratories, Inc. Patient monitoring sensor
US8911377B2 (en) 2008-09-15 2014-12-16 Masimo Corporation Patient monitor including multi-parameter graphical display
US8364220B2 (en) 2008-09-25 2013-01-29 Covidien Lp Medical sensor and technique for using the same
US8696585B2 (en) * 2008-09-30 2014-04-15 Nellcor Puritan Bennett Ireland Detecting a probe-off event in a measurement system
US8410951B2 (en) 2008-09-30 2013-04-02 Covidien Lp Detecting a signal quality decrease in a measurement system
US20100081891A1 (en) * 2008-09-30 2010-04-01 Nellcor Puritan Bennett Llc System And Method For Displaying Detailed Information For A Data Point
US8914088B2 (en) 2008-09-30 2014-12-16 Covidien Lp Medical sensor and technique for using the same
US8423112B2 (en) 2008-09-30 2013-04-16 Covidien Lp Medical sensor and technique for using the same
US8417309B2 (en) 2008-09-30 2013-04-09 Covidien Lp Medical sensor
US8346330B2 (en) 2008-10-13 2013-01-01 Masimo Corporation Reflection-detector sensor position indicator
US8401602B2 (en) 2008-10-13 2013-03-19 Masimo Corporation Secondary-emitter sensor position indicator
US8512260B2 (en) 2008-10-29 2013-08-20 The Regents Of The University Of Colorado, A Body Corporate Statistical, noninvasive measurement of intracranial pressure
US20110172545A1 (en) * 2008-10-29 2011-07-14 Gregory Zlatko Grudic Active Physical Perturbations to Enhance Intelligent Medical Monitoring
CA2741043C (en) * 2008-11-05 2014-03-25 Nellcor Puritan Bennett Llc System and method for facilitating observation of monitored physiologic data
US8771204B2 (en) 2008-12-30 2014-07-08 Masimo Corporation Acoustic sensor assembly
US8588880B2 (en) 2009-02-16 2013-11-19 Masimo Corporation Ear sensor
US8447961B2 (en) * 2009-02-18 2013-05-21 Saankhya Labs Pvt Ltd Mechanism for efficient implementation of software pipelined loops in VLIW processors
US20100234718A1 (en) * 2009-03-12 2010-09-16 Anand Sampath Open architecture medical communication system
US8452366B2 (en) 2009-03-16 2013-05-28 Covidien Lp Medical monitoring device with flexible circuitry
US8897847B2 (en) 2009-03-23 2014-11-25 Masimo Corporation Digit gauge for noninvasive optical sensor
US8221319B2 (en) 2009-03-25 2012-07-17 Nellcor Puritan Bennett Llc Medical device for assessing intravascular blood volume and technique for using the same
US8509869B2 (en) 2009-05-15 2013-08-13 Covidien Lp Method and apparatus for detecting and analyzing variations in a physiologic parameter
WO2010135373A1 (en) 2009-05-19 2010-11-25 Masimo Corporation Disposable components for reusable physiological sensor
US8364225B2 (en) * 2009-05-20 2013-01-29 Nellcor Puritan Bennett Ireland Estimating transform values using signal estimates
US8634891B2 (en) 2009-05-20 2014-01-21 Covidien Lp Method and system for self regulation of sensor component contact pressure
US8418524B2 (en) 2009-06-12 2013-04-16 Masimo Corporation Non-invasive sensor calibration device
US8505821B2 (en) 2009-06-30 2013-08-13 Covidien Lp System and method for providing sensor quality assurance
US8670811B2 (en) 2009-06-30 2014-03-11 Masimo Corporation Pulse oximetry system for adjusting medical ventilation
US8311601B2 (en) 2009-06-30 2012-11-13 Nellcor Puritan Bennett Llc Reflectance and/or transmissive pulse oximeter
US9010634B2 (en) 2009-06-30 2015-04-21 Covidien Lp System and method for linking patient data to a patient and providing sensor quality assurance
US8391941B2 (en) 2009-07-17 2013-03-05 Covidien Lp System and method for memory switching for multiple configuration medical sensor
US20110208015A1 (en) * 2009-07-20 2011-08-25 Masimo Corporation Wireless patient monitoring system
US20110040197A1 (en) * 2009-07-20 2011-02-17 Masimo Corporation Wireless patient monitoring system
US8471713B2 (en) 2009-07-24 2013-06-25 Cercacor Laboratories, Inc. Interference detector for patient monitor
US20110028806A1 (en) * 2009-07-29 2011-02-03 Sean Merritt Reflectance calibration of fluorescence-based glucose measurements
US20110028809A1 (en) * 2009-07-29 2011-02-03 Masimo Corporation Patient monitor ambient display device
US8346333B2 (en) * 2009-07-30 2013-01-01 Nellcor Puritan Bennett Ireland Systems and methods for estimating values of a continuous wavelet transform
US8594759B2 (en) 2009-07-30 2013-11-26 Nellcor Puritan Bennett Ireland Systems and methods for resolving the continuous wavelet transform of a signal
US20110087081A1 (en) * 2009-08-03 2011-04-14 Kiani Massi Joe E Personalized physiological monitor
US8417310B2 (en) 2009-08-10 2013-04-09 Covidien Lp Digital switching in multi-site sensor
US8428675B2 (en) 2009-08-19 2013-04-23 Covidien Lp Nanofiber adhesives used in medical devices
US20110172498A1 (en) 2009-09-14 2011-07-14 Olsen Gregory A Spot check monitor credit system
US20110137297A1 (en) 2009-09-17 2011-06-09 Kiani Massi Joe E Pharmacological management system
WO2011035070A1 (en) 2009-09-17 2011-03-24 Masimo Laboratories, Inc. Improving analyte monitoring using one or more accelerometers
US8840562B2 (en) * 2009-09-24 2014-09-23 Covidien Lp Signal processing warping technique
US8571618B1 (en) 2009-09-28 2013-10-29 Cercacor Laboratories, Inc. Adaptive calibration system for spectrophotometric measurements
US9066660B2 (en) * 2009-09-29 2015-06-30 Nellcor Puritan Bennett Ireland Systems and methods for high-pass filtering a photoplethysmograph signal
US20110082711A1 (en) * 2009-10-06 2011-04-07 Masimo Laboratories, Inc. Personal digital assistant or organizer for monitoring glucose levels
US8430817B1 (en) 2009-10-15 2013-04-30 Masimo Corporation System for determining confidence in respiratory rate measurements
US9106038B2 (en) 2009-10-15 2015-08-11 Masimo Corporation Pulse oximetry system with low noise cable hub
US8821415B2 (en) 2009-10-15 2014-09-02 Masimo Corporation Physiological acoustic monitoring system
WO2011047216A2 (en) 2009-10-15 2011-04-21 Masimo Corporation Physiological acoustic monitoring system
US8702627B2 (en) 2009-10-15 2014-04-22 Masimo Corporation Acoustic respiratory monitoring sensor having multiple sensing elements
US9848800B1 (en) 2009-10-16 2017-12-26 Masimo Corporation Respiratory pause detector
WO2011063106A1 (en) * 2009-11-18 2011-05-26 Nellcor Puritan Bennett Llc Intelligent user interface for medical monitors
US8801613B2 (en) 2009-12-04 2014-08-12 Masimo Corporation Calibration for multi-stage physiological monitors
US20110230733A1 (en) * 2010-01-19 2011-09-22 Masimo Corporation Wellness analysis system
US20110184296A1 (en) * 2010-01-27 2011-07-28 Newcardio, Inc. Method and system for quantitative assessment of cardiac electrical events
US8584345B2 (en) 2010-03-08 2013-11-19 Masimo Corporation Reprocessing of a physiological sensor
US9307928B1 (en) 2010-03-30 2016-04-12 Masimo Corporation Plethysmographic respiration processor
US8498683B2 (en) 2010-04-30 2013-07-30 Covidien LLP Method for respiration rate and blood pressure alarm management
US8712494B1 (en) 2010-05-03 2014-04-29 Masimo Corporation Reflective non-invasive sensor
US7884933B1 (en) 2010-05-05 2011-02-08 Revolutionary Business Concepts, Inc. Apparatus and method for determining analyte concentrations
US8666468B1 (en) 2010-05-06 2014-03-04 Masimo Corporation Patient monitor for determining microcirculation state
US9326712B1 (en) 2010-06-02 2016-05-03 Masimo Corporation Opticoustic sensor
US8740792B1 (en) 2010-07-12 2014-06-03 Masimo Corporation Patient monitor capable of accounting for environmental conditions
US9649054B2 (en) 2010-08-26 2017-05-16 Cercacor Laboratories, Inc. Blood pressure measurement method
US9211095B1 (en) 2010-10-13 2015-12-15 Masimo Corporation Physiological measurement logic engine
US8723677B1 (en) 2010-10-20 2014-05-13 Masimo Corporation Patient safety system with automatically adjusting bed
US9066666B2 (en) 2011-02-25 2015-06-30 Cercacor Laboratories, Inc. Patient monitor for monitoring microcirculation
WO2012117785A1 (en) * 2011-02-28 2012-09-07 日本光電工業株式会社 Bioelectric signal-measuring apparatus
US8830449B1 (en) 2011-04-18 2014-09-09 Cercacor Laboratories, Inc. Blood analysis system
US9095316B2 (en) 2011-04-20 2015-08-04 Masimo Corporation System for generating alarms based on alarm patterns
US9622692B2 (en) 2011-05-16 2017-04-18 Masimo Corporation Personal health device
US9532722B2 (en) 2011-06-21 2017-01-03 Masimo Corporation Patient monitoring system
US9986919B2 (en) 2011-06-21 2018-06-05 Masimo Corporation Patient monitoring system
US9245668B1 (en) 2011-06-29 2016-01-26 Cercacor Laboratories, Inc. Low noise cable providing communication between electronic sensor components and patient monitor
US9192351B1 (en) 2011-07-22 2015-11-24 Masimo Corporation Acoustic respiratory monitoring sensor with probe-off detection
EP2734103A4 (en) 2011-07-22 2014-11-05 Flashback Technologies Inc Hemodynamic reserve monitor and hemodialysis control
US8755872B1 (en) 2011-07-28 2014-06-17 Masimo Corporation Patient monitoring system for indicating an abnormal condition
US9323894B2 (en) 2011-08-19 2016-04-26 Masimo Corporation Health care sanitation monitoring system
US8880576B2 (en) 2011-09-23 2014-11-04 Nellcor Puritan Bennett Ireland Systems and methods for determining respiration information from a photoplethysmograph
US9693709B2 (en) 2011-09-23 2017-07-04 Nellcot Puritan Bennett Ireland Systems and methods for determining respiration information from a photoplethysmograph
US9119597B2 (en) 2011-09-23 2015-09-01 Nellcor Puritan Bennett Ireland Systems and methods for determining respiration information from a photoplethysmograph
US9675274B2 (en) 2011-09-23 2017-06-13 Nellcor Puritan Bennett Ireland Systems and methods for determining respiration information from a photoplethysmograph
US9402554B2 (en) 2011-09-23 2016-08-02 Nellcor Puritan Bennett Ireland Systems and methods for determining respiration information from a photoplethysmograph
US9808188B1 (en) 2011-10-13 2017-11-07 Masimo Corporation Robust fractional saturation determination
EP2765909A1 (en) 2011-10-13 2014-08-20 Masimo Corporation Physiological acoustic monitoring system
US9778079B1 (en) 2011-10-27 2017-10-03 Masimo Corporation Physiological monitor gauge panel
US8755871B2 (en) 2011-11-30 2014-06-17 Covidien Lp Systems and methods for detecting arrhythmia from a physiological signal
US9693736B2 (en) 2011-11-30 2017-07-04 Nellcor Puritan Bennett Ireland Systems and methods for determining respiration information using historical distribution
US9445759B1 (en) 2011-12-22 2016-09-20 Cercacor Laboratories, Inc. Blood glucose calibration system
US9392945B2 (en) 2012-01-04 2016-07-19 Masimo Corporation Automated CCHD screening and detection
US9247896B2 (en) 2012-01-04 2016-02-02 Nellcor Puritan Bennett Ireland Systems and methods for determining respiration information using phase locked loop
US9480435B2 (en) 2012-02-09 2016-11-01 Masimo Corporation Configurable patient monitoring system
WO2013148605A1 (en) 2012-03-25 2013-10-03 Masimo Corporation Physiological monitor touchscreen interface
US9179876B2 (en) 2012-04-30 2015-11-10 Nellcor Puritan Bennett Ireland Systems and methods for identifying portions of a physiological signal usable for determining physiological information
US9697928B2 (en) 2012-08-01 2017-07-04 Masimo Corporation Automated assembly sensor cable
US9955937B2 (en) 2012-09-20 2018-05-01 Masimo Corporation Acoustic patient sensor coupler
US9749232B2 (en) 2012-09-20 2017-08-29 Masimo Corporation Intelligent medical network edge router
US9724025B1 (en) 2013-01-16 2017-08-08 Masimo Corporation Active-pulse blood analysis system
US9560978B2 (en) 2013-02-05 2017-02-07 Covidien Lp Systems and methods for determining respiration information from a physiological signal using amplitude demodulation
US9687159B2 (en) 2013-02-27 2017-06-27 Covidien Lp Systems and methods for determining physiological information by identifying fiducial points in a physiological signal
US9554712B2 (en) 2013-02-27 2017-01-31 Covidien Lp Systems and methods for generating an artificial photoplethysmograph signal
US9986952B2 (en) 2013-03-14 2018-06-05 Masimo Corporation Heart sound simulator
US9474474B2 (en) 2013-03-14 2016-10-25 Masimo Corporation Patient monitor as a minimally invasive glucometer
US10022068B2 (en) 2013-10-28 2018-07-17 Covidien Lp Systems and methods for detecting held breath events
WO2015105787A1 (en) 2014-01-07 2015-07-16 Covidien Lp Apnea analysis system and method
US9901308B2 (en) 2014-02-20 2018-02-27 Covidien Lp Systems and methods for filtering autocorrelation peaks and detecting harmonics
US10258288B2 (en) * 2014-03-24 2019-04-16 Samsung Electronics Co., Ltd. Confidence indicator for physiological measurements using a wearable sensor platform
KR101560521B1 (en) * 2014-06-05 2015-10-14 길영준 Method, system and non-transitory computer-readable recording medium for monitoring real-time blood pressure
US9924897B1 (en) 2014-06-12 2018-03-27 Masimo Corporation Heated reprocessing of physiological sensors
US10231657B2 (en) 2014-09-04 2019-03-19 Masimo Corporation Total hemoglobin screening sensor
USD755392S1 (en) 2015-02-06 2016-05-03 Masimo Corporation Pulse oximetry sensor
JP2018112899A (en) * 2017-01-11 2018-07-19 横河電機株式会社 Data processing apparatus, data processing method, and program

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5303702A (en) * 1990-12-27 1994-04-19 Ela Medical Automatic adjustment of the control function for a rate adaptive pacemaker
US5626140A (en) * 1995-11-01 1997-05-06 Spacelabs Medical, Inc. System and method of multi-sensor fusion of physiological measurements
US5697958A (en) * 1995-06-07 1997-12-16 Intermedics, Inc. Electromagnetic noise detector for implantable medical devices
US6135952A (en) * 1998-03-11 2000-10-24 Siemens Corporate Research, Inc. Adaptive filtering of physiological signals using a modeled synthetic reference signal

Family Cites Families (236)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US4051522A (en) 1975-05-05 1977-09-27 Jonathan Systems Patient monitoring system
JPS5220753A (en) 1975-06-11 1977-02-16 Motorola Inc Quadrature phase shift keying demodulator
EP0104771B1 (en) 1982-09-02 1990-05-23 Nellcor Incorporated Pulse oximeter monitor
US4653498B1 (en) * 1982-09-13 1989-04-18
DE3328862A1 (en) 1982-09-16 1985-02-28 Siemens Ag Tissue photometry method and device, in particular for quantatively determining the blood oxygen saturation from photometric measurements
EP0137769A4 (en) 1983-02-14 1987-01-22 Arrhythmia Res Technology Inc System and method for predicting ventricular tachycardia.
US4623248A (en) 1983-02-16 1986-11-18 Abbott Laboratories Apparatus and method for determining oxygen saturation levels with increased accuracy
US4911167A (en) 1985-06-07 1990-03-27 Nellcor Incorporated Method and apparatus for detecting optical pulses
US4934372A (en) 1985-04-01 1990-06-19 Nellcor Incorporated Method and apparatus for detecting optical pulses
US4802486A (en) 1985-04-01 1989-02-07 Nellcor Incorporated Method and apparatus for detecting optical pulses
JPS61228831A (en) 1985-04-02 1986-10-13 Minolta Camera Kk Apparatus for detecting non-respiration fit
US4870588A (en) 1985-10-21 1989-09-26 Sundstrand Data Control, Inc. Signal processor for inertial measurement using coriolis force sensing accelerometer arrangements
US5259381A (en) 1986-08-18 1993-11-09 Physio-Control Corporation Apparatus for the automatic calibration of signals employed in oximetry
US4800495A (en) 1986-08-18 1989-01-24 Physio-Control Corporation Method and apparatus for processing signals used in oximetry
JPS6365845A (en) 1986-09-05 1988-03-24 Minolta Camera Kk Oximeter apparatus
US4745398A (en) 1987-02-09 1988-05-17 Sentrol, Inc. Self-powered sensor for use in closed-loop security system
USRE33643E (en) 1987-04-30 1991-07-23 Nonin Medical, Inc. Pulse oximeter with circuit leakage and ambient light compensation
GB8719333D0 (en) 1987-08-14 1987-09-23 Swansea University College Of Motion artefact rejection system
US4863265A (en) 1987-10-16 1989-09-05 Mine Safety Appliances Company Apparatus and method for measuring blood constituents
US4965840A (en) 1987-11-27 1990-10-23 State University Of New York Method and apparatus for determining the distances between surface-patches of a three-dimensional spatial scene and a camera system
US5041187A (en) 1988-04-29 1991-08-20 Thor Technology Corporation Oximeter sensor assembly with integral cable and method of forming the same
US4964408A (en) 1988-04-29 1990-10-23 Thor Technology Corporation Oximeter sensor assembly with integral cable
US5069213A (en) 1988-04-29 1991-12-03 Thor Technology Corporation Oximeter sensor assembly with integral cable and encoder
EP0352923A1 (en) 1988-07-25 1990-01-31 BAXTER INTERNATIONAL INC. (a Delaware corporation) Spectrophotometric apparatus and method for monitoring oxygen saturation
DE3836417A1 (en) * 1988-10-26 1990-05-03 Bodenseewerk Geraetetech measured variable influenced for generating a schaetzwertes a filter assembly by disturbances
US5163438A (en) 1988-11-14 1992-11-17 Paramed Technology Incorporated Method and apparatus for continuously and noninvasively measuring the blood pressure of a patient
US4960128A (en) 1988-11-14 1990-10-02 Paramed Technology Incorporated Method and apparatus for continuously and non-invasively measuring the blood pressure of a patient
US5353356A (en) 1989-02-09 1994-10-04 Waugh Richard M Product gauge methods and apparatus for use in the optical determination of the acceptability of products
US5193124A (en) 1989-06-29 1993-03-09 The Research Foundation Of State University Of New York Computational methods and electronic camera apparatus for determining distance of objects, rapid autofocusing, and obtaining improved focus images
US5003252A (en) 1989-08-16 1991-03-26 Load Controls Incorporated Apparatus and method for measuring power factor and torque on the output of variable frequency drives
US5018088A (en) * 1989-10-02 1991-05-21 The Johns Hopkins University Adaptive locally-optimum detection signal processor and processing methods
US5190038A (en) 1989-11-01 1993-03-02 Novametrix Medical Systems, Inc. Pulse oximeter with improved accuracy and response time
CA2030272C (en) 1989-11-24 1995-06-27 David R. Brunfeldt Vector network analyzer
EP0442011A1 (en) 1990-02-15 1991-08-21 Hewlett-Packard GmbH Sensor, apparatus and method for non-invasive measurement of oxygen saturation
GB9011887D0 (en) 1990-05-26 1990-07-18 Le Fit Ltd Pulse responsive device
US5136267A (en) * 1990-12-26 1992-08-04 Audio Precision, Inc. Tunable bandpass filter system and filtering method
WO1992011803A1 (en) 1991-01-07 1992-07-23 Baxter International Inc. Cardiopulmonary monitoring system with integrated blood oxygenation signal quality indicator
US5720293A (en) 1991-01-29 1998-02-24 Baxter International Inc. Diagnostic catheter with memory
JPH0614922B2 (en) * 1991-02-15 1994-03-02 日本光電工業株式会社 Calibration test equipment for pulse oximeter
MX9702434A (en) * 1991-03-07 1998-05-31 Masimo Corp Signal processing apparatus.
US7376453B1 (en) 1993-10-06 2008-05-20 Masimo Corporation Signal processing apparatus
US5632272A (en) 1991-03-07 1997-05-27 Masimo Corporation Signal processing apparatus
US5490505A (en) 1991-03-07 1996-02-13 Masimo Corporation Signal processing apparatus
EP0930045A3 (en) 1991-03-07 1999-10-27 Masimo Corporation Signal processing apparatus and method for an oximeter
US5226417A (en) 1991-03-11 1993-07-13 Nellcor, Inc. Apparatus for the detection of motion transients
US5638818A (en) 1991-03-21 1997-06-17 Masimo Corporation Low noise optical probe
US6541756B2 (en) 1991-03-21 2003-04-01 Masimo Corporation Shielded optical probe having an electrical connector
US5170791A (en) 1991-03-28 1992-12-15 Hewlett-Packard Company Method and apparatus for calculating the fetal heart rate
US5377676A (en) * 1991-04-03 1995-01-03 Cedars-Sinai Medical Center Method for determining the biodistribution of substances using fluorescence spectroscopy
JPH05189617A (en) 1991-04-15 1993-07-30 Microsoft Corp Method and device for segmentation of arc in hand-written character recognition
US5218962A (en) 1991-04-15 1993-06-15 Nellcor Incorporated Multiple region pulse oximetry probe and oximeter
DE69229554D1 (en) 1991-05-16 1999-08-12 Non Invasive Technology Inc Hemoglobin measurement for determination of metabolic parameters of a person
US5934277A (en) * 1991-09-03 1999-08-10 Datex-Ohmeda, Inc. System for pulse oximetry SpO2 determination
US5481620A (en) 1991-09-27 1996-01-02 E. I. Du Pont De Nemours And Company Adaptive vision system
US5442940A (en) 1991-10-24 1995-08-22 Hewlett-Packard Company Apparatus and method for evaluating the fetal condition
US5246002A (en) 1992-02-11 1993-09-21 Physio-Control Corporation Noise insensitive pulse transmittance oximeter
US5331394A (en) 1992-04-10 1994-07-19 Metaphase Corporation Automated lensometer
JP3116252B2 (en) 1992-07-09 2000-12-11 日本光電工業株式会社 Pulse Oximeter
US5345510A (en) 1992-07-13 1994-09-06 Rauland-Borg Corporation Integrated speaker supervision and alarm system
US5542421A (en) 1992-07-31 1996-08-06 Frederick Erdman Association Method and apparatus for cardiovascular diagnosis
WO1994004071A1 (en) 1992-08-19 1994-03-03 Lynn Lawrence A Apparatus for the diagnosis of sleep apnea
WO1995021567A1 (en) 1992-09-15 1995-08-17 Increa Oy Method and apparatus for measuring physical condition
US5368224A (en) 1992-10-23 1994-11-29 Nellcor Incorporated Method for reducing ambient noise effects in electronic monitoring instruments
US5270942A (en) 1992-12-04 1993-12-14 United Technologies Corporation Processing ultrasonic measurements of a rotating hollow workpiece
AT165962T (en) 1992-12-07 1998-05-15 Andromed Inc electronic stethoscope
US5384451A (en) 1993-01-29 1995-01-24 United Parcel Service Of America, Inc. Method and apparatus for decoding bar code symbols using composite signals
US5404003A (en) 1993-02-01 1995-04-04 United Parcel Service Of America, Inc. Method and apparatus for decoding bar code symbols using byte-based searching
US5406952A (en) 1993-02-11 1995-04-18 Biosyss Corporation Blood pressure monitoring system
US5341805A (en) 1993-04-06 1994-08-30 Cedars-Sinai Medical Center Glucose fluorescence monitor and method
US5494043A (en) 1993-05-04 1996-02-27 Vital Insite, Inc. Arterial sensor
DE69428119T2 (en) 1993-07-07 2002-03-21 Picturetel Corp Reduction of the background noise for speech enhancement
US5337744A (en) 1993-07-14 1994-08-16 Masimo Corporation Low noise finger cot probe
US5452717A (en) 1993-07-14 1995-09-26 Masimo Corporation Finger-cot probe
US5438983A (en) 1993-09-13 1995-08-08 Hewlett-Packard Company Patient alarm detection using trend vector analysis
JP3387171B2 (en) 1993-09-28 2003-03-17 セイコーエプソン株式会社 Pulse wave detecting apparatus and motion intensity measuring apparatus
US5456252A (en) 1993-09-30 1995-10-10 Cedars-Sinai Medical Center Induced fluorescence spectroscopy blood perfusion and pH monitor and method
US5357965A (en) 1993-11-24 1994-10-25 General Electric Company Method for controlling adaptive color flow processing using fuzzy logic
JP2816944B2 (en) 1993-12-20 1998-10-27 セイコーインスツルメンツ株式会社 Pulse meter
US5533511A (en) 1994-01-05 1996-07-09 Vital Insite, Incorporated Apparatus and method for noninvasive blood pressure measurement
USD359546S (en) 1994-01-27 1995-06-20 The Ratechnologies Inc. Housing for a dental unit disinfecting device
US5553615A (en) * 1994-01-31 1996-09-10 Minnesota Mining And Manufacturing Company Method and apparatus for noninvasive prediction of hematocrit
US5398003A (en) 1994-03-30 1995-03-14 Apple Computer, Inc. Pulse width modulation speaker amplifier
US5575284A (en) 1994-04-01 1996-11-19 University Of South Florida Portable pulse oximeter
US5421329A (en) 1994-04-01 1995-06-06 Nellcor, Inc. Pulse oximeter sensor optimized for low saturation
US5590649A (en) 1994-04-15 1997-01-07 Vital Insite, Inc. Apparatus and method for measuring an induced perturbation to determine blood pressure
US6371921B1 (en) * 1994-04-15 2002-04-16 Masimo Corporation System and method of determining whether to recalibrate a blood pressure monitor
US5810734A (en) 1994-04-15 1998-09-22 Vital Insite, Inc. Apparatus and method for measuring an induced perturbation to determine a physiological parameter
US5791347A (en) 1994-04-15 1998-08-11 Vital Insite, Inc. Motion insensitive pulse detector
US5785659A (en) 1994-04-15 1998-07-28 Vital Insite, Inc. Automatically activated blood pressure measurement device
USD361840S (en) 1994-04-21 1995-08-29 Gary Savage Stethoscope head
USD362063S (en) 1994-04-21 1995-09-05 Gary Savage Stethoscope headset
USD363120S (en) 1994-04-21 1995-10-10 Gary Savage Stethoscope ear tip
US5561275A (en) 1994-04-28 1996-10-01 Delstar Services Informatiques (1993) Inc. Headset for electronic stethoscope
US5807267A (en) 1994-06-01 1998-09-15 Advanced Body Metrics Corporation Heart pulse monitor
US5549111A (en) 1994-08-05 1996-08-27 Acuson Corporation Method and apparatus for adjustable frequency scanning in ultrasound imaging
US5503148A (en) * 1994-11-01 1996-04-02 Ohmeda Inc. System for pulse oximetry SPO2 determination
US5562002A (en) 1995-02-03 1996-10-08 Sensidyne Inc. Positive displacement piston flow meter with damping assembly
US5511042A (en) * 1995-05-25 1996-04-23 The United States Of America As Represented By The Secretary Of The Navy Enhanced adaptive statistical filter providing improved performance for target motion analysis noise discrimination
US5758644A (en) * 1995-06-07 1998-06-02 Masimo Corporation Manual and automatic probe calibration
US5743262A (en) 1995-06-07 1998-04-28 Masimo Corporation Blood glucose monitoring system
US5760910A (en) 1995-06-07 1998-06-02 Masimo Corporation Optical filter for spectroscopic measurement and method of producing the optical filter
US6931268B1 (en) 1995-06-07 2005-08-16 Masimo Laboratories, Inc. Active pulse blood constituent monitoring
US5638816A (en) 1995-06-07 1997-06-17 Masimo Corporation Active pulse blood constituent monitoring
US5645060A (en) * 1995-06-14 1997-07-08 Nellcor Puritan Bennett Incorporated Method and apparatus for removing artifact and noise from pulse oximetry
US5957866A (en) * 1995-07-03 1999-09-28 University Technology Corporation Apparatus and methods for analyzing body sounds
US5558096A (en) * 1995-07-21 1996-09-24 Biochem International, Inc. Blood pulse detection method using autocorrelation
US5853364A (en) * 1995-08-07 1998-12-29 Nellcor Puritan Bennett, Inc. Method and apparatus for estimating physiological parameters using model-based adaptive filtering
US5645440A (en) 1995-10-16 1997-07-08 Masimo Corporation Patient cable connector
US5904654A (en) 1995-10-20 1999-05-18 Vital Insite, Inc. Exciter-detector unit for measuring physiological parameters
US5588435A (en) 1995-11-22 1996-12-31 Siemens Medical Systems, Inc. System and method for automatic measurement of body structures
US6232609B1 (en) * 1995-12-01 2001-05-15 Cedars-Sinai Medical Center Glucose monitoring apparatus and method using laser-induced emission spectroscopy
US5652566A (en) 1995-12-15 1997-07-29 Aequitron Medical, Inc. Alarm system
US5890929A (en) 1996-06-19 1999-04-06 Masimo Corporation Shielded medical connector
US6027452A (en) 1996-06-26 2000-02-22 Vital Insite, Inc. Rapid non-invasive blood pressure measuring device
JPH1075159A (en) * 1996-08-30 1998-03-17 Icom Inc Digital filter system
DE19647276A1 (en) * 1996-11-15 1998-05-20 Alsthom Cge Alcatel Method and apparatus for adaptive echo cancellation
SE9604320D0 (en) 1996-11-25 1996-11-25 Pacesetter Ab Medical device
US5921921A (en) 1996-12-18 1999-07-13 Nellcor Puritan-Bennett Pulse oximeter with sigma-delta converter
US5842979A (en) 1997-02-14 1998-12-01 Ohmeda Inc. Method and apparatus for improved photoplethysmographic monitoring of oxyhemoglobin, deoxyhemoglobin, carboxyhemoglobin and methemoglobin
JP4555919B2 (en) 1997-03-17 2010-10-06 ノンインベイシブ モニタリング システムズ インコーポレイテッド Feedback system of physiological sign
AU736060B2 (en) 1997-03-21 2001-07-26 Nellcor Puritan Bennett Inc. Method and apparatus for arbitrating to obtain best estimates for blood constituent values and rejecting harmonics
DE69700253D1 (en) 1997-04-12 1999-07-08 Hewlett Packard Co Method and apparatus for determining the concentration of a constituent
US6002952A (en) 1997-04-14 1999-12-14 Masimo Corporation Signal processing apparatus and method
US6229856B1 (en) 1997-04-14 2001-05-08 Masimo Corporation Method and apparatus for demodulating signals in a pulse oximetry system
US5919134A (en) 1997-04-14 1999-07-06 Masimo Corp. Method and apparatus for demodulating signals in a pulse oximetry system
US6094627A (en) * 1997-05-30 2000-07-25 Perkinelmer Instruments, Inc. High-performance digital signal averager
US6124597A (en) 1997-07-07 2000-09-26 Cedars-Sinai Medical Center Method and devices for laser induced fluorescence attenuation spectroscopy
US5865736A (en) 1997-09-30 1999-02-02 Nellcor Puritan Bennett, Inc. Method and apparatus for nuisance alarm reductions
US5950139A (en) 1997-10-30 1999-09-07 Motorola, Inc. Radiotelephone with user perceivable visual signal quality indicator
US5987343A (en) 1997-11-07 1999-11-16 Datascope Investment Corp. Method for storing pulse oximetry sensor characteristics
US6119026A (en) 1997-12-04 2000-09-12 Hewlett-Packard Company Radiation apparatus and method for analysis of analytes in sample
US6184521B1 (en) 1998-01-06 2001-02-06 Masimo Corporation Photodiode detector with integrated noise shielding
US5995855A (en) 1998-02-11 1999-11-30 Masimo Corporation Pulse oximetry sensor adapter
US6241683B1 (en) 1998-02-20 2001-06-05 INSTITUT DE RECHERCHES CLINIQUES DE MONTRéAL (IRCM) Phonospirometry for non-invasive monitoring of respiration
US6188407B1 (en) 1998-03-04 2001-02-13 Critikon Company, Llc Reconfigurable user interface for modular patient monitor
US6525386B1 (en) 1998-03-10 2003-02-25 Masimo Corporation Non-protruding optoelectronic lens
US5997343A (en) 1998-03-19 1999-12-07 Masimo Corporation Patient cable sensor switch
US6165005A (en) 1998-03-19 2000-12-26 Masimo Corporation Patient cable sensor switch
US6728560B2 (en) * 1998-04-06 2004-04-27 The General Hospital Corporation Non-invasive tissue glucose level monitoring
US6721582B2 (en) * 1999-04-06 2004-04-13 Argose, Inc. Non-invasive tissue glucose level monitoring
US6505059B1 (en) * 1998-04-06 2003-01-07 The General Hospital Corporation Non-invasive tissue glucose level monitoring
US6094592A (en) * 1998-05-26 2000-07-25 Nellcor Puritan Bennett, Inc. Methods and apparatus for estimating a physiological parameter using transforms
CA2333062A1 (en) 1998-06-03 1999-12-09 Mohamed K. Diab Stereo pulse oximeter
US6285896B1 (en) 1998-07-13 2001-09-04 Masimo Corporation Fetal pulse oximetry sensor
US6108610A (en) * 1998-10-13 2000-08-22 Noise Cancellation Technologies, Inc. Method and system for updating noise estimates during pauses in an information signal
US6519486B1 (en) * 1998-10-15 2003-02-11 Ntc Technology Inc. Method, apparatus and system for removing motion artifacts from measurements of bodily parameters
US6721585B1 (en) 1998-10-15 2004-04-13 Sensidyne, Inc. Universal modular pulse oximeter probe for use with reusable and disposable patient attachment devices
US6343224B1 (en) 1998-10-15 2002-01-29 Sensidyne, Inc. Reusable pulse oximeter probe and disposable bandage apparatus
US6684091B2 (en) * 1998-10-15 2004-01-27 Sensidyne, Inc. Reusable pulse oximeter probe and disposable bandage method
US6144868A (en) 1998-10-15 2000-11-07 Sensidyne, Inc. Reusable pulse oximeter probe and disposable bandage apparatus
US6519487B1 (en) * 1998-10-15 2003-02-11 Sensidyne, Inc. Reusable pulse oximeter probe and disposable bandage apparatus
USRE41912E1 (en) 1998-10-15 2010-11-02 Masimo Corporation Reusable pulse oximeter probe and disposable bandage apparatus
US7245953B1 (en) 1999-04-12 2007-07-17 Masimo Corporation Reusable pulse oximeter probe and disposable bandage apparatii
US6463311B1 (en) 1998-12-30 2002-10-08 Masimo Corporation Plethysmograph pulse recognition processor
US6606511B1 (en) * 1999-01-07 2003-08-12 Masimo Corporation Pulse oximetry pulse indicator
US6684090B2 (en) * 1999-01-07 2004-01-27 Masimo Corporation Pulse oximetry data confidence indicator
DE60037106T2 (en) 1999-01-25 2008-09-11 Masimo Corp., Irvine Universal / improving pulse oximeter
US6658276B2 (en) 1999-01-25 2003-12-02 Masimo Corporation Pulse oximeter user interface
US6770028B1 (en) 1999-01-25 2004-08-03 Masimo Corporation Dual-mode pulse oximeter
US20020140675A1 (en) 1999-01-25 2002-10-03 Ali Ammar Al System and method for altering a display mode based on a gravity-responsive sensor
US6360114B1 (en) 1999-03-25 2002-03-19 Masimo Corporation Pulse oximeter probe-off detector
US6675031B1 (en) * 1999-04-14 2004-01-06 Mallinckrodt Inc. Method and circuit for indicating quality and accuracy of physiological measurements
US6216021B1 (en) * 1999-06-04 2001-04-10 The Board Of Trustees Of The University Of Illinois Method for measuring absolute saturation of time-varying and other hemoglobin compartments
WO2000078209A2 (en) 1999-06-18 2000-12-28 Masimo Corporation Pulse oximeter probe-off detection system
US6321100B1 (en) 1999-07-13 2001-11-20 Sensidyne, Inc. Reusable pulse oximeter probe with disposable liner
US6515273B2 (en) * 1999-08-26 2003-02-04 Masimo Corporation System for indicating the expiration of the useful operating life of a pulse oximetry sensor
US6580086B1 (en) 1999-08-26 2003-06-17 Masimo Corporation Shielded optical probe and method
US6943348B1 (en) 1999-10-19 2005-09-13 Masimo Corporation System for detecting injection holding material
US6639668B1 (en) 1999-11-03 2003-10-28 Argose, Inc. Asynchronous fluorescence scan
US6542764B1 (en) 1999-12-01 2003-04-01 Masimo Corporation Pulse oximeter monitor for expressing the urgency of the patient's condition
US6377829B1 (en) * 1999-12-09 2002-04-23 Masimo Corporation Resposable pulse oximetry sensor
US6950687B2 (en) 1999-12-09 2005-09-27 Masimo Corporation Isolation and communication element for a resposable pulse oximetry sensor
US6671531B2 (en) 1999-12-09 2003-12-30 Masimo Corporation Sensor wrap including foldable applicator
US6408198B1 (en) * 1999-12-17 2002-06-18 Datex-Ohmeda, Inc. Method and system for improving photoplethysmographic analyte measurements by de-weighting motion-contaminated data
US6152754A (en) 1999-12-21 2000-11-28 Masimo Corporation Circuit board based cable connector
CA2400409A1 (en) 2000-02-18 2001-08-23 James Mansfield Multivariate analysis of green to ultraviolet spectra of cell and tissue samples
JP2003522578A (en) 2000-02-18 2003-07-29 アーゴス インク Spatially averaged excitation in heterogeneous tissues - generation of emission map
US6438401B1 (en) * 2000-04-28 2002-08-20 Alpha Intervention Technology, Inc. Indentification and quantification of needle displacement departures from treatment plan
US6430525B1 (en) * 2000-06-05 2002-08-06 Masimo Corporation Variable mode averager
US6470199B1 (en) 2000-06-21 2002-10-22 Masimo Corporation Elastic sock for positioning an optical probe
US6697656B1 (en) 2000-06-27 2004-02-24 Masimo Corporation Pulse oximetry sensor compatible with multiple pulse oximetry systems
US6640116B2 (en) 2000-08-18 2003-10-28 Masimo Corporation Optical spectroscopy pathlength measurement system
US6368283B1 (en) * 2000-09-08 2002-04-09 Institut De Recherches Cliniques De Montreal Method and apparatus for estimating systolic and mean pulmonary artery pressures of a patient
WO2002024065A1 (en) * 2000-09-22 2002-03-28 Knobbe, Lim & Buckingham Method and apparatus for real-time estimation and control of pysiological parameters
US6594512B2 (en) * 2000-11-21 2003-07-15 Siemens Medical Solutions Usa, Inc. Method and apparatus for estimating a physiological parameter from a physiological signal
US6760607B2 (en) * 2000-12-29 2004-07-06 Masimo Corporation Ribbon cable substrate pulse oximetry sensor
US6517283B2 (en) 2001-01-16 2003-02-11 Donald Edward Coffey Cascading chute drainage system
JP2004532526A (en) * 2001-05-03 2004-10-21 マシモ・コーポレイション Method of making a flex circuit shields the optical sensor and the flex circuit shield optical sensor
US7081095B2 (en) 2001-05-17 2006-07-25 Lynn Lawrence A Centralized hospital monitoring system for automatically detecting upper airway instability and for preventing and aborting adverse drug reactions
US6850787B2 (en) * 2001-06-29 2005-02-01 Masimo Laboratories, Inc. Signal component processor
US6697658B2 (en) 2001-07-02 2004-02-24 Masimo Corporation Low power pulse oximeter
US6595316B2 (en) * 2001-07-18 2003-07-22 Andromed, Inc. Tension-adjustable mechanism for stethoscope earpieces
US6754516B2 (en) * 2001-07-19 2004-06-22 Nellcor Puritan Bennett Incorporated Nuisance alarm reductions in a physiological monitor
US20030073890A1 (en) 2001-10-10 2003-04-17 Hanna D. Alan Plethysmographic signal processing method and system
US6829501B2 (en) 2001-12-20 2004-12-07 Ge Medical Systems Information Technologies, Inc. Patient monitor and method with non-invasive cardiac output monitoring
US6934570B2 (en) 2002-01-08 2005-08-23 Masimo Corporation Physiological sensor combination
US6822564B2 (en) 2002-01-24 2004-11-23 Masimo Corporation Parallel measurement alarm processor
US7355512B1 (en) * 2002-01-24 2008-04-08 Masimo Corporation Parallel alarm processor
WO2003065557A2 (en) * 2002-01-25 2003-08-07 Masimo Corporation Power supply rail controller
US6961598B2 (en) 2002-02-22 2005-11-01 Masimo Corporation Pulse and active pulse spectraphotometry
US7509494B2 (en) * 2002-03-01 2009-03-24 Masimo Corporation Interface cable
US6850788B2 (en) 2002-03-25 2005-02-01 Masimo Corporation Physiological measurement communications adapter
US6661161B1 (en) 2002-06-27 2003-12-09 Andromed Inc. Piezoelectric biological sound monitor with printed circuit board
US7096054B2 (en) 2002-08-01 2006-08-22 Masimo Corporation Low noise optical housing
US6763256B2 (en) * 2002-08-16 2004-07-13 Optical Sensors, Inc. Pulse oximeter
US7341559B2 (en) * 2002-09-14 2008-03-11 Masimo Corporation Pulse oximetry ear sensor
US7274955B2 (en) 2002-09-25 2007-09-25 Masimo Corporation Parameter compensated pulse oximeter
US7142901B2 (en) 2002-09-25 2006-11-28 Masimo Corporation Parameter compensated physiological monitor
US7096052B2 (en) 2002-10-04 2006-08-22 Masimo Corporation Optical probe including predetermined emission wavelength based on patient type
US7027849B2 (en) * 2002-11-22 2006-04-11 Masimo Laboratories, Inc. Blood parameter measurement system
US6970792B1 (en) 2002-12-04 2005-11-29 Masimo Laboratories, Inc. Systems and methods for determining blood oxygen saturation values using complex number encoding
US7225006B2 (en) 2003-01-23 2007-05-29 Masimo Corporation Attachment and optical probe
US6920345B2 (en) * 2003-01-24 2005-07-19 Masimo Corporation Optical sensor including disposable and reusable elements
US7003338B2 (en) * 2003-07-08 2006-02-21 Masimo Corporation Method and apparatus for reducing coupling between signals
US7500950B2 (en) * 2003-07-25 2009-03-10 Masimo Corporation Multipurpose sensor port
US7254431B2 (en) 2003-08-28 2007-08-07 Masimo Corporation Physiological parameter tracking system
US7254434B2 (en) 2003-10-14 2007-08-07 Masimo Corporation Variable pressure reusable sensor
US7483729B2 (en) * 2003-11-05 2009-01-27 Masimo Corporation Pulse oximeter access apparatus and method
US7373193B2 (en) 2003-11-07 2008-05-13 Masimo Corporation Pulse oximetry data capture system
US7280858B2 (en) 2004-01-05 2007-10-09 Masimo Corporation Pulse oximetry sensor
US7371981B2 (en) 2004-02-20 2008-05-13 Masimo Corporation Connector switch
US7438683B2 (en) 2004-03-04 2008-10-21 Masimo Corporation Application identification sensor
EP1722676B1 (en) 2004-03-08 2012-12-19 Masimo Corporation Physiological parameter system
US7292883B2 (en) 2004-03-31 2007-11-06 Masimo Corporation Physiological assessment system
US7343186B2 (en) * 2004-07-07 2008-03-11 Masimo Laboratories, Inc. Multi-wavelength physiological monitor
USD566282S1 (en) * 2005-02-18 2008-04-08 Masimo Corporation Stand for a portable patient monitor
USD554263S1 (en) 2005-02-18 2007-10-30 Masimo Corporation Portable patient monitor
US7647083B2 (en) * 2005-03-01 2010-01-12 Masimo Laboratories, Inc. Multiple wavelength sensor equalization
CA2604653A1 (en) 2005-04-13 2006-10-19 Glucolight Corporation Method for data reduction and calibration of an oct-based blood glucose monitor
US7530942B1 (en) 2005-10-18 2009-05-12 Masimo Corporation Remote sensing infant warmer
US7791155B2 (en) 2006-12-22 2010-09-07 Masimo Laboratories, Inc. Detector shield
USD587657S1 (en) * 2007-10-12 2009-03-03 Masimo Corporation Connector assembly
USD609193S1 (en) * 2007-10-12 2010-02-02 Masimo Corporation Connector assembly
USD614305S1 (en) * 2008-02-29 2010-04-20 Masimo Corporation Connector assembly
USD606659S1 (en) 2008-08-25 2009-12-22 Masimo Laboratories, Inc. Patient monitor
USD621516S1 (en) 2008-08-25 2010-08-10 Masimo Laboratories, Inc. Patient monitoring sensor

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5303702A (en) * 1990-12-27 1994-04-19 Ela Medical Automatic adjustment of the control function for a rate adaptive pacemaker
US5697958A (en) * 1995-06-07 1997-12-16 Intermedics, Inc. Electromagnetic noise detector for implantable medical devices
US5626140A (en) * 1995-11-01 1997-05-06 Spacelabs Medical, Inc. System and method of multi-sensor fusion of physiological measurements
US6135952A (en) * 1998-03-11 2000-10-24 Siemens Corporate Research, Inc. Adaptive filtering of physiological signals using a modeled synthetic reference signal

Cited By (82)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US9675286B2 (en) 1998-12-30 2017-06-13 Masimo Corporation Plethysmograph pulse recognition processor
US10130289B2 (en) 1999-01-07 2018-11-20 Masimo Corporation Pulse and confidence indicator displayed proximate plethysmograph
US10231676B2 (en) 1999-01-25 2019-03-19 Masimo Corporation Dual-mode patient monitor
US9814418B2 (en) 2001-06-29 2017-11-14 Masimo Corporation Sine saturation transform
US9848806B2 (en) 2001-07-02 2017-12-26 Masimo Corporation Low power pulse oximeter
US10213108B2 (en) 2002-03-25 2019-02-26 Masimo Corporation Arm mountable portable patient monitor
US9872623B2 (en) 2002-03-25 2018-01-23 Masimo Corporation Arm mountable portable patient monitor
US9795300B2 (en) 2002-03-25 2017-10-24 Masimo Corporation Wearable portable patient monitor
US10219706B2 (en) 2002-03-25 2019-03-05 Masimo Corporation Physiological measurement device
US9788735B2 (en) 2002-03-25 2017-10-17 Masimo Corporation Body worn mobile medical patient monitor
US10201298B2 (en) 2003-01-24 2019-02-12 Masimo Corporation Noninvasive oximetry optical sensor including disposable and reusable elements
US9801588B2 (en) 2003-07-08 2017-10-31 Cercacor Laboratories, Inc. Method and apparatus for reducing coupling between signals in a measurement system
US10058275B2 (en) 2003-07-25 2018-08-28 Masimo Corporation Multipurpose sensor port
US10098591B2 (en) 2004-03-08 2018-10-16 Masimo Corporation Physiological parameter system
US10130291B2 (en) 2004-08-11 2018-11-20 Masimo Corporation Method for data reduction and calibration of an OCT-based physiological monitor
US10251585B2 (en) 2005-03-01 2019-04-09 Cercacor Laboratories, Inc. Noninvasive multi-parameter patient monitor
US10123726B2 (en) 2005-03-01 2018-11-13 Cercacor Laboratories, Inc. Configurable physiological measurement system
US9750443B2 (en) 2005-03-01 2017-09-05 Cercacor Laboratories, Inc. Multiple wavelength sensor emitters
US10092249B2 (en) 2005-10-14 2018-10-09 Masimo Corporation Robust alarm system
US10226576B2 (en) 2006-05-15 2019-03-12 Masimo Corporation Sepsis monitor
US10188348B2 (en) 2006-06-05 2019-01-29 Masimo Corporation Parameter upgrade system
US9687160B2 (en) 2006-09-20 2017-06-27 Masimo Corporation Congenital heart disease monitor
US10194847B2 (en) 2006-10-12 2019-02-05 Masimo Corporation Perfusion index smoother
US10219746B2 (en) 2006-10-12 2019-03-05 Masimo Corporation Oximeter probe off indicator defining probe off space
US9949676B2 (en) 2006-10-12 2018-04-24 Masimo Corporation Patient monitor capable of monitoring the quality of attached probes and accessories
US9861305B1 (en) 2006-10-12 2018-01-09 Masimo Corporation Method and apparatus for calibration to reduce coupling between signals in a measurement system
US10064562B2 (en) 2006-10-12 2018-09-04 Masimo Corporation Variable mode pulse indicator
US9848807B2 (en) 2007-04-21 2017-12-26 Masimo Corporation Tissue profile wellness monitor
US10251586B2 (en) 2007-04-21 2019-04-09 Masimo Corporation Tissue profile wellness monitor
US10258266B1 (en) 2008-07-03 2019-04-16 Masimo Corporation Multi-stream data collection system for noninvasive measurement of blood constituents
US9717425B2 (en) 2008-07-03 2017-08-01 Masimo Corporation Noise shielding for a noninvaise device
US9591975B2 (en) 2008-07-03 2017-03-14 Masimo Corporation Contoured protrusion for improving spectroscopic measurement of blood constituents
US10258265B1 (en) 2008-07-03 2019-04-16 Masimo Corporation Multi-stream data collection system for noninvasive measurement of blood constituents
USRE47353E1 (en) 2008-07-29 2019-04-16 Masimo Corporation Alarm suspend system
USRE47244E1 (en) 2008-07-29 2019-02-19 Masimo Corporation Alarm suspend system
USRE47249E1 (en) 2008-07-29 2019-02-19 Masimo Corporation Alarm suspend system
US10255994B2 (en) 2009-03-04 2019-04-09 Masimo Corporation Physiological parameter alarm delay
US10007758B2 (en) 2009-03-04 2018-06-26 Masimo Corporation Medical monitoring system
US10032002B2 (en) 2009-03-04 2018-07-24 Masimo Corporation Medical monitoring system
US10205272B2 (en) 2009-03-11 2019-02-12 Masimo Corporation Magnetic connector
US9795739B2 (en) 2009-05-20 2017-10-24 Masimo Corporation Hemoglobin display and patient treatment
US10194848B1 (en) 2009-07-29 2019-02-05 Masimo Corporation Non-invasive physiological sensor cover
US10188331B1 (en) 2009-07-29 2019-01-29 Masimo Corporation Non-invasive physiological sensor cover
US9668680B2 (en) 2009-09-03 2017-06-06 Masimo Corporation Emitter driver for noninvasive patient monitor
US9839381B1 (en) 2009-11-24 2017-12-12 Cercacor Laboratories, Inc. Physiological measurement system with automatic wavelength adjustment
US9847002B2 (en) 2009-12-21 2017-12-19 Masimo Corporation Modular patient monitor
US9775570B2 (en) 2010-03-01 2017-10-03 Masimo Corporation Adaptive alarm system
USRE47218E1 (en) 2010-03-01 2019-02-05 Masimo Corporation Adaptive alarm system
US9876320B2 (en) 2010-05-03 2018-01-23 Masimo Corporation Sensor adapter cable
US10052037B2 (en) 2010-07-22 2018-08-21 Masimo Corporation Non-invasive blood pressure measurement system
US9775545B2 (en) 2010-09-28 2017-10-03 Masimo Corporation Magnetic electrical connector for patient monitors
US9538949B2 (en) 2010-09-28 2017-01-10 Masimo Corporation Depth of consciousness monitor including oximeter
US10159412B2 (en) 2010-12-01 2018-12-25 Cercacor Laboratories, Inc. Handheld processing device including medical applications for minimally and non invasive glucose measurements
US9579039B2 (en) 2011-01-10 2017-02-28 Masimo Corporation Non-invasive intravascular volume index monitor
US9782077B2 (en) 2011-08-17 2017-10-10 Masimo Corporation Modulated physiological sensor
US9943269B2 (en) 2011-10-13 2018-04-17 Masimo Corporation System for displaying medical monitoring data
US9913617B2 (en) 2011-10-13 2018-03-13 Masimo Corporation Medical monitoring hub
US9993207B2 (en) 2011-10-13 2018-06-12 Masimo Corporation Medical monitoring hub
USD788312S1 (en) 2012-02-09 2017-05-30 Masimo Corporation Wireless patient monitoring device
US10149616B2 (en) 2012-02-09 2018-12-11 Masimo Corporation Wireless patient monitoring device
US10188296B2 (en) 2012-02-09 2019-01-29 Masimo Corporation Wireless patient monitoring device
US9775546B2 (en) 2012-04-17 2017-10-03 Masimo Corporation Hypersaturation index
US9717458B2 (en) 2012-10-20 2017-08-01 Masimo Corporation Magnetic-flap optical sensor
US9560996B2 (en) 2012-10-30 2017-02-07 Masimo Corporation Universal medical system
US9787568B2 (en) 2012-11-05 2017-10-10 Cercacor Laboratories, Inc. Physiological test credit method
US9750461B1 (en) 2013-01-02 2017-09-05 Masimo Corporation Acoustic respiratory monitoring sensor with probe-off detection
US9750442B2 (en) 2013-03-09 2017-09-05 Masimo Corporation Physiological status monitor
US9936917B2 (en) 2013-03-14 2018-04-10 Masimo Laboratories, Inc. Patient monitor placement indicator
US9891079B2 (en) 2013-07-17 2018-02-13 Masimo Corporation Pulser with double-bearing position encoder for non-invasive physiological monitoring
US10010276B2 (en) 2013-10-07 2018-07-03 Masimo Corporation Regional oximetry user interface
US9839379B2 (en) 2013-10-07 2017-12-12 Masimo Corporation Regional oximetry pod
US10086138B1 (en) 2014-01-28 2018-10-02 Masimo Corporation Autonomous drug delivery system
US10231670B2 (en) 2014-06-19 2019-03-19 Masimo Corporation Proximity sensor in pulse oximeter
US10154815B2 (en) 2014-10-07 2018-12-18 Masimo Corporation Modular physiological sensors
US10205291B2 (en) 2015-02-06 2019-02-12 Masimo Corporation Pogo pin connector
US10226187B2 (en) 2015-08-31 2019-03-12 Masimo Corporation Patient-worn wireless physiological sensor
USD835285S1 (en) 2017-04-28 2018-12-04 Masimo Corporation Medical monitoring device
USD835284S1 (en) 2017-04-28 2018-12-04 Masimo Corporation Medical monitoring device
USD835282S1 (en) 2017-04-28 2018-12-04 Masimo Corporation Medical monitoring device
USD835283S1 (en) 2017-04-28 2018-12-04 Masimo Corporation Medical monitoring device
US10271748B2 (en) 2017-09-19 2019-04-30 Masimo Corporation Patient monitor for determining microcirculation state
US10271749B2 (en) 2017-10-30 2019-04-30 Masimo Corporation Patient monitor for monitoring microcirculation

Also Published As

Publication number Publication date
US8489364B2 (en) 2013-07-16
EP1286619A4 (en) 2005-03-16
US7499835B2 (en) 2009-03-03
US7873497B2 (en) 2011-01-18
JP2003535417A (en) 2003-11-25
US6430525B1 (en) 2002-08-06
EP1286619A1 (en) 2003-03-05
EP1286619B1 (en) 2011-04-20
US20120330562A1 (en) 2012-12-27
US9138192B2 (en) 2015-09-22
US8260577B2 (en) 2012-09-04
US20110112799A1 (en) 2011-05-12
DE60144474D1 (en) 2011-06-01
US20090204371A1 (en) 2009-08-13
US20060161389A1 (en) 2006-07-20
US20030101027A1 (en) 2003-05-29
US20140025306A1 (en) 2014-01-23
US6999904B2 (en) 2006-02-14
WO2001093757A1 (en) 2001-12-13
US20180256113A1 (en) 2018-09-13

Similar Documents

Publication Publication Date Title
US5772601A (en) Apparatus for evaluating cardiac function of living subject
US8652060B2 (en) Perfusion trend indicator
EP0870465B1 (en) Method and apparatus for the non-invasive determination of the concentration of a component
US10194847B2 (en) Perfusion index smoother
US8852094B2 (en) Physiological parameter system
JP4360699B2 (en) Method for detecting system and the blood oxygen saturation detecting blood oxygen saturation
EP0993803B1 (en) Blood-pressure monitoring apparatus
US6850787B2 (en) Signal component processor
US5299120A (en) Method for digitally processing signals containing information regarding arterial blood flow
US5503148A (en) System for pulse oximetry SPO2 determination
JP4748854B2 (en) The methods and media for the sensor to determine whether it is connected to the blood perfusion tissue samples
US6594512B2 (en) Method and apparatus for estimating a physiological parameter from a physiological signal
JP4865737B2 (en) Reliability of physiological parameters
US5259381A (en) Apparatus for the automatic calibration of signals employed in oximetry
US7720516B2 (en) Motion compatible sensor for non-invasive optical blood analysis
CA2454057C (en) Nuisance alarm reductions in a physiological monitor
US7291112B2 (en) Method and apparatus for control of non-invasive parameter measurements
US5237997A (en) Method of continuous measurement of blood pressure in humans
US6839580B2 (en) Adaptive calibration for pulse oximetry
JP3124073B2 (en) Blood oxygen saturation monitoring device
US8682407B2 (en) Cyanotic infant sensor
JP4338242B2 (en) Apparatus for reducing the level of artifact signal in physiological signals
EP0262779A1 (en) Method and apparatus for the automatic calibration of signals employed in oximetry
US5687722A (en) System and method for the algebraic derivation of physiological signals
US6022320A (en) Blood pressure monitor apparatus