The present disclosure relates generally to non-invasive measurement of physiological parameters and, more particularly, to multi-wavelength photon density wave measurements of physiological parameters.
This section is intended to introduce the reader to various aspects of art that may be related to various aspects of the present disclosure, which are described and/or claimed below. This discussion is believed to be helpful in providing the reader with background information to facilitate a better understanding of the various aspects of the present disclosure. Accordingly, it should be understood that these statements are to be read in this light, and not as admissions of prior art.
Pulse oximetry may be defined as a non-invasive technique that facilitates monitoring of a patient's blood flow characteristics. For example, pulse oximetry may be used to measure blood oxygen saturation of hemoglobin in a patient's arterial blood and/or the patient's heart rate. Specifically, these blood flow characteristic measurements may be acquired using a non-invasive sensor that passes light through a portion of a patient's tissue and photo-electrically senses the absorption and scattering of the light through the tissue. Typical pulse oximetry technology may employ two light emitting diodes (LEDs) and a single optical detector to measure pulse and oxygen saturation of a given tissue bed.
A typical signal resulting from the sensed light may be referred to as a plethysmograph waveform. The plethysmograph waveform is largely based on absorption of emitted light by specific types of blood constituents and may be used with various algorithms to estimate a relative amount of blood constituent in the tissue. For example, the plethysmograph waveform may provide a ratio of oxygenated hemoglobin to total hemoglobin in the volume being monitored. The amount of arterial blood in the tissue is generally time-varying during a cardiac cycle, which is reflected in the plethysmographic waveform.
The accuracy of blood flow characteristic estimation via pulse oximetry may depend on a number of factors. For example, variations in light absorption characteristics can affect accuracy, and such variations may depend on where the sensor is located and/or the physiology of the patient being monitored. Additionally, various types of noise and interference can create inaccuracies. For example, electrical noise, physiological noise, and other interference can contribute to inaccurate blood flow characteristic estimates.
Advantages of the presently disclosed subject matter may become apparent upon reading the following detailed description and upon reference to the drawings in which:
One or more specific embodiments of the present disclosure will be described below. In an effort to provide a concise description of these embodiments, not all features of an actual implementation are described in the specification. It should be appreciated that in the development of any such actual implementation, as in any engineering or design project, numerous implementation-specific decisions must be made to achieve the developers' specific goals, such as compliance with system-related and business-related constraints, which may vary from one implementation to another. Moreover, it should be appreciated that such a development effort might be complex and time consuming, but would nevertheless be a routine undertaking of design, fabrication, and manufacture for those of ordinary skill having the benefit of this disclosure.
Present embodiments relate to non-invasively measuring physiological parameters corresponding to blood flow in a patient. Specifically, light may be emitted into a patient and photoelectrically detected after having propagated through (e.g., transmitted through, scattered by, and/or reflected by) pulsatile tissue of a patient. The propagation of light through pulsatile tissue may by affected by the composition of the tissue, which may vary as blood enters and exits the pulsatile tissue. Rather than emitting a light signal modulated at a rate that is effectively DC through the pulsatile patient tissue, present embodiments involve emitting a light modulated at frequencies sufficient to produce waves of photons known as photon density waves. A photon density wave may refer to light that is modulated at frequencies of approximately 50 MHz-3 GHz. Photon density waves may be resolvable in pulsatile tissue because the photon density waves may have a wavelength that is shorter than a mean absorption distance in pulsatile tissue.
A photon density wave (“PDW”) signal that has propagated through the pulsatile tissue of the patient may be detected and analyzed to obtain absorption and/or scattering properties of the pulsatile patient tissue. Certain changes between the PDW signal emitted into the tissue (i.e., the input signal) and the PDW signal detected after propagating through the tissue (i.e., an output signal) may be indicative of tissue conditions. In particular, a change in amplitude between the output signal and the input signal may correspond to absorptive components in the pulsatile tissue. A change in phase between the output signal and the input signal may correspond to scattering components in the pulsatile tissue.
Changes in amplitude of the PDW signals may correspond to the amount of absorptive components in the pulsatile patient tissue, as certain components of the tissue may absorb different wavelengths of light, such as red or infrared light, in different amounts. By analyzing decreases in amplitudes between the output signal and the input signal, a ratio of different types of particles in the pulsatile patient tissue, such as oxygenated and deoxygenated hemoglobin, may be estimated.
Changes in phase of the PDW signals may correspond to the total number of scattering particles in the area of measurement of the patient tissue. More specifically, the phase change between the output signal and the input signal may correspond to the total number of particles (e.g., total hemoglobin) which scatter the PDW signal, and not merely a ratio of particles (e.g., oxygenated and total hemoglobin). Further, variations in the phase change may also be measured to provide information associated with variations of total particles in the patient tissue. With measurements of absorption and scattering by components of the patient tissue, physiological parameters such as SpO2, regional oxygen saturation, total hemoglobin, perfusion, and many others may be monitored.
Thus, PDW signals may be used in the present embodiments to provide physiological information based on the amplitude and phase change of the detected output signal. It is now recognized that using multiple PDW signals having different wavelengths may provide even more physiological information, as patient tissue may have different components of interest (e.g., various types of cells or structures), which may each have different absorption and scattering coefficients. To emit multiple wavelengths of PDW signals to the patient tissue, multiple optical fibers may be used to transmit the generated PDW signals from the monitor to the sensor and into the patient tissue. Likewise, multiple detectors may be used to detect the PDW signals that have propagated through the patient tissue. However, such a configuration may increase system complexity and cost.
In accordance with the present techniques, multiple PDW signals of various wavelengths of light may be time-division multiplexed using an optical switch, such that one wavelength of light is transmitted through a single emission optical cable at any one instant. Thus, the single emission optical cable may transmit to a sensor a multi-wavelength PDW signal which includes multiple single-wavelength PDW signal components transmitted in series over time. Such a multi-wavelength PDW signal (i.e., the input signal), emitted from the sensor into pulsatile patient tissue, may be received by a detector in the sensor after propagating (e.g., reflecting, scattering, and/or passing) through the tissue. Thereafter, a single optical cable may carry the received signal (i.e., the output signal) to the patient monitor. Since the multi-wavelength PDW input signal is time-division multiplexed, only one wavelength of the output signal is received at one time. Thus, a single detector may photoelectrically detect and digitize the output signal. The detected and digitized output signal may be demultiplexed into its component single-wavelength PDW signals and processed to determine various physiological parameters based on comparisons with the multi-wavelength PDW input signal.
With the foregoing in mind,
The driving circuit 28 may modulate light emitted from the light sources 30 at a modulation frequency between approximately 50 MHz to 3 GHz, which may produce resolvable photon density waves in pulsatile tissue. In some embodiments, the driving circuit 28 may sweep the modulation frequency of one or more of the light sources in a range from 50 MHz to 2.4 GHz. Some embodiments of the patient monitor 12 may be configured to modulate light between 100 MHz and 1 GHz or to sweep a range from 100 MHz to 1 GHz. The driving circuit 28 may, in certain embodiments, modulate the light sources primarily at a frequency of approximately 500 MHz. Examples of PDW signals that may be generated by the driving circuit 28 of the patient monitor 12 may be illustrated below with reference to
An optical switch 36 may switch between the two optical cables 32 and 34, selecting one of the two modulated single-wavelength PDW signals, such that a multi-wavelength PDW signal is produced with multiple single-wavelength PDW signal portions in series. The switching of the optical switch 36 may time-division multiplex the single-wavelength PDW signals from the optical cables 32 and 34 to form the multi-wavelength PDW signal. Each of the single-wavelength PDW signals is alternatingly the sole wavelength active in the multi-wavelength PDW signal for brief periods of time (e.g., on the order of several ms). In other words, the multi-wavelength PDW signal includes several time-multiplexed components of single-wavelength PDW signals. Generally, periods of time that each single wavelength PDW signal is active may be brief enough to enable each of the single-wavelength PDW signals to pass through the pulsatile tissue with substantially no perceptible change in the pulsatile tissue of the patient occurring between the start of the first single-wavelength PDW signal and the end of the last single-wavelength PDW signal in the multi-wavelength PDW signal. Furthermore, the periods may be brief enough such that a pulse through the pulsatile tissue may be adequately sampled by each of the single-wavelength PDW signals. An example of a multi-wavelength PDW signal composed of time-multiplexed single-wavelength PDW signals is illustrated below with reference to
The optical switch 36 may be any circuit element capable of selecting one single-wavelength PDW signal generated by the driving circuit 28 at one time. In some embodiments, the optical switch 36 may switch between the two optical cables 32 and 34 mechanically. For example, the optical switch 36 may alternate between providing an optical route for each of the two optical cables 32 and 34 to the emitter output 22. Further, the optical switch 36 may be capable of steering light by switching or altering the wavelengths of a signal provided by either of the two optical cables 32 and 34. In some embodiments, the optical switch 36 may enable the constant operation of multiple light sources 30 in the driving circuit 28, which may decrease the complexity of the driving circuit 28 and improve the stability of the light sources 30 while still producing a multi-wavelength PDW signal.
The multi-wavelength PDW signal resulting from the switching of the optical switch 36 may be transmitted through a single optical cable 38 to be emitted into the patient tissue 26 via the emitter output 22 of the sensor 14. An input signal 23 (i.e., multi-wavelength PDW signal emitted by the emitter output 22 into the pulsatile patient tissue 26) may then propagate through the pulsatile tissue 26. The detector input 24 may receive a resulting output signal 25 (i.e., portions of the input signal 23 that have propagated through the patient tissue 26) and transmit the output signal 25 to the patient monitor 12 over an optical cable 40. In one or more embodiments, the optical cable 40 may be a second of only two optical cables of the sensor cable 16.
Because the multi-wavelength PDW signal represents a time-division multiplexed combination of the several single-wavelength PDW signals, only one of the single-wavelength PDW signals generally may pass through the patient tissue 26 at any given time. As such, the output signal 25 may generally be photoelectrically detected in a single photodetector 42, which may receive and convert the optical output signal 25 to an electrical signal referred to as a digitized output signal 27.
The digitized output signal 27 from the detector 42 may enter phase detection circuitry 44, and the output of the phase detection circuitry 44 may be entered into a processor, such as a digital signal processor (DSP) 46, to be analyzed for phase and amplitude changes. The driving circuit 28 may provide the phase detection circuitry 44 and the DSP 46 with information regarding the input signal 23 generated by the driving circuit 28. The information may include reference signals and time-division information relating to the input signal 23. The reference signals may be digital representations of the input signal 23, and may enable the phase detection circuitry 44 and the DSP 46 to analyze amplitude and phase changes between the output signal 25 and corresponding portions of the input signal 23. The time-division information may indicate which single-wavelength PDW signal is currently being received and may enable the phase detection circuitry 44 and the DSP 46 to distinguish between the multiple single-wavelength PDW signals of the multi-wavelength PDW signal. Thus, the DSP 46 may use the time-division information to demultiplex the multi-wavelength PDW signal into its component single-wavelength PDW signals.
By analyzing changes in amplitude and phase between the output signal 25 and the input signal 23, absorption and scattering properties of the patient tissue 26 for that wavelength of light may be determined. To determine amplitude and phase changes corresponding to absorption and scattering in the patient tissue 26, the phase detection circuitry 44 may obtain the output signal 25 (which may be digitized by the detector 42), time-division information, clock signals, and/or reference signals relating to the corresponding original input signal 23. By comparing amplitude changes between the digitized output signal 25 and the input signal 23 (or a digital reference signal corresponding to the input signal 23), absorption properties of the patient tissue 26 for each wavelength of light may be determined. Further, the phase detection circuitry 44 may detect phase changes between the output signal 25 and the input signal 23 to determine scattering properties in the patient tissue 26. In certain embodiments, the phase detection circuitry 44 and the driving circuit 28 may be individual components of a single semiconductor device, such as a DVD R/W driver circuit.
The DSP 46 may receive the output from the phase detection circuitry 44 and time-division information and/or reference signal information from the driver circuit 28. Using the absorption and scattering information associated with the amplitude changes and phase changes between the input signal 23 and the output signal 25, the DSP 46 may determine a variety of properties based on algorithms stored in memory on the DSP 46 or received from external sources, such as a microprocessor 48 or other devices via a bus 49. One example of such an algorithm may be described below with reference to
In general, the DSP 46 may ascertain certain properties of the patient tissue 26 based on the relationships described below. For a modulation frequency where the product of the frequency and the mean time between absorption events is much larger than 1, the change in phase Δφ between two points located a distance r from each other on a tissue bed may be given by the following relation:
where c is the speed of light, ω is the angular frequency of modulation, and μs′ is the reduced scattering coefficient. The reduced scattering coefficient for a tissue bed accounts for both blood and surrounding tissue components. This can be written as:
μs
The time varying component of equation (1) at a single wavelength will generally be only the portion due to arterial blood. The time varying component of equation (1) at a second wavelength will allow for the deconvolution of the scattering coefficient. The scattering coefficient for blood is related to the hematocrit (HCT) through the following relation:
μs
where g is the anisotropy factor, σ is the scattering cross section of an erythrocyte, Vi is the volume of an erythrocyte and HCT is the hematocrit.
As indicated above, the phase of the PDW signals may be sensitive to changes in the scattering coefficient, while the amplitude of the photon density waves may be sensitive to the concentration of absorbers in the medium. Specifically, with regard to amplitude measurements, the AC amplitude and DC amplitude may yield information about absorption in the volume. Thus, detection of amplitude changes in the photon density waves may be utilized to calculate absorber concentration values in the observed medium, such as blood oxygen saturation values. Such calculations may be made using a standard ratio of ratios (e.g., ratrat) technique for the constant and modulated values of the photon density wave amplitudes at two wavelengths. Once the ratio of ratios values is obtained, it may be mapped to the saturation from clinical calibration curves. In general, the amplitude of the resulting photon density waves after passing through the patient tissue 26 may be described as follows:
where A0 is the initial amplitude, D is the diffusion coefficient given as
is the absorption coefficient, and rsd is the distance between the emitter and the detector.
With regard to phase shift measurements, when the wavelength of the photon density waves is less than a mean absorption distance of the pulsatile tissue 26, the phase becomes almost exclusively a function of the scattering coefficient. While dependent upon the tissue bed being probed, this is generally believed to occur at a modulation frequency in the range of approximately 500 MHz. Thus, the phase shift measurement may yield information about the number of erythrocytes or red blood cells in the local probed volume. The HCT discussed above is proportional to the number of erythrocytes. Accordingly, by sweeping frequencies, a multi-parameter output may be obtained that relates to standard pulse oximetry measurements as well as the puddle hematocrit. In general, the change in phase of the resulting photon density waves after passing through the patient tissue 26 may be described as follows:
where Φ0 is a constant.
The amplitude and phase at a given frequency may be proportional to the scattering and absorption coefficient at a given wavelength until the product of the frequency and the mean time between absorption events is much larger than 1. When the product of the frequency and the mean time between absorption events is much larger than 1, the amplitude is a function of the absorption and phase is only a function of the scattering. Thus, in some embodiments, the driving circuit 28 may perform a frequency sweep over time (e.g., from 100 MHz to 1 GHz) to reduce the error in the determination of a single value of reduced scattering coefficient for the blood and a single value of absorption coefficient.
In some embodiments, by modulating the light sources at a sufficient frequency, and, thus, facilitating a detectable phase shift that corresponds to scattering particles, present embodiments may provide an extra degree of certainty for blood flow parameter measurements. Indeed, the detected amplitude for the photon density waves may be utilized to calculate traditional pulse oximetry information and the phase may be utilized to confirm that such values are correct (e.g., within a certain range of error). For example, the amplitude information may be utilized to calculate a blood oxygen saturation (SpO2) value and empirical data may indicate that a particular SpO2 value should correspond to a particular phase variation at a given frequency. In other words, there may be a certain phase change that should accompany a given increase in absorber that may be observed as a change in amplitude. Various known techniques (e.g., learning based algorithms such as support vector machines, cluster analysis, neural networks, and PCA) based on the measured phase shift and amplitude change may be compared to determine if the amplitude shift and phase shift correlate to a known SpO2. If both the measured amplitude shift and phase shift correlate to a known SpO2, the measured SpO2 value may be deemed appropriate and displayed or utilized as a correct SpO2 value. Alternatively, if the measured amplitude shift and phase shift do not agree, the calculated SpO2 value may be identified as being corrupt or including too much noise and, thus, may be discarded.
As shown in
Other components of the patient monitor 12 may include random access memory (RAM) 56, a display interface 58, and control inputs 60. The RAM 56 may provide temporary storage of variables and other data employed while carrying out certain techniques described herein. The display interface 58 may allow physiological parameters obtained by the patient monitor 12 to appear on the display 20. The control inputs 60 may enable a physician or other medical practitioner to vary the operation of the patient monitor 12. By way of example, a practitioner may select whether the patient is an adult or neonate, and/or whether the patient tissue 26 is high perfusion or low perfusion tissue. Such a selection with the control inputs 60 may vary the modulation frequency of one or more of the single-wavelength PDW signals, may disable one or more of the single-wavelength PDW signals, or may cause a preprogrammed sequence of operation, such as a sweep of modulation frequencies for one or more of the single-wavelength PDW signals, to begin.
As noted above, the driving circuit 28 may emit several single-wavelength PDW signals that may be selected by the optical switch 36 to generate one multi-wavelength PDW signal which is sent to the sensor 14.
The first PDW signal 68 may be active at regular intervals for a given period of time (e.g., approximately several milliseconds) in the time-multiplexed multi-wavelength PDW signal. An active interval 70 of the first PDW signal 68 may correspond with a time period during which the optical switch 36 selects a first single-wavelength PDW signal (e.g., via a first optical cable 32) from one of the light sources 30 in the driving circuit 28, such that the first PDW signal 68 is transmitted to the emitter output 22 in the sensor 14 to be emitted into the patient tissue 26. An inactive interval 72 of the first single-wavelength PDW signal 68 may correspond with a time period where the optical switch 36 does not select the first single-wavelength PDW signal, and instead selects a single-wavelength PDW signal modulated from another one of the light sources 30 (e.g., via a second optical cable 34).
As noted below with reference to
The first and second PDW signals 68 and 76 emitted by the driving circuitry 28 may be selected by the optical switch 36 and combined as a single multi-wavelength PDW signal transmitted through a single emitting optical cable 38 to the sensor 14.
When the multi-wavelength PDW signal of the plot 82 has passed through the pulsatile patient tissue 26, single-wavelength components of the output signal (i.e., portions of the signals 68 and 76 which have propagated through the patient tissue 26) may be isolated (i.e., demultiplexed) in the phase detection circuitry 44 and the DSP 46 using time-division information from the driving circuit 28. Comparing one of the de-multiplexed output signals with the corresponding first or second PDW signals 68 or 76 of the plot 82 may indicate various properties of the patient tissue 26.
For example,
Since another single-wavelength PDW signal, such as the second PDW signal 76, may occur very shortly thereafter, performing a similar comparison with the following single-wavelength PDW signal may yield additional measurements for absorption and scattering properties of the patient tissue 26 for the second wavelength, at substantially the same time. Thus, the patient monitor 12 may determine at least four measurements associated with properties of the patient tissue 26 for substantially the same time for medical purposes associated with pulse oximetry, including two absorption and two scattering properties. In other words, because substantially no perceptible change in the pulsatile tissue of the patient may occur between the start of the first PDW signal 68 and the start of the second PDW signal 76, for purposes of pulse oximetry, the four measurements may be understood to occur at substantially the same time. Furthermore, the emissions of the first PDW signal 68 and the second PDW signal 76 may be sufficiently frequent to adequately sample pulse from the patient tissue 26 using, for example, the patient monitor 12 (from
In step 104, the optical switch 36 may select the first PDW signal 98 or the second PDW signal 102 for transmission via the single optical cable 38 to be emitted into the patient tissue 26. The selected single-wavelength PDW signal, referred to as the input signal 106, may pass through the patient tissue 26 in step 108 (e.g., emitted from the emitter output 22 of the sensor 14). Once the input signal 106 has propagated through the patient tissue 26, portions of the input signal 106 (including light that has been scattered by, reflected by, or transmitted through the tissue) may be received at a detector input 24 of the sensor 14 and passed through a receiving optical cable 40 to the detector 42, as represented by step 110. In step 114, such portions of the detected signal, also referred to as the output signal 112, may be used by the DSP 46 and/or the microprocessor 48 to determine properties of the patient tissue 26 based on phase and amplitude changes between the output signal 112 and the input signal 106 which correspond to scattering and absorption properties in the tissue.
Portions of the process 94, including steps 104, 108, 110, and 114, may repeat indefinitely to generate and emit a multi-wavelength PDW signal into the patient tissue 26 tissue. More specifically, in each iteration of steps 104, 108, 110, and 114, the selected input signal 106 may represent a single-wavelength PDW signal of a multi-wavelength PDW signal, and by alternately selecting a different input signal 106 (e.g., alternating between the first signal 98 and the second signal 102), a multi-wavelength PDW signal may be emitted and detected. In some embodiments, the repetition may be between steps 104, 108, and 110, and the determination and/or analyses of phase and amplitude changes may occur after multiple repetitions of steps 104, 108, and 110, and after a certain length of a multi-wavelength PDW signal has been emitted and detected from the patient tissue 26. Furthermore, the line 115 drawn from the first and second signals 98 and 102 to step 114 may represent that information, such as time-division information, clock signals, and/or reference signals relating to the corresponding original emitted single-wavelength PDW signals 98 and 102 may be used in step 114.
In step 120, the DSP 46 may determine an absorption property of the patient tissue 26 for the moment in time at which the single-wavelength component of the multi-wavelength PDW signal has passed through the pulsatile tissue 26. Generally, the absorption property may be represented by an absorption coefficient, and may be determined based on the amplitude change ΔDC1 and/or ΔAC1 values obtained in step 116 by using Equations (1) and (4).
While the embodiments set forth in the present disclosure may be susceptible to various modifications and alternative forms, specific embodiments have been shown by way of example in the drawings and have been described in detail herein. However, it should be understood that the disclosure is not intended to be limited to the particular forms disclosed. The disclosure is to cover all modifications, equivalents, and alternatives falling within the spirit and scope of the disclosure as defined by the following appended claims.
Number | Name | Date | Kind |
---|---|---|---|
3638640 | Shaw | Feb 1972 | A |
4223680 | Jobsis | Sep 1980 | A |
4936679 | Mersch | Jun 1990 | A |
4971062 | Hasebe et al. | Nov 1990 | A |
4974591 | Awazu et al. | Dec 1990 | A |
5028787 | Rosenthal et al. | Jul 1991 | A |
5065749 | Hasebe et al. | Nov 1991 | A |
5084327 | Stengel | Jan 1992 | A |
5088493 | Giannini et al. | Feb 1992 | A |
5119815 | Chance | Jun 1992 | A |
5253646 | Delpy et al. | Oct 1993 | A |
5275159 | Griebel | Jan 1994 | A |
5353799 | Chance | Oct 1994 | A |
5416582 | Knutson et al. | May 1995 | A |
5424843 | Tromberg et al. | Jun 1995 | A |
5441054 | Tsuchiya | Aug 1995 | A |
5477051 | Tsuchiya | Dec 1995 | A |
5483646 | Uchikoga | Jan 1996 | A |
5492118 | Gratton et al. | Feb 1996 | A |
5497769 | Gratton et al. | Mar 1996 | A |
5730124 | Yamauchi | Mar 1998 | A |
5772587 | Gratton et al. | Jun 1998 | A |
5779631 | Chance | Jul 1998 | A |
5800348 | Kaestle | Sep 1998 | A |
5813988 | Alfano et al. | Sep 1998 | A |
5818583 | Sevick-Muraca et al. | Oct 1998 | A |
5830139 | Abreu | Nov 1998 | A |
5831598 | Kauffert et al. | Nov 1998 | A |
5859713 | Khoury et al. | Jan 1999 | A |
5871442 | Madarasz et al. | Feb 1999 | A |
5873821 | Chance et al. | Feb 1999 | A |
6009340 | Hsia | Dec 1999 | A |
6064917 | Matson | May 2000 | A |
6078833 | Hueber | Jun 2000 | A |
6081742 | Amano et al. | Jun 2000 | A |
6120460 | Abreu | Sep 2000 | A |
6134460 | Chance | Oct 2000 | A |
6192260 | Chance | Feb 2001 | B1 |
6192261 | Gratton et al. | Feb 2001 | B1 |
6246892 | Chance | Jun 2001 | B1 |
6272367 | Chance | Aug 2001 | B1 |
6285895 | Ristolainen et al. | Sep 2001 | B1 |
6309352 | Oraevsky et al. | Oct 2001 | B1 |
6312393 | Abreu | Nov 2001 | B1 |
6335792 | Tsuchiya | Jan 2002 | B1 |
6353750 | Kimura et al. | Mar 2002 | B1 |
6415236 | Kobayashi et al. | Jul 2002 | B2 |
6419671 | Lemberg | Jul 2002 | B1 |
6453183 | Walker | Sep 2002 | B1 |
6456862 | Benni | Sep 2002 | B2 |
6461305 | Schnall | Oct 2002 | B1 |
6487439 | Skladnev et al. | Nov 2002 | B1 |
6493565 | Chance et al. | Dec 2002 | B1 |
6542772 | Chance | Apr 2003 | B1 |
6544193 | Abreu | Apr 2003 | B2 |
6549284 | Boas et al. | Apr 2003 | B1 |
6549795 | Chance | Apr 2003 | B1 |
6591122 | Schmitt | Jul 2003 | B2 |
6594513 | Jobsis et al. | Jul 2003 | B1 |
6606509 | Schmitt | Aug 2003 | B2 |
6618042 | Powell | Sep 2003 | B1 |
6618614 | Chance | Sep 2003 | B1 |
6622095 | Kobayashi et al. | Sep 2003 | B2 |
6662030 | Khalil et al. | Dec 2003 | B2 |
6671528 | Steuer et al. | Dec 2003 | B2 |
6675029 | Monfre et al. | Jan 2004 | B2 |
6687519 | Steuer et al. | Feb 2004 | B2 |
6690958 | Walker et al. | Feb 2004 | B1 |
6704110 | Tsuchiya | Mar 2004 | B2 |
6711426 | Benaron et al. | Mar 2004 | B2 |
6714245 | Ono | Mar 2004 | B1 |
6731274 | Powell | May 2004 | B2 |
6785568 | Chance | Aug 2004 | B2 |
6793654 | Lemberg | Sep 2004 | B2 |
6802812 | Walker et al. | Oct 2004 | B1 |
6850053 | Daalmans et al. | Feb 2005 | B2 |
6859658 | Krug | Feb 2005 | B1 |
6873865 | Steuer et al. | Mar 2005 | B2 |
6882874 | Huiku | Apr 2005 | B2 |
6898451 | Wuori | May 2005 | B2 |
6944322 | Johnson et al. | Sep 2005 | B2 |
6947781 | Asada et al. | Sep 2005 | B2 |
6949081 | Chance | Sep 2005 | B1 |
6957094 | Chance et al. | Oct 2005 | B2 |
7006676 | Zeylikovich et al. | Feb 2006 | B1 |
7006856 | Baker et al. | Feb 2006 | B2 |
7010341 | Chance | Mar 2006 | B2 |
7035697 | Brown | Apr 2006 | B1 |
7041063 | Abreu | May 2006 | B2 |
7043289 | Fine et al. | May 2006 | B2 |
7065392 | Kato | Jun 2006 | B2 |
7072701 | Chen et al. | Jul 2006 | B2 |
7095491 | Forstner et al. | Aug 2006 | B2 |
7139603 | Chance | Nov 2006 | B2 |
7164938 | Geddes et al. | Jan 2007 | B2 |
7184148 | Alphonse | Feb 2007 | B2 |
7187441 | Sevick-Muraca et al. | Mar 2007 | B1 |
7197355 | Nelson | Mar 2007 | B2 |
7236811 | Schmitt | Jun 2007 | B2 |
7239902 | Schmitt et al. | Jul 2007 | B2 |
7251518 | Herrmann | Jul 2007 | B2 |
7268873 | Sevick-Muraca et al. | Sep 2007 | B2 |
7272426 | Schmid | Sep 2007 | B2 |
7277741 | Debreczeny et al. | Oct 2007 | B2 |
7283242 | Thornton | Oct 2007 | B2 |
7327463 | Alphonse | Feb 2008 | B2 |
7330746 | Demuth et al. | Feb 2008 | B2 |
7355688 | Lash et al. | Apr 2008 | B2 |
7469158 | Cutler et al. | Dec 2008 | B2 |
7483731 | Hoarau et al. | Jan 2009 | B2 |
7500953 | Oraevsky et al. | Mar 2009 | B2 |
7525647 | Lash et al. | Apr 2009 | B2 |
7538865 | Lash et al. | May 2009 | B2 |
7551950 | Cheng | Jun 2009 | B2 |
7621877 | Schnall | Nov 2009 | B2 |
7623285 | Gross | Nov 2009 | B2 |
7689259 | Mannheimer et al. | Mar 2010 | B2 |
7753902 | Mansour et al. | Jul 2010 | B1 |
20020042558 | Mendelson | Apr 2002 | A1 |
20020156354 | Larson | Oct 2002 | A1 |
20020198443 | Ting | Dec 2002 | A1 |
20030023140 | Chance | Jan 2003 | A1 |
20050059870 | Aceti | Mar 2005 | A1 |
20050113651 | Wood et al. | May 2005 | A1 |
20050113656 | Chance | May 2005 | A1 |
20050192488 | Bryenton et al. | Sep 2005 | A1 |
20050228248 | Dietiker | Oct 2005 | A1 |
20050250998 | Huiku | Nov 2005 | A1 |
20060020181 | Schmitt | Jan 2006 | A1 |
20060122475 | Balberg et al. | Jun 2006 | A1 |
20060135860 | Baker et al. | Jun 2006 | A1 |
20060189861 | Chen et al. | Aug 2006 | A1 |
20060247501 | Ali | Nov 2006 | A1 |
20060247506 | Balberg et al. | Nov 2006 | A1 |
20070093702 | Yu et al. | Apr 2007 | A1 |
20070129613 | Rochester et al. | Jun 2007 | A1 |
20080139908 | Kurth | Jun 2008 | A1 |
20080312533 | Balberg et al. | Dec 2008 | A1 |
20100016732 | Wells et al. | Jan 2010 | A1 |
20110118574 | Chang et al. | May 2011 | A1 |
Number | Date | Country |
---|---|---|
497021 | May 1992 | EP |
0580414 | Jan 1994 | EP |
832599 | Jan 1998 | EP |
0945100 | Sep 1999 | EP |
WO9313706 | Jul 1993 | WO |
WO9727801 | Aug 1997 | WO |
0025112 | May 2000 | WO |
WO0140776 | Jun 2001 | WO |
WO03077750 | Sep 2003 | WO |
WO2004010844 | Feb 2004 | WO |
WO2005025399 | Mar 2005 | WO |
WO2005064314 | Jul 2005 | WO |
WO2006097910 | Sep 2006 | WO |
WO2006124455 | Nov 2006 | WO |
WO2006124696 | Nov 2006 | WO |
WO2007048039 | Apr 2007 | WO |
2010039418 | Apr 2010 | WO |
2011034699 | Mar 2011 | WO |
2011034700 | Mar 2011 | WO |
2011041071 | Apr 2011 | WO |
Entry |
---|
Ntziachristos, et al.; “Oximetry based on diffuse photon density wave differentials;” Medical Physics, AIP, vol. 27, No. 2, Feb. 1, 2000; pp. 410-421. |
Ulas, et al.; “Noninvasive diffuse optical measurement of blood flow and blood oxygenation for monitoring radiation therapy in patients with head and neck tumors: a pilot study;” Journal of Biomedical Optics, vol. 11, No. 6; Jan. 1, 2006, p. 064021. |
International Search Report and Written Opinion for PCT Application No. PCT/US2011/028437 dated Jul. 14, 2011, 15 pgs. |
Addison, Paul S., et al.; “A novel time-frequency-based 3D Lissajous figure method and its application to the determination of oxygen saturation from the photoplethysmogram,” Institute of Physic Publishing, Meas. Sci. Technol., vol. 15, pp. L15-L18 (2004). |
Aoyagi, T., et al.; “Analysis of Motion Artifacts in Pulse Oximetry,” Japanese Society ME, vol. 42, p. 20 (1993) (Article in Japanese—contains English summary of article). |
Barreto, Armando B., et al.; “Adaptive LMS Delay Measurement in dual Blood Volume Pulse Signals for Non-Invasive Monitoring,” IEEE, pp. 117-120 (1997). |
Belal, Suliman Yousef, et al.; “A fuzzy system for detecting distorted plethysmogram pulses in neonates and paediatric patients,” Physiol. Meas., vol. 22, pp. 397-412 (2001). |
Chan, K.W., et al.; “17.3: Adaptive Reduction of Motion Artifact from Photoplethysmographic Recordings using a Variable Step-Size LMS Filter,” IEEE, pp. 1343-1346 (2002). |
Coetzee, Frans M.; “Noise-Resistant Pulse Oximetry Using a Synthetic Reference Signal,” IEEE Transactions on Biomedical Engineering, vol. 47, No. 8, Aug. 2000, pp. 1018-1026. |
Cyrill, D., et al.; “Adaptive Comb Filter for Quasi-Periodic Physiologic Signals,” Proceedings of the 25th Annual International Conference of the IEEE EMBS, Cancun, Mexico, Sep. 17-21, 2003; pp. 2439-2442. |
Cysewska-Sobusaik, Anna; “Metrological Problems With noninvasive Transillumination of Living Tissues,” Proceedings of SPIE, vol. 4515, pp. 15-24 (2001). |
East, Christine E., et al.; “Fetal Oxygen Saturation and Uterine Contractions During Labor,” American Journal of Perinatology, vol. 15, No. 6, pp. 345-349 (Jun. 1998). |
Edrich, Thomas, et al.; “Can the Blood Content of the Tissues be Determined Optically During Pulse Oximetry Without Knowledge of the Oxygen Saturation?—An In-Vitro Investigation,” Proceedings of the 20th Annual International conference of the IEEE Engie. |
Goldman, Julian M.; “Masimo Signal Extraction Pulse Oximetry,” Journal of Clinical Monitoring and Computing, vol. 16, pp. 475-483 (2000). |
Hamilton, Patrick S., et al.; “Effect of Adaptive Motion-Artifact Reduction on QRS Detection,” Biomedical Instrumentation & Technology, pp. 197-202 (undated). |
Huang, J., et al.; “Low Power Motion Tolerant Pulse Oximetry,” Abstracts, A7, p. S103. (undated). |
Johansson, A.; “Neural network for photoplethysmographic respiratory rate monitoring,” Medical & Biological Engineering & Computing, vol. 41, pp. 242-248 (2003). |
Kaestle, S.; “Determining Artefact Sensitivity of New Pulse Oximeters in Laboratory Using Signals Obtained from Patient,” Biomedizinische Technik, vol. 45 (2000). |
Kim, J.M., et al.; “Signal Processing Using Fourier & Wavelet Transform,” pp. II-310-II-311 (undated). |
Leahy, Martin J., et al.; “Sensor Validation in Biomedical Applications,” IFAC Modelling and Control in Biomedical Systems, Warwick, UK; pp. 221-226 (1997). |
Lee, C.M., et al.; “Reduction of motion artifacts from photoplethysmographic recordings using wavelet denoising approach,” IEEE EMBS Asian-Pacific Conference on Biomedical Engineering, Oct. 20-22, 2003; pp. 194-195. |
Lopez-Silva, S.M., et al.; “Transmittance Photoplethysmography and Pulse Oximetry With Near Infrared Laser Diodes,” IMTC 2004—Instrumentation and Measurement Technology Conference, Como, Italy, May 18-20, 2004; pp. 718-723. |
Lopez-Silva, Sonnia Maria Lopez, et al.; “Near-infrared transmittance pulse oximetry with laser diodes,” Journal of Biomedical Optics, vol. 8, No. 3, pp. 525-533 (Jul. 2003). |
Lutter, N., et al.; “Comparison of Different Evaluation Methods for a Multi-wavelength Pulse Oximeter,” Biomedizinische Technik, vol. 43, (1998). |
Maletras, Francois-Xavier, et al.; “Construction and calibration of a new design of Fiber Optic Respiratory Plethysmograph (FORP),” Optomechanical Design and Engineering, Proceedings of SPIE, vol. 4444, pp. 285-293 (2001). |
Neumann, et al.; “Fourier Artifact suppression Technology Provides Reliable SpO2,,” Abstracts, A11, p. S105. (undated). |
Odagiri, Y.; “Pulse Wave Measuring Device,” Micromechatronics, vol. 42, No. 3, pp. 6-11 (undated) (Article in Japanese—contains English summary of article). |
Relente, A.R., et al.; “Characterization and Adaptive Filtering of Motion Artifacts in Pulse Oximetry using Accelerometers,” Proceedings of the Second joint EMBS/BMES Conference, Houston, Texas, Oct. 23-26, 2002; pp. 1769-1770. |
Rhee, Sokwoo, et al.; “Design of a Artifact-Free Wearable Plethysmographic Sensor,” Proceedings of the First joint BMES/EMBS Conference, Oct. 13-16, 1999, Altanta, Georgia, p. 786. |
Stetson, Paul F.; “Determining Heart Rate from Noisey Pulse Oximeter Signals Using Fuzzy Logic,” The IEEE International Conference on Fuzzy Systems, St. Louis, Missouri, May 25-28, 2003; pp. 1053-1058. |
Such, Hans Olaf; “Optoelectronic Non-invasive Vascular Diagnostics Using multiple Wavelength and Imaging Approach,” Dissertation, (1998). |
Todd, Bryan, et al.; “The Identification of Peaks in Physiological Signals,” Computers and Biomedical Research, vol. 32, pp. 322-335 (1999). |
Yang, Boo-Ho, et al.; “A Twenty-Four Hour Tele-Nursing System Using a Ring Sensor,” Proceedings of the 1998 IEEE International Conference on Robotics & Automation, Leaven, Belgium, May 1998; pp. 387-392. |
Yao, Jianchu, et al.; “A Novel Algorithm to Separate Motion Artifacts from Photoplethysmographic Signals Obtained With a Reflectance Pulse Oximeter,” Proceedings of the 26th Annual International conference of the IEEE EMBS, San Francisco, California, Sept. |
Yao, Jianchu, et al.; “Design of a Plug-and-Play Pulse Oximeter,” Proceedings of the Second Joint EMBS/BMES Conference, Houston, Texas, Oct. 23-26, 2002; pp. 1752-1753. |
Yoon, Gilwon, et al.; Multiple diagnosis based on Photo-plethysmography: hematocrit, SpO2, pulse and respiration, Optics in Health Care and Biomedical optics: Diagnostics and Treatment; Proceedings of the SPIE, vol. 4916; pp. 185-188 (2002). |
Number | Date | Country | |
---|---|---|---|
20110245636 A1 | Oct 2011 | US |