(12) United States Patent
`IsaacsOn
`
`(10) Patent No.:
`(45) Date of Patent:
`
`US 8,725.226 B2
`May 13, 2014
`
`USOO872.5226B2
`
`(54) OPTICAL SENSOR PATH SELECTION
`(75) Inventor: Philip O. Isaacson, Chanhassen, MN
`(US)
`(73) Assignee: Nonin Medical, Inc., Plymouth, MN
`(US)
`Subject to any disclaimer, the term of this
`y
`patent is extended or adjusted under 35
`U.S.C. 154(b) by 838 days.
`(21) Appl. No.: 12/618,120
`
`*) Notice:
`
`(22) Filed:
`
`Nov. 13, 2009
`
`(65)
`
`Prior Publication Data
`US 2010/O13O840 A1
`May 27, 2010
`
`JP
`JP
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`(Continued)
`OTHER PUBLICATIONS
`
`Related U.S. Application Data
`(60) Provisional application No. 61/114,528, filed on Nov.
`14, 2008.
`
`(2006.01)
`
`(51) Int. Cl.
`A6 IB5/00
`(52) U.S. Cl.
`USPC ........................................... 600/323; 600/357
`(58) Field of Classification Search
`USPC .......................................... 600/323,326,357
`See application file for complete search history.
`
`(56)
`
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`
`(Continued)
`Primary Examiner — Clayton E LaBalle
`Assistant Examiner — Warren K Fenwick
`(74) Attorney, Agent, or Firm — Schwegman, Lundberg &
`Woessner, P.A.
`
`ABSTRACT
`(57)
`A device includes a sensor for measuring a parameter for
`tissue. The sensor includes a plurality of optical elements
`including a plurality of detectors and at least one emitter.
`Separation distances between the various optical elements are
`selected based on a depth corresponding to a region of interest
`in the tissue and based on a depth corresponding to an exclu
`sion region in the tissue.
`10 Claims, 4 Drawing Sheets
`
`Petitioner Apple Inc. - Exhibit 1063, p. 1
`
`

`

`US 8,725.226 B2
`Page 2
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`“European Application No. 06795079.0, Office Action Mailed Sep.
`25, 2009, 5 pgs.
`“International Application Serial No. PCT/IB2006/001863, Interna
`tional Search Report and Written Opinion mailed Sep. 18, 2007”. 13
`pgS
`
`"International Application Serial No. PCTIB2006001863, Interna
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`Transportation in Tissue'. 4pgs.
`
`Petitioner Apple Inc. - Exhibit 1063, p. 2
`
`

`

`US 8,725.226 B2
`Page 3
`
`(56)
`
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`OTHER PUBLICATIONS
`
`Rais-Bahrami, K, et al., "Validation of a noninvasive neonatal optical
`cerebral oximeter in veno-venous ECMO patients with a cephalad
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`2009, 23 pgs.
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`
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`
`* cited by examiner
`
`Petitioner Apple Inc. - Exhibit 1063, p. 3
`
`

`

`U.S. Patent
`US. Patent
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`May 13, 2014
`May 13, 2014
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`Sheet 1 of 4
`Sheet 1 of4
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`US 8,725.226 B2
`US 8,725,226 132
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`Petitioner Apple Inc. - Exhibit 1063, p. 4
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`Petitioner Apple Inc. - Exhibit 1063, p. 4
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`

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`U.S. Patent
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`May 13, 2014
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`Sheet 2 of 4
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`US 8,725.226 B2
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`PROCESSOR
`-
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`
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`32 St -?-s
`V ><
`2. /
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`a/
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`Petitioner Apple Inc. - Exhibit 1063, p. 5
`
`

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`U.S. Patent
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`May 13, 2014
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`Sheet 3 of 4
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`US 8,725.226 B2
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`N
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`IDENTIFYING A REGION OF INTEREST
`
`35
`
`SELECTING A PATH DEPTH BASED ON
`THE REGION OF INTEREST
`
`ESTABLISHING A DIMENSION BETWEEN
`AN EMITTER AND A DETECTOR
`
`Petitioner Apple Inc. - Exhibit 1063, p. 6
`
`

`

`U.S. Patent
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`May 13, 2014
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`Sheet 4 of 4
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`US 8,725.226 B2
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`AW N
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`A5
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`A.
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`Af
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`A2)
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`A25
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`AR
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`A5
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`AA
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`IDENTIFYING A REGION OF INTEREST DISPOSED
`INA FIRST LAYER OF A BIOLOGICAL TISSUE
`
`IDENTIFYING AN EXCLUSION REGION DISPOSED
`IN A SECOND LAYER OF THE BIOLOGICAL TISSUE
`
`SELECTING A FIRST DEPTH CORRESPONDING TO
`THE REGION OF INTEREST
`
`SELECTING ASECOND DEPTH CORRESPONDING
`TO THE EXCLUSION REGION
`
`USING THE FIRST DEPTH TO DETERMINE A FIRST
`DIMENSION BETWEEN A FIRST EMITTER AND A
`SECOND DETECTOR AND BETWEEN A SECOND
`EMITTER AND A FIRST DETECTOR
`
`USING THE SECOND DEPTH TO DETERMINEA
`SECOND DIMENSION BETWEEN THE FIRST EMITTER
`AND THE FIRST DETECTOR AND BETWEEN THE
`SECOND EMITTER AND THE SECOND DETECTOR
`
`USING THE FIRST DIMENSION TO POSITION THE
`FIRST EMITTER RELATIVE TO THE SECOND DETECTOR
`AND TO POSITION THE SECOND EMITTER RELATIVE
`TO THE FIRST DETECTOR
`
`USING THE SECOND DIMENSION TO POSITION THE
`FIRST EMITTER RELATIVE TO THE FIRST DETECTOR
`AND TO POSITION THE SECOND EMITTER RELATIVE
`TO THE SECOND DETECTOR
`
`
`
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`
`
`Petitioner Apple Inc. - Exhibit 1063, p. 7
`
`

`

`1.
`OPTICAL SENSOR PATH SELECTION
`
`CLAIM OF PRIORITY
`
`This patent application claims the benefit of priority, under
`35 U.S.C. Section 119(e), to Isaacson, U.S. Provisional
`Patent Application Ser. No. 61/114,528, entitled “OPTICAL
`SENSOR PATH SELECTION, filed on Nov. 14, 2008, and is
`incorporated herein by reference.
`
`BACKGROUND
`
`The human brain requires a continuous Supply of oxygen.
`A measure of blood oxygenation can help to accurately diag
`nose a medical condition or monitor the health of a patient.
`Current technology for determining cerebral oXimetry is
`inadequate.
`
`10
`
`15
`
`SUMMARY
`
`The present Subject matter includes systems and methods
`as described herein. For example, a patient sensor includes a
`first emitter and a first detector separated by a first dimension
`and a second emitter and a second detector separated by a
`second dimension. The first dimension and the second dimen
`sion can be determined by a particular technique.
`In one example, the sensor is fully compensated and
`include two emitters and two detectors. In this example, a first
`emitter and a first detector are coupled by a short path that
`traverses a Surface layer of the tissue as well as an exclusion
`region within the tissue. The first emitter is also coupled to a
`second detector by a long path that traverses the surface layers
`of the tissue as well as a region of interestata particular depth
`within the tissue. A second emitter is coupled to the first
`detector by a long path that traverses the surface layers of the
`tissue as well as the region of interest within the tissue. The
`second emitter is also coupled to the second detector by a
`short path that traverses the surface layers of the tissue and
`passes through exclusion region of the tissue without
`encroaching on the region of interest.
`The mean depth of the light path is approximately one third
`of the distance between the emitter and the detector. Accord
`ing to one example, a method includes selecting a long path
`dimension and selecting a short path dimension for placement
`of detectors and emitters.
`Consider first, selecting a long path dimension for a sensor
`having two emitters and two detectors. The long path dimen
`sion refers to the lateral separation between an emitter and a
`detector in which the path through the biological tissue
`traverses the region of interest. The long path dimension is
`proportional to the average depth of the region of interest. In
`one example, the region of interest is the cerebral cortex and
`the long path dimension is approximately 40 mm.
`Next, consider selecting the short path dimension. The
`short path dimension also refers to the separation between an
`emitter and a detector. The short path dimension is selected to
`provide an optical path having a tissue depth that traverses a
`Surface layer and does not traverse the region of interest. As
`with the long path dimension, the short path dimension is
`proportional to the penetration depth in the tissue. The optical
`path corresponding to the short path dimension is selected to
`be approximately three times the thickness of the surface
`layer to be excluded (e.g., the dermis and epidermis) and just
`short of the depth of the region of interest. A typical scalp
`thickness is approximately at least 3 mm and a typical skull
`thickness is approximately at least 5 mm which means that the
`minimum depth to the brain is approximately 8 mm. Thus, for
`
`25
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`US 8,725,226 B2
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`2
`cerebral oximetry the short path dimension is selected to be
`less than three times 8 mm (24 mm). In one example, the short
`path dimension is 20 mm.
`More generally, the scalp depth is between approximately
`3 mm and 10 mm and the skull depth is between approxi
`mately 5 mm and 10 mm.
`For a neonate, typical dimensions are 3 mm for the scalp
`and 4 mm for the skull. As such, the long path dimension is at
`least approximately three times 7 mm (21 mm). In one
`example, the long path dimension is 25 mm. The short path
`dimension is at least three times the scalp thickness (9 mm)
`and less than 21 mm. In one example, the short path dimen
`sion is 12.5 mm.
`In one example, the long path dimension is twice that of the
`short path dimension. For example, an adult cerebral oxim
`etry sensor has a long path dimension and short path dimen
`sion of 25 mm and 12.5 mm, respectively and a neonate
`cerebral oximetry sensor has dimensions of 40 mm and 20
`mm, respectively. The 2:1 ratio between long dimension and
`short dimension provides good compensation and good sig
`nal; however, other ratios are also contemplated.
`This summary is intended to provide an overview of sub
`ject matter of the present patent application. It is not intended
`to provide an exclusive or exhaustive explanation of the
`invention. The detailed description is included to provide
`further information about the present subject matter.
`
`BRIEF DESCRIPTION OF THE DRAWINGS
`
`In the drawings, which are not necessarily drawn to scale,
`like numerals may describe similar components in different
`views. Like numerals having different letter suffixes may
`represent different instances of similar components. The
`drawings illustrate generally, by way of example, but not by
`way of limitation, various embodiments discussed in the
`present document.
`FIG. 1 includes a view of a sensor according to one
`example.
`FIG. 2 includes a system according to one example.
`FIG. 3 includes a method according to one example.
`FIG. 4 includes a method according to one example.
`
`DETAILED DESCRIPTION
`
`The present subject matter is directed to in vivo optical
`examination and monitoring of selected blood metabolites or
`constituents in human or other living Subjects. Examination
`and monitoring can include transmitting selected wave
`lengths of light into a particular area of biological tissue and
`receiving the resulting light as it emerges from the area, and
`analyzing the received light to determine the desired data
`based on light absorption.
`One example includes an optical sensor assembly that is
`particularly adapted for in Vivo use as the patient interface in
`a patient-monitoring apparatus Such as a cerebral or tissue
`Oximeter.
`One example can be used for non-invasive determination
`of tissue oxygenation or non-invasive cerebral oXimetry.
`Cerebral oximetry provides a measure of blood oxygen Satu
`ration in the brain. One example includes an optical sensor
`having light emitters and detectors that can be applied to the
`forehead of the patient.
`One example includes an apparatus for in vivo monitoring
`of blood metabolites Such as hemoglobin oxygen concentra
`tion in any of a plurality of different regions of a patient
`through application of an optical sensor assembly. The optical
`sensor assembly is in communication with, or is coupled to, a
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`Petitioner Apple Inc. - Exhibit 1063, p. 8
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`processor. The processor can be configured to control the
`sensor and analyze data from the sensor. One example of a
`processor includes a monitor which provides a visible display
`based on the analysis.
`The processor can be configured to operate the sensor. The
`sensor is configured to couple with tissue of the patient and
`emit and detect light energy. The sensor provides an output
`signal to the processor corresponding to the detected energy.
`One example includes an optical probe configured to con
`form to a shape of the cerebrum or other anatomical area.
`FIG. 1 illustrates view 100 including processor 30A, sensor
`34A (in partial sectional view), and biological tissue 50 (also
`in partial sectional view) according to one example.
`Processor 30A is in communication with, or is coupled to,
`sensor 34A by link32A. Processor 30A can include a digital
`processor, a central processor unit (CPU), a microprocessor,
`a computer, a digital signal processor, an application specific
`integrated circuit (ASIC), an analog processor, or a mixed
`signal processor. In addition, processor 30A can include a
`memory or other device for storing instructions or data. Pro
`cessor 30A can include other elements as well, including, for
`example, an analog-to-digital converter (ADC), a digital-to
`analog converter (DAC), a driver, an amplifier, a filter, or
`other circuitry to perform a method as described herein.
`Link 32A can include a wired or wireless channel. Link
`32A can conveyan corresponding to a detected signal.
`Sensor 34A includes housing 38 having a surface 36.
`Housing 38 can be rigid or flexible and is configured for
`coupling to biological tissue 50 at surface 36. In the example
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`shown, surface 36 is closely conformed to the contours of
`biological tissue 50. Sensor 34A can be affixed to biological
`tissue by adhesive, a strap, a band, a clamp, or other means.
`Sensor 34A includes first emitter 10, second emitter 20,
`first detector 12, and second detector 22. Emitters 10 and 20
`and detectors 12 and 22 are positioned about surface 36 in a
`manner that allows optical signals to freely pass between
`sensor 34A and biological tissue 50. In one example, emitters
`10 and 20 and detectors 12 and 22 are mounted to an electrical
`circuit (such as a printed wire board, a Substrate, rigid circuit
`board, or flexible circuit material) within sensor 34A and
`optical energy passes through an aperture or window in Sur
`face 36.
`In one example, at least one of first emitter 10 and second
`emitter 20 includes a light emitting diode (LED). In the figure,
`first emitter 10 and second emitter 20 are shown as unitary
`devices but in various examples, either can include multiple
`individual LEDs configured to produce light of a particular
`wavelength. In one example, first emitter 10 and second emit
`ter 20 include a fiber-optic element. The energy emitted by
`emitter 10 or emitter 20 can include visible light, infrared
`energy, and near infrared energy. In one example, first emitter
`10 produces light of a particular wavelength and secondemit
`ter 20 produces light of a different wavelength. First emitter
`10 and second emitter 20 are coupled to processor 30A by link
`15 and link 25, respectively.
`In one example, at least one of first detector 12 and second
`detector 22 includes a photodetector. First detector 12 and
`second detector 22 are configured to generate an output based
`on received energy having a particular wavelength. The sen
`sitivities of first detector 12 and second detector 22 can be
`selected (or adjusted) to generate an output for particular
`wavelengths. First detector 12 and second detector 22 are
`coupled to processor 30A by link 19 and link 29, respectively.
`In addition to sensor 34A, FIG. 1 illustrates biological
`tissue 50. Biological tissue 50, in the example shown, depicts
`a portion of a human forehead; however other biological
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`tissue can be monitored as well. For example, the present
`Subject matter can be used with an arm, a finger (or thumb), a
`toe, an ear lobe, and a torso.
`Biological tissue 50, as illustrated, includes a plurality of
`layers. As shown in the figure, the layers include scalp 52,
`skull 54, dura 56, arachnoid 58, pia mater 60, and cerebral
`cortex 62. In the figure, each layer has a relatively uniform
`thickness however, this can vary from site to site of a particu
`lar patient as well as from one patient to the next. A typical
`thickness for scalp 52 is in the range of 3 mm to 10 mm and for
`skull 54, the typical thickness is between 5 mm and 10 mm.
`As such, the brain (cerebral cortex) is typically at a depth of
`greater than 8 mm below the exterior surface of scalp 52.
`FIG. 1 illustrates region of interest 18 and exclusion region
`28. In the example shown, region of interest 18 lies wholly
`within the layer of cerebral cortex 62 at an average depth
`denoted by first depth 17. Region of interest 18 is represen
`tative of a portion of the cerebral cortex. Exclusion region 28
`extends from the surface of biological tissue 50 to nearly the
`region of interest 18 and has an average depth denoted by
`second depth 27. Exclusion region 28, in the example shown
`includes scalp 52, skull 54, dura 56, arachnoid 58, pia mater
`60, and a portion of cerebral cortex 62.
`In other examples, region of interest 18 and exclusion
`region 28 may occur in layers other than that shown in the
`figure. For example, region of interest 18 can lie in cerebral
`cortex 62 and exclusion region 28 can include the layers of
`dura 56, arachnoid 58, and pia mater 60. In one example,
`region of interest 18 can lie in a first portion of cerebral cortex
`62 and exclusion region 28 can include a second portion of
`cerebral cortex 62 where the first portion has a depth of 10 mm
`and the second portion has a depth of 8 mm. The depth of
`exclusion region 28 is less than the depth of the region of
`interest 18.
`As shown in the figure, energy emitted from first emitter 10
`can be modeled by path 16A and by path 26A. Path 16A
`enters biological tissue 50, traverses region of interest 18, and
`emerges from biological tissue 50 and the resulting energy is
`detected by second detector 22. Path 26A enters biological
`tissue 50, traverses exclusion region 28, and emerges from
`biological tissue 50 and the resulting energy is detected by
`first detector 12. In a similar manner, energy emitted from
`second emitter 20 can be modeled by path 16B and by path
`26B. Path 16B enters biological tissue 50, traverses region of
`interest 18, and emerges from biological tissue 50 and the
`resulting energy is detected by first detector 12. Path 26B
`enters biological tissue 50, traverses exclusion region 28, and
`emerges from biological tissue 50 and the resulting energy is
`detected by second detector 22.
`To the extent that paths 16A and 16B and paths 26A and
`26B are models, the actual path followed by energy delivered
`by sensor 34A may be different than that shown. For example,
`light scattering and other optical effects can change the actual
`path through biological tissue 50. Paths 16A, 16B, 26A, and
`26B represent a mean path by which light traverses biological
`tissue 50. In general, the light traverses the tissue in a curved
`shape that resembles a banana.
`Path 16B and path 26A illustrate that energy detected by
`first detector 12 originates from second emitter 20 and first
`emitter 10, respectively. In a similar manner, path 26B and
`path 16A illustrate that energy detected by second detector 22
`originates from secondemitter 20 and first emitter 10, respec
`tively.
`First emitter 10 is separated from first detector 12 by a
`lateral distance denoted in the figure as dimension 24A and is
`separated from second detector 22 by a lateral distance
`denoted in the figure as dimension 14A. In a similar manner,
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`Petitioner Apple Inc. - Exhibit 1063, p. 9
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`second emitter 20 is separated from second detector 22 by a
`lateral distance denoted in the figure as dimension 24B and is
`separated from first detector 12 by a lateral distance denoted
`in the figure as dimension 14B. Dimension 14A and dimen
`sion 14B are approximately equal and dimension 24A and 5
`dimension 24B are approximately equal. Dimension 14A
`(and thus dimension 14B) is approximately twice the length
`of dimension 24A (and thus dimension 24B), thus having a
`ratio of approximately 2:1.
`The depth of energy penetration into biological tissue 50, 10
`and thus the depth of the region (region of interest 18 or
`exclusion region 28) are proportional to the corresponding
`lateral distance. To a close approximation, the depth of pen
`etration is approximately one third the lateral distance at the
`surface of biological tissue 50.
`FIG. 2 illustrates system 200 according to one example.
`System 200 includes sensor 34B coupled by link 32B to a
`module, here shown to include processor 30B. Sensor 34B is
`affixed to a forehead of biological tissue 50 (depicted herein
`as that of an infant or neonate), however, sensor 34B can be 20
`affixed to another particular site of a human. Sensor 34B
`includes a pair of emitters and a pair of detectors as described
`elsewhere in this document, and in the example shown, is
`depicted as adhesively coupled to tissue 50. Link 32B is
`illustrated as a wired connection however, a wireless coupling 25
`is also contemplated. For example, link32B can include an
`optical fiber or a short-range radio frequency (RF) trans
`ceiver.
`Processor 30B is shown coupled to output 220. Output 220
`can include, in various examples, a visual display, a memory, 30
`a printer, a network (data or communication), a speaker, or
`other such device. In one example, processor 30B generates a
`processor output that is communicated to output 220. In one
`example, processor 30B and output 220 are part of a stand
`alone unit typically referred to as monitor 210. Monitor 210 35
`can be configured for patient use or for use by medical per
`Sonnel.
`FIG. 3 includes method 300 according to one example. At
`305, method 300 includes identifying a region of interest. The
`region of interest can include the cerebral cortex, a muscle, or 40
`other Substance at a particular depth within biological tissue.
`At 310, method 300 includes selecting a path depth based on
`the region of interest. The path traverses the biological tissue
`and the region of interest at a particular depth. In the example
`shown in FIG. 1, a representative path depth is depicted as 45
`first depth 17.
`The path can be projected onto an adjacent Surface of the
`biological tissue to yield a spacing dimension. At 315.
`method 300 includes establishing the dimension between the
`emitter and the detector. As shown in the example of FIG. 1, 50
`this corresponds to, for example, dimension 14A. For some
`biological tissue, the path length and depth are related by ratio
`of 3:1.
`Method 300 represents a general procedure for selection of
`a path length. The discussion has focused on the region of 55
`interest but a similar calculation can be performed for the
`region denoted earlier as the exclusion region.
`FIG. 4 includes method 400 according to one example. At
`405, method 400 includes identifying a region of interest
`disposed in a first layer of a biological tissue. With respect to 60
`the example of FIG. 1, region of interest 18 lies in the layer of
`cerebral cortex 62 of biological tissue 50. At 410, method 400
`includes identifying an exclusion region disposed in a second
`layer of the biological tissue. FIG. 1 illustrates exclusion
`region 28 within the layer of scalp 52, skull 54, dura 56, 65
`arachnoid 58, pia mater 60, and also cerebral cortex 62. As
`shown, exclusive region 28 occupies a different layer than
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`that of region of interest 18. In particular, the regions are
`exclusive of each other. In addition, the depth of region of
`interest 18 (depth 17) is greater than that of the depth of
`exclusion region 28 (depth 27).
`At 415, method 40