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Improving Non-Invasive Blood
Analysis by Expanding the Medical
         Spectral Window




                Katherine Paseman
Goal: Detect Medical Problems by non-
Invasively measuring Optical
Properties of Blood

Optical Blood   Medical             Example
Property        Diagnostic          Problem
                (Symptom)
Fluorescence    Zinc Protoporphyrin Iron Deficient
                (ZPP) Concentration Anemia, Lead
                                    Poisoning
Absorption      Hemoglobin          Anemia
                Concentration

Scattering      Hematocrit          Low- Blood loss,
                                    High - Dehydration
Beer-Lambert Law
 Optical approaches leverage the Beer-Lambert
  law which uses 3 variables to model light
  entering (Ii) and exiting (Io) a sample.
 Io = Ii 10 –2.303 ε(λ) c t /(64,500 g Hb/mole)
 t – Sample thickness – cm
 c – concentration of absorbent - g/liter (A typical
  value of c for whole blood is 150 g Hb/liter.)
 ε(λ) – extinction coefficient of absorbent, which
  is a function of the light’s wavelength.
    –   Blood’s ε(λ) is very large for λ < 600 nm
    –   This is why a flashlight shone through the hand only
        transmits red light.
Prior Work: Pulse Oximetry

   A Pulse Oximeter non-
    invasively determines Pulse
    and Blood Oxygenation using
    differential light absorption.
   A Photodiode measures light
    intensity of Red (660nm) &
    Infrared (940 nm) LEDs shone
    through Finger during
    systole/diastole.
   Blood Oxygenation is a
    function of the “Ratio of
    Ratios” of Light Intensities at
    these points.
                             Webster, JG. Design of Pulse Oximeters
Prior Work: Masimo pt 1

Most non-invasive blood      λ    Hb02 ε(λ)     Hb ε(λ)
                             nm   cm-1/M        cm-1/M
sensors extend the pulse
oximeter’s differential      610 1506           9443.6
absorption trick. Like the
                             620 942            6509.6
pulse oximeter, they
                             630 610            5148.8
target the finger using
                             660 319.6          3226.56
wavelengths above 600
nm, the so called ”Medical   700 290            1794.28

Spectral Window”, to         730 390            1102.2
collect enough light.        805 844            730.28
                             905 1209.2         769.8

                               Source: Masimo [US7377794]
Prior Work: Masimo pt 2




                          Medical
                          Spectral
                          Window
Prior Work: Samsung pt 1

Samsung’s work [Yoon et. al.        λ     Hb02 ε(λ)   Hb ε(λ)
  2005] states“Three variables            cm-1/M      cm-1/M
  of R569,805, R569,940, and
  R569,975 were used for            569 44496         45072
  calibration and prediction
  models.” producing this
  comment by one author:            660   319.6       3226.56
G Yoon <gyoon@snut.ac.kr> -
  569nm is highly absorbing in      805   844         730.28
  tissue and, at the same time,
  569nm intensity is small          940   1214        693.44
  compared with that at longer
  wavelength. That is why you
  may not get good signal. We       975   1144        389.288
  used a custom-made LED array
  that has several chips of 569nm
  to increase intensity.
Prior Work: Samsung pt 2


                            569 nm lies
                            outside the
                            Medical
                            Spectral
                            Window




                           Medical
                           Spectral
                           Window
Our Research: Target Thumb Webbing
for Absorption instead of Finger

   Our hypothesis: We can
    extend the medical spectral
    window by offsetting the
    increase in extinction
    coefficient at λ< 600 nm with a
    decrease in sample thickness
   [Sabrina Paseman 2008] did
    this by targeting the thumb
    webbing for fluorescence
    measurements.
   We do this for absorption.
   This allows us to get better
    absorption measurements by
    increasing signal and so
    decreasing noise based error.
   It also allows us to detect
    additional sources of error.
The Apparatus
   We created an adjustable width clip
    that fits either the subject’s index
    finger or thumb webbing.
   One end of the clip holds the same
    5-LED package used by Samsung
    and the other holds a fiber optic
    cable which connects to a
    spectrometer.
   This allows us to double check the
    LED’s wavelength, determine LED
    intensity, see if there are any LED
    artifacts, and observe any swamping
    or fluorescing effects.
   The LEDs and spectrometer were
    controlled by an Arduino
    microcontroller.
Experimental Approach 1

   Clamp is adjusted to fit the subject’s index finger.
    Subject removes finger so distance between
    spectrometer and LED can be measured with a
    micrometer.
   Thumb webbing is placed over the entire LED
   Spectrometer auto-adjusts the integration time to a
    full scale reading and the data is collected.
   Subject removes thumb webbing and places index
    finger over LED. Data is collected with the same
    integration time and plotted on the same axis for
    comparison
Data: 569 nm Subject 1

                             Thumb webbing
                             Index Finger
       54054.5 counts

                           Integration Time: 404.05 ms


                           Width: 0.7175 cm




           4131.5 counts
Findings

   Transmission increases 13 fold
   Samsung’s LED chip has an artifact at around 875nm
    when the 569nm LED is lit. If Samsung’s device uses
    a photodiode to collect light, especially at low
    intensities, much of the collected light would come
    from the artifact rather than the 569nm absorption
   This method limited the quality of the readings we
    could take from subjects with darker skin
Experimental Approach 2

 Hold  LED underneath the thumb webbing
  and the spectrometer on the other side.
 Let the spectrometer auto-integrate and
  capture the graph.
 For data analysis, find the ratio between the
  ratios of the peak counts at 569nm and the
  integration time               Counts        thumb webbing
                                      Integration timethumb webbing
         Absorption Amplification =
                                      Countsindex finger
                                      Integration timeindex finger
Integration Time: 3097.90 ms

Data: 569 nm Subject 1 Finger
                      50000
                                                                    Index Finger
                      40000
 Scope (ADC Counts)




                      30000


                      20000
                                                 13640.500 counts
                      10000


                          0
                               400   500   600        700          800     900     1000
                      -10000
                                                 Wavelength (nm)
Integration Time: 99.70 ms

Data: 569 nm Subject 1 Webbing

                     35000                                              Thumb Webbing
                                         32847.801 counts
                     30000

                     25000
Scope (ADC Counts)




                     20000

                     15000

                     10000

                     5000

                         0
                             400   500   600        700           800        900        1000
                     -5000
                                               Wavelength (nm)
Integration Time: 1736.15 ms

Data: 569 nm Subject 2 Finger

                      70000                                         Index Finger

                      60000
 Scope (ADC Counts)




                      50000

                      40000
                                                 33273.000 counts
                      30000

                      20000

                      10000

                           0
                               400   500   600        700          800     900     1000
                      -10000
                                                 Wavelength (nm)
Integration Time: 208.91 ms

Data: 569 nm Subject 2 Webbing

                      70000                                         Thumb Webbing
                      60000
                                            60849.000 counts
 Scope (ADC Counts)




                      50000

                      40000

                      30000

                      20000

                      10000

                          0
                               400   500   600         700         800    900       1000
                      -10000
                                                 Wavelength (nm)
Integration Time: 3808.11 ms

Data: 569 nm Subject 3 Finger

                      70000                                            Index Finger

                      60000
                                           60534.000 counts
                      50000
 Scope (ADC Counts)




                      40000

                      30000

                      20000

                      10000

                          0
                               400   500   600         700            800       900      1000
                      -10000
                                                 Wavelength (nm)
Integration Time: 114.73 ms

Data: 569 nm Subject 3 Webbing

                     60000
                                                                          Thumb Webbing
                                          55602.750 counts
                     50000


                     40000
Scope (ADC Counts)




                     30000


                     20000


                     10000


                         0
                              400   500   600        700            800         900       1000
                     -10000
                                                Wavelength (nm)
Data: 569 nm


Subject Scopetw (ADC   Integrationtw Scopeif (ADC   Integrati   Ampli-
        Counts)        (ms)          Counts)        onif        fication
                                                    (ms)
1       32847.801      99.70         13640.500      3097.90     74.825
2       60849.000      208.91        33273.000      1736.15     15.198
3       55602.750      114.73        60534.000      3808.11     30.488
Conclusions

 Transmission  increases across the board but
  varies from subject to subject
 Our suspicions about the artifact are
  confirmed by our second set up
Further Research
 See  if there is a statistically significant
  difference between the light absorption of
  systolic and diastolic blood at 569, 660, 805,
  940 and 975 nm.
 Correlate more medical problems to
  absorption differentials and fluorescent
  phenomena.
  –   See if there is a statistically significant difference
      between the fluorescence of systolic and diastolic
      blood excited at 425 nm.
 Collect
        data for more subjects with varying
  melanin contents
References
   [Sabrina Paseman 2008] Paseman, Sabrina. The
    Ferrometer: A Device to Detect Iron Deficient Anemia via
    Non-Invasive Optical Measurement of Zinc
    Protoporphyrin. Issue brief no. SO499. Los Angeles:
    University of Southern California, 2008. PDF file.
   [US7377794] "Multiple Wavelength Sensor Interconnect” –
    p57 lists Masimo’s wavelengths
   [Yoon et. Al. 2005] Yoon, Gilwon, Ph.D, et al. "Development
    of a Compact Home Health Monitor for Telemedicine."
    TELEMEDICINE AND e-HEALTH 11.6 (2005): 660-67.
    PDF File.
   “Tabulated Molar Extinction Coefficient for Hemoglobin in
    Water”
    http://omlc.ogi.edu/spectra/hemoglobin/summary.html

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Expanding the medical spectral window v6

  • 1. Improving Non-Invasive Blood Analysis by Expanding the Medical Spectral Window Katherine Paseman
  • 2. Goal: Detect Medical Problems by non- Invasively measuring Optical Properties of Blood Optical Blood Medical Example Property Diagnostic Problem (Symptom) Fluorescence Zinc Protoporphyrin Iron Deficient (ZPP) Concentration Anemia, Lead Poisoning Absorption Hemoglobin Anemia Concentration Scattering Hematocrit Low- Blood loss, High - Dehydration
  • 3. Beer-Lambert Law  Optical approaches leverage the Beer-Lambert law which uses 3 variables to model light entering (Ii) and exiting (Io) a sample.  Io = Ii 10 –2.303 ε(λ) c t /(64,500 g Hb/mole)  t – Sample thickness – cm  c – concentration of absorbent - g/liter (A typical value of c for whole blood is 150 g Hb/liter.)  ε(λ) – extinction coefficient of absorbent, which is a function of the light’s wavelength. – Blood’s ε(λ) is very large for λ < 600 nm – This is why a flashlight shone through the hand only transmits red light.
  • 4. Prior Work: Pulse Oximetry  A Pulse Oximeter non- invasively determines Pulse and Blood Oxygenation using differential light absorption.  A Photodiode measures light intensity of Red (660nm) & Infrared (940 nm) LEDs shone through Finger during systole/diastole.  Blood Oxygenation is a function of the “Ratio of Ratios” of Light Intensities at these points. Webster, JG. Design of Pulse Oximeters
  • 5. Prior Work: Masimo pt 1 Most non-invasive blood λ Hb02 ε(λ) Hb ε(λ) nm cm-1/M cm-1/M sensors extend the pulse oximeter’s differential 610 1506 9443.6 absorption trick. Like the 620 942 6509.6 pulse oximeter, they 630 610 5148.8 target the finger using 660 319.6 3226.56 wavelengths above 600 nm, the so called ”Medical 700 290 1794.28 Spectral Window”, to 730 390 1102.2 collect enough light. 805 844 730.28 905 1209.2 769.8 Source: Masimo [US7377794]
  • 6. Prior Work: Masimo pt 2 Medical Spectral Window
  • 7. Prior Work: Samsung pt 1 Samsung’s work [Yoon et. al. λ Hb02 ε(λ) Hb ε(λ) 2005] states“Three variables cm-1/M cm-1/M of R569,805, R569,940, and R569,975 were used for 569 44496 45072 calibration and prediction models.” producing this comment by one author: 660 319.6 3226.56 G Yoon <gyoon@snut.ac.kr> - 569nm is highly absorbing in 805 844 730.28 tissue and, at the same time, 569nm intensity is small 940 1214 693.44 compared with that at longer wavelength. That is why you may not get good signal. We 975 1144 389.288 used a custom-made LED array that has several chips of 569nm to increase intensity.
  • 8. Prior Work: Samsung pt 2 569 nm lies outside the Medical Spectral Window Medical Spectral Window
  • 9. Our Research: Target Thumb Webbing for Absorption instead of Finger  Our hypothesis: We can extend the medical spectral window by offsetting the increase in extinction coefficient at λ< 600 nm with a decrease in sample thickness  [Sabrina Paseman 2008] did this by targeting the thumb webbing for fluorescence measurements.  We do this for absorption.  This allows us to get better absorption measurements by increasing signal and so decreasing noise based error.  It also allows us to detect additional sources of error.
  • 10. The Apparatus  We created an adjustable width clip that fits either the subject’s index finger or thumb webbing.  One end of the clip holds the same 5-LED package used by Samsung and the other holds a fiber optic cable which connects to a spectrometer.  This allows us to double check the LED’s wavelength, determine LED intensity, see if there are any LED artifacts, and observe any swamping or fluorescing effects.  The LEDs and spectrometer were controlled by an Arduino microcontroller.
  • 11. Experimental Approach 1  Clamp is adjusted to fit the subject’s index finger. Subject removes finger so distance between spectrometer and LED can be measured with a micrometer.  Thumb webbing is placed over the entire LED  Spectrometer auto-adjusts the integration time to a full scale reading and the data is collected.  Subject removes thumb webbing and places index finger over LED. Data is collected with the same integration time and plotted on the same axis for comparison
  • 12. Data: 569 nm Subject 1 Thumb webbing Index Finger 54054.5 counts Integration Time: 404.05 ms Width: 0.7175 cm 4131.5 counts
  • 13. Findings  Transmission increases 13 fold  Samsung’s LED chip has an artifact at around 875nm when the 569nm LED is lit. If Samsung’s device uses a photodiode to collect light, especially at low intensities, much of the collected light would come from the artifact rather than the 569nm absorption  This method limited the quality of the readings we could take from subjects with darker skin
  • 14. Experimental Approach 2  Hold LED underneath the thumb webbing and the spectrometer on the other side.  Let the spectrometer auto-integrate and capture the graph.  For data analysis, find the ratio between the ratios of the peak counts at 569nm and the integration time Counts thumb webbing Integration timethumb webbing Absorption Amplification = Countsindex finger Integration timeindex finger
  • 15. Integration Time: 3097.90 ms Data: 569 nm Subject 1 Finger 50000 Index Finger 40000 Scope (ADC Counts) 30000 20000 13640.500 counts 10000 0 400 500 600 700 800 900 1000 -10000 Wavelength (nm)
  • 16. Integration Time: 99.70 ms Data: 569 nm Subject 1 Webbing 35000 Thumb Webbing 32847.801 counts 30000 25000 Scope (ADC Counts) 20000 15000 10000 5000 0 400 500 600 700 800 900 1000 -5000 Wavelength (nm)
  • 17. Integration Time: 1736.15 ms Data: 569 nm Subject 2 Finger 70000 Index Finger 60000 Scope (ADC Counts) 50000 40000 33273.000 counts 30000 20000 10000 0 400 500 600 700 800 900 1000 -10000 Wavelength (nm)
  • 18. Integration Time: 208.91 ms Data: 569 nm Subject 2 Webbing 70000 Thumb Webbing 60000 60849.000 counts Scope (ADC Counts) 50000 40000 30000 20000 10000 0 400 500 600 700 800 900 1000 -10000 Wavelength (nm)
  • 19. Integration Time: 3808.11 ms Data: 569 nm Subject 3 Finger 70000 Index Finger 60000 60534.000 counts 50000 Scope (ADC Counts) 40000 30000 20000 10000 0 400 500 600 700 800 900 1000 -10000 Wavelength (nm)
  • 20. Integration Time: 114.73 ms Data: 569 nm Subject 3 Webbing 60000 Thumb Webbing 55602.750 counts 50000 40000 Scope (ADC Counts) 30000 20000 10000 0 400 500 600 700 800 900 1000 -10000 Wavelength (nm)
  • 21. Data: 569 nm Subject Scopetw (ADC Integrationtw Scopeif (ADC Integrati Ampli- Counts) (ms) Counts) onif fication (ms) 1 32847.801 99.70 13640.500 3097.90 74.825 2 60849.000 208.91 33273.000 1736.15 15.198 3 55602.750 114.73 60534.000 3808.11 30.488
  • 22. Conclusions  Transmission increases across the board but varies from subject to subject  Our suspicions about the artifact are confirmed by our second set up
  • 23. Further Research  See if there is a statistically significant difference between the light absorption of systolic and diastolic blood at 569, 660, 805, 940 and 975 nm.  Correlate more medical problems to absorption differentials and fluorescent phenomena. – See if there is a statistically significant difference between the fluorescence of systolic and diastolic blood excited at 425 nm.  Collect data for more subjects with varying melanin contents
  • 24. References  [Sabrina Paseman 2008] Paseman, Sabrina. The Ferrometer: A Device to Detect Iron Deficient Anemia via Non-Invasive Optical Measurement of Zinc Protoporphyrin. Issue brief no. SO499. Los Angeles: University of Southern California, 2008. PDF file.  [US7377794] "Multiple Wavelength Sensor Interconnect” – p57 lists Masimo’s wavelengths  [Yoon et. Al. 2005] Yoon, Gilwon, Ph.D, et al. "Development of a Compact Home Health Monitor for Telemedicine." TELEMEDICINE AND e-HEALTH 11.6 (2005): 660-67. PDF File.  “Tabulated Molar Extinction Coefficient for Hemoglobin in Water” http://omlc.ogi.edu/spectra/hemoglobin/summary.html