Measurement of bioluminescence and thermal fields from ...kcreath/pdf/pubs/2006_KC_GES_SPIE_v6285_p6… · Measurement of bioluminescence and thermal fields from humans: Comparison

Measurement of bioluminescence and thermal fields from humans:

Comparison of three techniques for imaging biofields

Katherine Creatha,b,c,d

, Gary E. Schwartz b,d

aCollege of Optical Sciences, University of Arizona,

1630 E. University Blvd, Tucson, AZ, USA 85721-0094;

bCenter for Frontier Medicine in Biofield Science, University of Arizona,

1601 N. Tucson Blvd., Su.17, Tucson, AZ, USA 85719; cOptineering, and

dBiofield Optics, LLC, 2247 E. La Mirada St., Tucson, AZ, USA

ABSTRACT

All biological objects emit radiation over a large wavelength range as part of metabolic processes. We

hypothesize that biofields surrounding living biological objects can be observed by imaging the photonic and

thermal radiation emitted. In this paper we compare three different methods of visualizing biofields we have

developed over the last 3-1/2 years: imaging of self-bioluminescence with a highly-sensitive silicon CCD

array, dynamic interferometry for measurement of subtle thermal microbursts from biological objects

correlated with pulse and respiration, and infrared imaging in the 3-5µm region. Although the self-

bioluminescence signal is weak from humans, it can be imaged using 10min exposures with a highly sensitive

camera. These speeds do not enable tracking of dynamic changes, but they do enable looking at subtle

processes that have not been previously imaged. Dynamic interferometry provides a means of measuring

subtle variations in refractive index of air currents by freezing them in time. These air currents are related to

bursts of thermal energy emitted by the human body. Although the body is not directly measured, it is possible

to track cycles in the range of tenths of seconds to many seconds. Infrared imaging has the advantage of both

being fast and not requiring a darkened enclosure. Subtle changes in temperature can be tracked, but ambient

environmental conditions need to be controlled to get absolute numbers. Tracking relative changes works the

best with this technique. Each of these techniques has advantages and disadvantages that are outlined in this

paper. The technique of choice depends upon the particular application. The rate at which the technology is

developing and improving indicates that soon it will be much easier to apply any of these techniques to a wider

variety of applications.

Keywords: bioluminescence, autoluminescence, biophoton imaging, dynamic interferometry, infrared imaging,

biofield measurement

1. INTRODUCTION

Biofields are fields surrounding living biological objects.1 They can have photonic, thermal, magnetic and

electromagnetic components.2 These fields can provide information about the state of being of a living system.

Although not visible with the naked eye, highly sensitive optical instruments are able to detect and measure aspects of

these fields that our eyes cannot see.

The research presented in this paper has grown out of an intention to develop instrumentation to measure these fields

from and around living objects to support research in energy healing and complementary and alternative medicine

(CAM).3 In particular, our interest has been to develop techniques to detect subtle changes in biofields that can be

[email protected]; phone 1 520 626-1730; fax 1 520 882-6976

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linked to state of health in humans and to develop quantitative measures of healer efficacy and healing energy dosage

for energy healing.

This paper discusses three different techniques we have developed and studied over the last 3-1/2 years. The first

technique uses a highly-sensitive low-noise CCD sensitive to radiation between 400-1000nm. Oxidative metabolic

processes within the biological system producing singlet oxygen have been shown to produce this self-bioluminescence

(also known as autoluminescence and biophoton emission) in the red and near infrared region of the spectrum in plant,

animal and human cells.4-8

This technique requires long exposures and total darkness and the technology is not yet

sufficiently advanced to allow short-exposure, high-resolution, low-noise imaging.

The second technique, known as dynamic interferometry (DI), enables dynamic tracking of thermal fields around the

body. Although this technique doesn’t directly measure the biological object, it is highly sensitive to very small

temperature variations and microchanges in refractive index caused by these temperature fluctuations.

The third technique directly measures thermal infrared (IR) fields in a biological object by imaging the infrared

radiation emitted from the object. This type of measurement sometimes called thermography has been studied for a

couple of decades. Recently the technology has developed to the point of easily being able to purchase high-resolution

infrared imaging arrays. Although these devices can easily be used in broad daylight, they appear to be best suited for

following relative variations as a function of time in an environmentally controlled setting. Careful measurements with

a sensitive camera can enable tracking blood flow or distribution of drugs within a biological system.9, 10

2. BACKGROUND 2.1 Self-Bioluminescence

During metabolics processes, all biological systems absorb and emit light. This emission is known as biological

chemiluminescence or bioluminescence. When there are no external radiation sources present and no chemical or

biological markers have been used, it is further differentiated as self-bioluminescence. It is a type of autoluminescence

or light produced from internal energy in the organism. In the last few decades many authors have referred to this

emission as biophoton emission to provide a short catchy word. However, most of the literature on these phenomena,

especially studies done on a cellular level with plant, animal and human cells, are easier to find by searching for

chemiluminescence and bioluminescence.

Research investigating these processes has been abundant. There are hundreds of published papers describing this

emission in plants, bacteria, and animals – including humans (reviews include refs.11-13.11-13

). It is well-known that all

living organisms emit low-intensity chemiluminescence as part of their metabolic processes.4, 5

When electrons move

between energy states during chemical reactions as part of metabolic processes, photons may either be absorbed or

emitted. A major source of photons is the breaking down of larger molecules into smaller ones resulting in the chemical

byproducts of the reaction as well as emitted photons. (The opposite can also be observed in the example of

photosynthesis where smaller molecules are combined with the absorption of photons from sunlight to create larger

molecules.) (see, for example, refs. 6-7.6, 7

)

A common link between plants, animals and humans is that emission has been measured in the wavelength range of

600-900 m from isolated plant, animal and human mitochondria.14-17

Mitochondria serve a vital role in the healthy

functioning of cells and energy metabolism. Another link among plant, animal and human cells is a correlation between

singlet oxygen production not related to chlorophyll or mitrochondria and increased photon emission.18-21

Recent

research indicates that the presence of free radicals, reactive oxygen species and singlet oxygen is associated with

weakened immune function and various diseases.22-24

In live animals most bioluminescence studies utilize markers of

some kind. One type of background noise they have to deal with is autoluminescence (self-bioluminescence). The

spectra of this radiation has recently been measured by Troy et al, and found to peak at around 660nm and be related to

metabolic processes after ruling out hair, food, and other possible sources.25

They also note that this radiation is not

there after the animal is euthanized so it is not likely due to blackbody radiation either. Because of the similarities in the

emission from different types of cells, an advantage of developing a self-bioluminescence measurement (biophoton)

model is that studies beginning with plants can be then be extended to animals and humans. A more thorough review of

the literature is available in ref. 8.8



2.2 Dynamic Interferometry

The human body emits dynamic patterns of thermal radiation as well as light as part of basic metabolic processes.

Cycles with time constants related to blood flow and respiration generate small bursts of thermal energy that create

convective air currents we term “microbreezes.” Thermal variations caused by these microbreezes subtly modulate the

refractive index of the air around the perimeter of biological systems. Subtle changes in refractive index change the

optical path length of rays of light by fractions of a wavelength of light. These subtle optical path length variations can

be measured using interferometry.26

Dynamic interferometry is a highly sensitive means of obtaining phase information that can take phase data at rates of

multiple frames per second.27, 28

Dynamic interferometry techniques enable taking all necessary interferometric data

simultaneously to determine phase in a single snapshot.29-31

These instruments have been designed with the purpose of

measuring phase data in the presence of vibration and air turbulence.32, 33

Interferograms can be captured in “real” time.

Turbulence in the area near an object can be “frozen.” Flows and vibrational motion can be followed.34

Quantitative

phase maps can be obtained over a time series to create movies (“burst” mode) of the optical path (OPD) variations over

time due to a living biological object.

The system used for our measurements is comprised of a phase-measuring Twyman-Green interferometer with the

ability to multiplex all necessary data onto a single CCD camera utilizing a specially designed holographic optical

element.32-34

The multiplexed data are used to calculate the relative optical path difference (OPD) between a reference

path and a object test path in units of wavelengths of departure.35

Although absolute determinations of refractive index

and temperature are not possible with this system, relative variations are measurable. The minimum detectable variation

is approximately 0.001 waves corresponding to a refractive index change of roughly 1 part in 104.36, 37

This sensitivity enables measurement of the relative motion of air molecules in space. Normally, for most optical

measurements using DI, the kind of “signal” we are looking for in our measurements was usually considered as “noise.”

Instead, we have considered subtle dynamic changes in the air currents as “signal” to be imaged. At this level of

sensitivity noise sources must be carefully adjusted and accounted for.

For the study presented in this paper we focused on looking at the difference between room temperature and body

temperature objects and compared these to a human finger. The human body dynamically emits thermal energy. This

thermal energy relates to metabolic processes. We hypothesize that the thermal emission from the human body is

dynamic and cycles with time constants related to blood flow and respiration. These cycles create small bursts of

thermal energy that creates convection and air currents. We have termed these subtle air currents generated by the

human body “microbreezes”. The thermal variations of these microbreezes modulate the refractive index of the air path.

Because dynamic interferometry can measure subtle changes in refractive index and thereby measure air currents and

microbreezes, we hypothesize that this technique will enable us to visualize the thermal aura around human body parts

such as a finger tip, and furthermore that we will be able to quantify the relative variations over time.

2.3 Infrared Imaging

All objects emit infrared radiation as a function of their temperature.38

The wavelength of this radiation can vary from

0.7µm to 100µm in the electromagnetic spectrum. The spectral range of interest for biological objects is in the infrared

from 0.7µm to 14µm with major water transmission regions in the mid-IR (3–5 µm) and far-IR (8–14 µm).38

Infrared

technology has become more affordable in the last decade and this has lead to the application of this technology to a

wide variety of new biological applications.38-40

For example, thermal imaging has been used to look at breast

malignancies,41

mapping perforator blood vessels,9 radiative heat loss in barn owls in motion,

42 cervical disk

herniations,43

and movement of drugs after injection into a horse’s leg.10

Most biological objects are modeled as “black bodies” that have a well-defined energetic output as a function of

wavelength given by the Planck energy distribution formula.38, 44

The peak of the blackbody radiation curve moves to

lower wavelengths as the blackbody temperature increases. For example, a 5000°K blackbody has its peak in the mid-



part of the visible spectrum (yellow). For room temperature background radiation at 300°K, there is almost no radiation

below 0.7µm and only a few photons in the near infrared extending up to 1µm.

The maximum radiation output of biological specimens varies between specimens and depends upon several factors.45

For human skin, the wavelength bands of interest are 3-5µm and 8-12µm because these are regions where water

transmits the radiation and we are mostly made of water. Although the IR signal from human skin is higher in the 8-

12µm region, depending upon the application and other noise sources present, one or the other wavelength band may be

advantageous.40

3. SELF-BIOLUMINESCENCE (BIOPHOTON) IMAGING

The imaging system used for these measurements was a Princeton Instruments VersArray 1300B low-noise high-

performance CCD with cryogenic cooler, manufactured by Roper Scientific.46

The system includes a camera head

containing the sensor and readout electronics along with electronics to get images into a computer, a CryoTiger

cryogenic cooler and software for controlling the camera and acquiring images. The camera is mounted on top of a dark

box that is as light tight as possible (see Fig. 1). The sensor is a back-illuminated silicon CCD with 20 m x 20 m pixels

(E2V CCD36-40, grade 1) digitized to 16 bits yielding 65,536 grey scale levels (GSLs). It is cooled to reduce thermal

and readout noise. For optimal exposures, the sensor is cooled to a temperature of –80 to –100°C using the CryoTiger.

The response of this sensor spans from 350-1000 nm with the maximum response in the 400-800 nm wavelength range.

Figure 1. Photograph of imaging system. Not

shown is the optional door (a cloth darkroom bag)

with light tight cuffs for imaging of hands.

A standard Nikon F/1.2 50mm lens set at F/1.2 is used as the

imaging lens. The field of view (FOV) at the closest focal

distance (CFD) is 220 mm wide. The sensor output is directly

proportional to the number of photons incident at each pixel.

Using Roper Scientific46

specifications when operating the camera

in low-noise mode with a gain of 4x and assuming an average

quantum efficiency of 0.8 there are approximately 1.6 photons per

GSL. This camera is essentially close to counting photons.

Because nothing is ever 100% light tight (just as you can’t remove

every dust particle in a clean room) darkness of the chamber and

surrounding room were repeatedly tested using 10min to 1 hour

long exposures to ensure that the background illumination was as

low as possible and below the electronic noise level of the sensor.

Baseline images are taken without the presence of objects and

have the same exposure time as the regular images so that we may

determine noise background levels.

Emission of self-generated radiation from the human body as part

of basic metabolic processes has been measured with

photomultiplier tubes by many researchers from the hands and

other body parts.47, 48

Typically, a photomultiplier tube measures

about 20-30 photons per cm2 per sec compared to about 200

photons per cm2 per sec that can be measured from plant

parts.13, 48

Results from the work of Choi et al.48

and Cohen and

Popp47

show that the emission from human bodies varies

depending upon state of health, position on the body, time of day,

and time of the year.

Figure 2 shows images of the first author’s (KC’s) hands taken by the second author using the system depicted in Fig. 1

with 10-minute exposures in total darkness. The camera was configured utilizing hardware binning (during integration

before readout) providing 67x65 pixels with each pixel having a 400 m square sensing area. The bright spots are

“cosmic ray hits” from higher energy noise in the room. Their effects on the image can be reduced by using a 5x5



median window filter, but some of the detail would be blurred. Note that the fingertips are more emissive than say the

back of the hands, and the palms of the hands are in between. These images show good detail, but because of the long

exposure times they do not enable us to look at dynamic changes on shorter time scales.

Figure 2. Top images are 10-minute exposures taken in total darkness using 20x20 binning with a

Princeton Instruments VersArray 1300B camera cooled to –100°C. These images represent biophoton

emission (biological chemiluminescence) generated within the body as part of normal biological

metabolic processes. Bottom images are 10ms exposures taken with white-light illumination.

4. DYNAMIC INTERFEROMETRY

The dynamic interferometer used for this study was a PhaseCam developed by 4D Technology.49

This system takes all

necessary interferometric data simultaneously to determine phase in a single snapshot.29-31

These instruments have been

designed with the purpose of measuring phase data in the presence of vibration and air turbulence.32, 33

Interferograms

can be captured in “real” time and turbulence in the area near an object can be “frozen.” Quantitative phase maps can be

obtained over a time series to create movies (“burst” mode) of the optical path (OPD) variations over time due to a

living biological object. More details about the system can be found in refs. 32, 33, and 36. 32, 33, 36

For this study the dynamic interferometer was set up as shown in Fig. 3. The object cavity between the collimating lens

and the return mirror was enclosed with a cardboard tube except for an approximately 3cm space to place the object in

the beam. This limited ambient air currents from affecting the measurements as much as possible. Interferograms were

taken as a series of images in real time and then subsequently evaluated and averaged (if desired) to produce phase

maps. Reference data sets were taken with no object present and averaged 30 single measurements taken in a single



Optical Transferand HolographicElement

PhasePlate

I

Enclosure

N

CollimatingLens

Single Mode Laser

IF-ReturnMirror

Object

High• Resolution

PolanzerCamera

I

burst. They were subtracted from subsequent measurements to remove variations across the field due to the

interferometer itself and create a null cavity when no object was present.

Figure 3. Dynamic interferometer setup. All beam paths are enclosed except for 3 cm in the object beam for

placement of object.

Figure 4 displays various images of the dynamics of air under different conditions. The images are snapshots taken in a

single CCD frame (30ms). To subtract out effects of optical elements in the system a reference measurement consisting

of an average of 30 single frame measurements of an empty cavity has been subtracted from every subsequent

measurement shown. All images are scaled from –0.05 to +0.05 waves OPD. Figure 4A shows the empty object cavity.

Bright areas (white) are warmer than dark areas (black). Figure 4B shows a blast from a can of canned air. Note that the

turbulence is easily frozen in time and that the canned air is cooler than the background air. Figure 4C shows the effect

of a candle flame below the object beam. The area heated by the candle flame is obviously brighter than the darker

ambient air temperature.

(A) (B) (C)

Figure 4. (A) Empty object cavity. (B) Blast of canned air. (C) Candle flame. Bright (yellow) is warm and dark (blue) is cool.

Figure 5A shows a screwdriver handle approximately 2 cm across at room temperature. These images are scaled the

same as Fig. 4. The presence of the room temperature screwdriver handle does not appear to thermally affect the air

path at all. However, when the screwdriver handle is warmed up to body temperature and placed in the beam, there is

obviously a thermal gradient around it (Fig. 5B). Figure 5C shows a finger of the second author placed in the beam.

Note that the thermal gradient around the finger is similar to that around the body temperature screwdriver handle. The

differences between these two objects are mainly in the surrounding “halo”.



a

IP

(A) (B) (C)

Figure 5. (A) Room temperature screwdriver handle. (B) Body temperature screwdriver handle. (C) Human finger. All

phase maps are scaled from +0.050 to –0.050 waves for comparison.

Figure 6 displays three consecutive images of dynamic air patterns taken ~0.1s apart surrounding the tip of a human

finger (A-C) and a screwdriver handle at finger temperature (D-F). The images were further processed using ImageJ

software50

utilizing a lookup table to reveal structure and changes in structure over time. A number of distinctions can

be seen in these figures. The screwdriver is more symmetric and static, while the finger is more asymmetric and

dynamic.

(A) (B) (C)

(D) (E) (F)

Figure 6. Consecutive images taken ~0.1s apart of a human finger (A-C) and a body temperature screwdriver handle

(D-F). Lines indicate areas of equal optical path like a topographic map. Note there are more dynamic variations

between images of the finger than the screwdriver handle.



When displayed as a movie the difference in dynamics reveals that the pattern around the finger pulsates approximately

once per second while the pattern around the screwdriver is relatively static. Dynamic interactions in living systems

become much easier to visual when the movies are displayed using pseudo-color lookup tables.

5. INFRARED IMAGING

Because of the low light levels from the bioluminescence measurements, we investigated infrared imaging as another

alternative for sensing biofields. This type of imaging intrigued us both because of the body of research that has been

done with thermal imaging and thermography (see for instance refs. 38-40.38-40

), and because we have seen what we

hypothesize to be subtle temperature fluctuations with dynamic interferometry, and subtle stress and energy responses

could possibly be manifest as subtle temperature variations.

The camera used in this study is a Merlin InSb Laboratory Camera manufactured by Indigo Systems (now part of FLIR

Systems). It uses a cold filter to limit its wavelength sensitive to radiation in the 3-5 m region. It operates at 30 frames

(or 60 fields) per second providing a standard NTSC output with a dynamic range of >72dB and well capacity of 18x106

electrons which is digitized to 12 bits. The sensor, housed in a Dewar, is cooled to liquid nitrogen temperatures during

normal operation (77°K or –320°F). The focal plane array is an ISC9705 chip with 320x256 pixels on a 30 m pitch.

The standard range of the sensor is 0-350°C with an accuracy of ±2°C and a minimum detectable temperature difference

of approximately 0.1°C. All images were taken using a standard imaging lens. A background image of a cold paddle at

liquid nitrogen temperature (77°K) was subtracted from all images. All images were then processed using a median

window of 5x5 or 7x7 pixels to reduce the noise and help fill in the bad pixels. This particular array had a lot of non-

responding pixels. Those remaining after processing appear as dark spots. The images are scaled by using histogram

stretching for best reproduction in this medium. The scales of the individual images have not all been set the same.

Figure 7 shows the primary author’s (KC’s) right hand next to a cup of hot water. In Fig. 7A the room lights are on,

whereas in Fig. 7B the room lights are off and the door is closed to created a visibly darkened environment. As expected

this did not change the background illumination or the object illumination. Note that detail of temperature as a function

of position can be determined relatively easily from these images.

(A) (B)

Figure 7. (A) Room lights on. (B) Room lights off and door closed. Note that ambient room light does not

have much affect on image in 3-5 m images.

Because we are interested in dynamic images and seeing differences as a function of time, the 30 frames per second we

could obtain from this camera was of interest. We noted that it was possible to see the blood pulsating in veins as well

as view air expelled from the mouth.

With all we could do with this sensor, we did encounter limitations that would make comparative studies difficult. In

the research literature where others have studied various subjects using IR imaging, most have not said much about

these limitations. The largest by far is ambient temperature. A good example of this is shown in Fig. 8 where 2 images

of KC’s hand are shown taken on 2 different days. In the one on the left the veins in the back of the hand are brighter



indicating they are warmer than the surrounding tissue, whereas in the image on the right the veins are darker indicating

they are cooler than the surrounding tissue. So this brings up the need to make sure the body acclimatizes to the room

before taking images. With these images it also depended on whether I had on long or short sleeves and what I had just

been doing – ie. had I just picked up a mug of hot water?

(A) (B)

Figure 8. Back of KC’s hand in darkened room. (A) Taken on 29 Nov 2004. (B) Taken on 14 Dec 2004.

Not scaled to absolute temperature. Note the relative difference in skin temperature and temperature of veins.

One day the veins are warmer, the other they are cooler than the surrounding tissue.

From the studies we have done so far it appears that doing quantitative analysis as a function of time to find relative

changes after the object has acclimatized to the room would be the best way to study subtle changes. Determining

absolute differences with this particular sensor and environment is not possible when looking at small temperature

differences. There are other sensors manufactured that on paper appear to be more accurate, but to do careful

measurements the environment and thermal experimental conditions need to be carefully monitored and controlled as

much as possible.

6. DISCUSSION 6.1 Self-bioluminescence Imaging

In other experiments we have demonstrated that self-bioluminescence (biophoton) imaging can quantitatively and

locally monitor physiological processes such as response to injury in plants.8 The average BE (bioluminescence

emission) in a given area yields indications about localized metabolic processes and the functional state of health of the

living system as it is tracked with time. The quantitative nature of BE enables it to be a baseline measurement correlated

to state of health that can be used as a measured outcome to determine efficacy of any therapeutic modality (i.e. energy

healing, herbs, drugs, etc.).

The results we have presented here show that it is also possible to image BE from human body parts. At this point in

time we have not yet performed the detailed tests on human subjects that we have with plants. However, our lab at the

University of Arizona has another study underway that is imaging the hands of 50 different human subjects under

different conditions to determine if we can see variations between individuals and different conditions.51

6.2 Dynamic Interferometry

The sensitivity of the dynamic interferometry measurements shows that our eye can easily discern 0.01 waves

difference in OPD (optical path difference). Calculations can further extend the repeatability to have a sensitivity of

around 0.001 waves. The refractive index of air is roughly 1.003 and is dependent upon temperature, pressure, humidity,

CO2 quantity and wavelength. These dependencies have been studied extensively for accurate distance measurements

using light.26

Operating with an interferometric measurement sensitivity on the order of 0.001 waves, variations of 1

part in 104 of refractive index can be resolved. As seen in the phase maps presented here, this type of variation is

apparent in the fields around the human fingers.



The main limitation of dynamic interferometry as used in this study is that the software in its current incarnation does

not enable unwrapping the phase in time. This would enable tracking a specific air current over time and enable

determination of the refractive index (or OPD changes) between frames of phase data. Because algorithms have been

developed for this unwrapping in other interferometer applications we do not feel that this is a major limitation. Since

we are interested in dynamic changes and not absolute values, we feel that this technique is useful for tracking dynamic

changes in subtle thermal fields around biological objects.

6.3 Infrared Imaging

Infrared imaging enables tracking subtle thermal variations such as blood flow in biological objects in real time.

Cameras are now available that have at least an order of magnitude finer thermal resolution that the camera used in our

studies, yet we were still able to discern changes with time in our short movies. With a camera having a larger dynamic

range and digitizing to 16 bits instead of 12 it should be possible to discern differences of 0.01 degrees C.

Our experience with IR imaging shows that environmental factors are important considerations when designing

measurements in the IR. In much of the literature published relating to IR imaging of biological objects, not much is

mentioned about environmental factors. In studies with environmental controls, most commonly the ambient room

temperature is controlled and taken into account.38

Background radiation is usually accounted for because the imaging

software enables a baseline measurement to be subtracted from all subsequent measurements. Some studies have shown

that some environmental factors do not need to be controlled.10, 40

However, when objects are not given time to come to

thermal equilibrium with their environment, measurements will vary because the absolute temperature values are

different as seen in our results. In studies that look at relative differences or compare different parts of the same object,

results appear to be more consistent.

7. CONCLUSIONS

Research in these techniques and their applications are all in the developmental stages. There are many opportunities for

research to better understand the nature and function of these types of radiation and how they relate to the state of the

biological system. The potential applications in medical and biological research are many and range from basic science

experiments measuring the variations as a function of various physiological conditions to clinical studies evaluating

different types of interventions. We are particularly interested in applications related to complementary and integrative

medicine to track and quantify dynamical variations in these emissions as a function of time.

As with most newer technology, performance is directly proportional to cost. However, the trends in new technology

are pointing towards more versatile and less expensive systems. Within the next decade we should realize at least as

great of an improvement in our imaging capabilities as we have in the last decade.

Light holds an important key in our understanding of biofields and the dynamics of energy within a biosystem. Images

like these give us a window into a seemingly invisible part of the mystery of light and life. We are only beginning to

see the light within.

ACKNOWLEDGEMENTS

The authors wish to thank Prof. Arthur F. Gmitro and his research group for use of equipment and facilities for the bioluminescence (biophoton) measurements, Steve Martinek and John Hayes of 4D Technology, Inc. for the use of their

PhaseCam interferometer, Prof. Eustace Dereniak and Jim Scholl for use of their infrared imaging system, and Ben

Johnson for helping with literature searches. This work was partially supported by NIH P20 AT00774-01 (Center for Frontier Medicine in Biofield Science, GES Director) from the National Center for Complementary and Alternative

Medicine (NCCAM). The contents of this paper are solely the responsibility of the authors and do not necessarily

represent the official views of NCCAM or NIH.

Proc. of SPIE Vol. 6285 628505-10


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