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The Energetic Heart: Bioelectromagnetic Communication Within and Between People

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https://www.researchgate.net/profile/Rollin_Mccraty2/publication/274451622_The_Energetic_Heart_Biolectromagnetic_Interactions_Within_and_Between_People/links/55938d3808aed7453d466f86/The-Energetic-Heart-Biolectromagnetic-Interactions-Within-and-Between-People.pdf

This paper will focus on electromagnetic fields generated by the heart that permeate every cell and may act as a synchronizing signal for the body in a manner analogous to information carried by radio waves. Particular emphasis will be devoted to evidence demonstrating that this energy is not only transmitted internally to the brain but is also detectable by others within its range of communication. Finally, data will be discussed indicating that cells studied in vitro are also responsive to the heart’s bioelectromagnetic field. 

https://www.researchgate.net/publication/274451622_The_Energetic_Heart_Biolectromagnetic_Interactions_Within_and_Between_People [accessed Feb 09 2018].

The Energetic Heart

Bioelectromagnetic Interactions

Within and Between People

Rollin McCraty, Ph.D.

HeartMath Research Center

Institute of HeartMath

Copyright © 2003 Institute of HeartMath

All rights reserved. No part of this book may be reproduced or transmitted

in any form or by any means, electronic or mechanical, including photocopying,

recording, or by any information storage and retrieval system without

permission in writing from the publisher.

Published in the United States of America by:

Institute of HeartMath

14700 West Park Ave., Boulder Creek, California 95006

1-831-338-8500

info@heartmath.org

http://www.heartmath.org

Manufactured in the United States of America.

First Edition 2003

Cover design Sandy Royall

1

The Energetic Heart:

Bioelectromagnetic Interactions Within and Between People

Rollin McCraty, Ph.D.

Man’s perceptions are not bounded by organs of perception; he perceives far more

than sense (tho’ ever so acute) can discover. —William Blake

This paper will focus on electromagnetic fields

generated by the heart that permeate every cell and

may act as a synchronizing signal for the body in a

manner analogous to information carried by radio

waves. Particular emphasis will be devoted to evi-

dence demonstrating that this energy is not only

transmitted internally to the brain but is also de-

tectable by others within its range of communica-

tion. Finally, data will be discussed indicating that

cells studied in vitro are also responsive to the heart’s

bioelectromagnetic field.

The heart generates the largest electromag-

netic field in the body. The electrical field as mea-

sured in an electrocardiogram (ECG) is about 60

times greater in amplitude than the brain waves re-

corded in an electroencephalogram (EEG). The

magnetic component of the heart’s field, which is

around 5000 times stronger than that produced by

the brain, is not impeded by tissues and can be mea-

sured several feet away from the body with Super-

conducting Quantum Interference Device (SQUID)-

based magnetometers.1 We have also found that the

clear rhythmic patterns in beat-to-beat heart rate

variability are distinctly altered when different emo-

tions are experienced. These changes in electromag-

netic, sound pressure, and blood pressure waves pro-

duced by cardiac rhythmic activity are “felt” by ev-

ery cell in the body, further supporting the heart’s

role as a global internal synchronizing signal.

Biological Patterns Encode Information

One of the primary ways that signals and mes-

sages are encoded and transmitted in physiological

systems is in the language of patterns. In the ner-

vous system, it is well established that information

is encoded in the time intervals between action po-

tentials—patterns of electrical activity—and this may

also apply to humoral communications. Several re-

cent studies have revealed that biologically relevant

information is encoded in the time interval between

hormonal pulses.2-4 As the heart secretes a number

of different hormones with each contraction, there

is a hormonal pulse pattern that correlates with heart

rhythms. In addition to the encoding of information

in the space between nerve impulses and in the in-

tervals between hormonal pulses, it is likely that in-

formation is also encoded in the interbeat intervals

of the pressure and electromagnetic waves produced

by the heart. Karl Pribram has proposed that the low-

frequency oscillations generated by the heart and

body in the form of afferent neural, hormonal, and

electrical patterns are the carriers of emotional in-

formation, and that the higher frequency oscillations

found in the EEG reflect the conscious perception

and labeling of feelings and emotions.5

Detecting Bioelectromagnetic Patterns Using Signal

Averaging

A useful technique for detecting patterns in

biological systems and investigating a number of

bioelectromagnetic phenomena is signal averaging.

This is accomplished by superimposing any number

of equal-length epochs, each of which contains a re-

peating periodic signal. This emphasizes and distin-

guishes any signal that is time-locked to the periodic

signal while eliminating variations that are not time-

locked to the periodic signal. This procedure is com-

HeartMath Research Center, Institute of HeartMath, Publication No.

02-035. Boulder Creek, CA, 2002.

An abbreviated version of this paper is published as a chapter in

Clinical Applications of Bioelectromagnetic Medicine, edited by Paul

Rosch and Marko Markov. New York: Marcel Dekker, in press.

Address for correspondence: Rollin McCraty, Ph.D., HeartMath

Research Center, Institute of HeartMath, 14700 West Park Avenue,

Boulder Creek, CA 95006. Phone: 831.338.8500, Fax: 831.338.1182,

Email: rollin@heartmath.org. Institute of HeartMath web site:

www.heartmath.org.

© Copyright 2003 Institute of HeartMath

2

monly used to detect and record cerebral cortical

responses to sensory stimulation.6 When signal av-

eraging is used to detect activity in the EEG that is

time-locked to the ECG, the resultant waveform is

called the heartbeat evoked potential.

The Heartbeat Evoked Potential

In looking at heartbeat evoked potential data,

it can be seen that the electromagnetic signal arrives

at the brain instantaneously, while a host of differ-

ent neural signals reach the brain starting about 8

milliseconds later and continue arriving throughout

the cardiac cycle. Although the precise timing var-

ies with each cycle, at around 240 milliseconds the

blood pressure wave arrives at the brain and acts to

synchronize neural activity, especially the alpha

rhythm. It is also possible that information is en-

coded in the shape (modulation) of the ECG wave

itself. For example, if one examines consecutive ECG

cycles, it can be seen that each wave is slightly var-

ied in a complex manner.

As indicated, the heart generates a powerful

pressure wave that travels rapidly throughout the

arteries much faster than the actual flow of blood

that we feel as our pulse. These pressure waves force

the blood cells through the capillaries to provide

oxygen and nutrients to cells and expand the arter-

Overlapped segments

before averaging

(mV)

(µV)

-1

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00.20.40.60.811.2

Seconds

Signal averaging is a digital

technique for separating a

repetitive signal from noise without

introducing signal distortion.

-0.5

0.5

-1

1

012345

Seconds

-0.5

0.5

-1

1

00.20.40.60.811.2

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-0.2

0.2

(mV)

(µV)

(mV)

(µV)

Resultant waveforms after

averaging

ies, causing them to generate a relatively large elec-

trical voltage. These waves also apply pressure to

the cells in a rhythmic fashion that can cause some

of their proteins to generate an electrical current in

response to this “squeeze.” Experiments conducted

in our laboratory have shown that a change in the

brain’s electrical activity can be seen when the blood

pressure wave reaches the brain around 240 milli-

seconds after systole.

There is a replicable and complex distribution

of heartbeat evoked potentials across the scalp.

Changes in these evoked potentials associated with

the heart’s afferent neurological input to the brain

are detectable between 50 to 550 milliseconds after

the heartbeat.7 Gary Schwartz and colleagues at the

University of Arizona believe the earlier components

in this complex distribution cannot be explained by

simple physiological mechanisms alone and suggest

that an energetic interaction between the heart and

brain also occurs.8 They have confirmed our find-

ings that heart-focused attention is associated with

increased heart-brain synchrony, providing further

support for energetic heart-brain communications.

Schwartz and colleagues also demonstrated that

Figure 1. Signal averaging.

The sequence of the signal averaging procedure is shown above.

First, the signals recorded from the EEG and ECG are digitized

and stored in a computer. The R-wave (peak) of the ECG is

used as the time reference for cutting the EEG and ECG signals

into individual segments. The individual segments are then

averaged together to produce the resultant waveforms. Only

signals that are repeatedly synchronous with the ECG are present

in the resulting waveform. Signals not related to the signal source

(ECG) are eliminated through this process.

Figure 2. Heartbeat evoked potentials.

This figure shows an example of typical heartbeat evoked

potentials. In this example, 450 averages were used. The pulse

wave is also shown, indicating the timing relationship of the

blood pressure wave reaching the brain. In this example, there

is less synchronized alpha activity immediately after the R-

wave. The time range between 10 and 250 milliseconds is

when afferent signals from the heart are impinging upon the

brain, and the alpha desynchronization indicates the processing

of this information. Increased alpha activity can be clearly seen

later in the waveforms, starting at around the time the blood

pressure wave reaches the brain.

© Copyright 2003 Institute of HeartMath

3

when subjects focused their attention on the per-

ception of their heartbeat, the synchrony in the

preventricular region of the heartbeat evoked poten-

tial increased. From this they concluded that

preventricular synchrony may reflect an energetic

mechanism of heart-brain communication, while

postventricular synchrony most likely reflects direct

physiological mechanisms.8

The Heart’s Role in Emotion

Throughout the 1990s, the view that the brain

and body work in conjunction in order for percep-

tions, thoughts, and emotions to emerge gained mo-

mentum and is now widely accepted. The brain is an

analog processor that relates whole concepts (pat-

terns) to one another and looks for similarities, dif-

ferences, or relationships between them, in contrast

to a digital computer that assembles thoughts and

feelings from bits of data. This new understanding of

how the brain functions has challenged several

longstanding assumptions about the nature of emo-

tions. While it was formerly maintained that emo-

tions originated only in the brain, we now recognize

that emotions can be more accurately described as a

product of the brain and body acting in concert.

Moreover, evidence suggests that of the bodily or-

gans, the heart may play a particularly important

role in emotional experience. Research in the rela-

tively new discipline of neurocardiology has con-

firmed that the heart is a sensory organ and acts as a

sophisticated information encoding and processing

center that enables it to learn, remember, and make

independent functional decisions that do not involve

the cerebral cortex.9 Additionally, numerous experi-

ments have demonstrated that patterns of cardiac

afferent neurological input to the brain not only af-

fect autonomic regulatory centers, but also influence

higher brain centers involved in perception and emo-

tional processing.10-13

Heart rate variability (HRV), derived from the

ECG, is a measure of the naturally occurring beat-

to-beat changes in heart rate that has proven to be

invaluable in studying the physiology of emotions.

The analysis of HRV, or heart rhythms, provides a

powerful, noninvasive measure of neurocardiac func-

tion that reflects heart-brain interactions and auto-

nomic nervous system dynamics, which are particu-

larly sensitive to changes in emotional states.

14, 15

Our

research, along with that of others, suggests that there

is an important link between emotions and changes

in the patterns of both efferent (descending) and af-

ferent (ascending) autonomic activity.

12, 14, 16-18

These

changes in autonomic activity are associated with

dramatic changes in the pattern of the heart’s rhythm

that often occur without any change in the amount

of heart rate variability. Specifically, we have found

that during the experience of negative emotions such

as anger, frustration, or anxiety, heart rhythms be-

come more erratic and disordered, indicating less

synchronization in the reciprocal action that ensues

between the parasympathetic and sympathetic

branches of the autonomic nervous system (ANS).

14,

16

In contrast, sustained positive emotions, such as

appreciation, love, or compassion, are associated with

highly ordered or coherent patterns in the heart

rhythms, reflecting greater synchronization between

the two branches of the ANS, and a shift in autonomic

balance toward increased parasympathetic activity

14,

16, 17, 19

(Figure 3).

Physiological Coherence

Based on these findings, we have introduced

the term physiological coherence to describe a num-

ber of related physiological phenomena associated

Figure 3. Emotions are reflected in heart rhythm patterns.

Real-time heart rate variability (heart rhythm) pattern of an

individual making an intentional shift from a self-induced state

of frustration to a genuine feeling of appreciation by using a

positive emotion refocusing exercise known as the Freeze-

Frame technique. It is of note that when the recording is

analyzed statistically, the

amount

of heart rate variability is

found to remain virtually the same during the two different

emotional states; however, the

pattern

of the heart rhythm

changes distinctly. Note the immediate shift from an erratic,

disordered heart rhythm pattern associated with frustration to

a smooth, harmonious, sine wave-like (coherent) pattern as

the individual uses the positive emotion refocusing technique

and self-generates a heartfelt feeling of appreciation.

© Copyright 2003 Institute of HeartMath

4

with more ordered and harmonious interactions

among the body’s systems.20

The term coherence has several related defi-

nitions. A common definition of the term is “the

quality of being logically integrated, consistent, and

intelligible,” as in a coherent argument. In this con-

text, thoughts and emotional states can be consid-

ered “coherent” or “incoherent.” Importantly, how-

ever, these associations are not merely metaphori-

cal, as different emotions are in fact associated with

different degrees of coherence in the oscillatory

rhythms generated by the body’s various systems.

The term “coherence” is used in physics to

describe the ordered or constructive distribution of

power within a waveform. The more stable the fre-

quency and shape of the waveform, the higher the

coherence. An example of a coherent wave is the

sine wave. The term autocoherence is used to de-

note this kind of coherence. In physiological systems,

this type of coherence describes the degree of order

and stability in the rhythmic activity generated by a

single oscillatory system. Methodology for comput-

ing coherence has been published elsewhere.14

Coherence also describes two or more waves

that are either phase- or frequency-locked. In physi-

ology, coherence is used to describe a functional

mode in which two or more of the body’s oscillatory

systems, such as respiration and heart rhythms, be-

come entrained and oscillate at the same frequency.

The term cross-coherence is used to specify this type

of coherence.

All the above definitions apply to the study of

both emotional physiology and bioelectromagnetism.

We have found that positive emotions are associated

with a higher degree of coherence within the heart’s

rhythmic activity (autocoherence) as well as in-

creased coherence between different oscillatory sys-

tems (cross-coherence/entrainment).14, 20 Typically,

entrainment is observed between heart rhythms,

respiratory rhythms, and blood pressure oscillations;

however, other biological oscillators, including very

low frequency brain rhythms, craniosacral rhythms,

electrical potentials measured across the skin, and,

most likely, rhythms in the digestive system, can also

become entrained.20

We have also demonstrated that physiological

coherence is associated with increased synchroni-

zation between the heartbeat (ECG) and alpha

rhythms in the EEG. In experiments measuring

heartbeat evoked potentials, we found that the brain’s

alpha activity (8-12 hertz frequency range) is natu-

rally synchronized to the cardiac cycle. However,

when subjects used a positive emotion refocusing

technique to consciously self-generate feelings of

appreciation, their heart rhythm coherence signifi-

cantly increased, as did the ratio of the alpha rhythm

that was synchronized to the heart.20, 21

Another related phenomenon associated with

physiological coherence is resonance. In physics,

resonance refers to a phenomenon whereby an un-

usually large vibration is produced in a system in

response to a stimulus whose frequency is identical

or nearly identical to the natural vibratory frequency

of the system. The frequency of the vibration pro-

duced in such a state is said to be the resonant fre-

quency of the system. When the human system is

operating in the coherent mode, increased synchro-

nization occurs between the sympathetic and para-

sympathetic branches of the ANS, and entrainment

between the heart rhythms, respiration and blood

pressure oscillations is observed. This occurs because

these oscillatory subsystems are all vibrating at the

resonant frequency of the system. Most models show

that the resonant frequency of the human cardio-

vascular system is determined by the feedback loops

between the heart and brain.22, 23 In humans and in

many animals, the resonant frequency is approxi-

mately 0.1 hertz, which is equivalent to a 10-second

rhythm.

In summary, we use coherence as an umbrella

term to describe a physiological mode that encom-

passes entrainment, resonance, and synchroniza-

tion—distinct but related phenomena, all of which

emerge from the harmonious activity and interac-

tions of the body’s subsystems. Correlates of physi-

ological coherence include: increased synchroniza-

tion between the two branches of the ANS, a shift in

autonomic balance toward increased parasympa-

thetic activity, increased heart-brain synchroniza-

tion, increased vascular resonance, and entrainment

between diverse physiological oscillatory systems.

The coherent mode is reflected by a smooth, sine

wave-like pattern in the heart rhythms (heart rhythm

coherence) and a narrow-band, high-amplitude peak

in the low frequency range of the heart rate variabil-

ity power spectrum, at a frequency of about 0.1 hertz.

© Copyright 2003 Institute of HeartMath

5

Benefits of Coherence

Coherence confers a number of benefits to the

system in terms of both physiological and psycho-

logical functioning. At the physiological level, there

is increased efficiency in fluid exchange, filtration,

and absorption between the capillaries and tissues;

increased ability of the cardiovascular system to adapt

to circulatory demands; and increased temporal syn-

chronization of cells throughout the body.

24, 25

This

results in increased system-wide energy efficiency and

conservation of metabolic energy. These observations

support the link between positive emotions and in-

creased physiological efficiency that may partially

explain the growing number of documented correla-

tions between positive emotions, improved health,

and increased longevity.

26-28

We have also shown that

practicing certain techniques that increase physiologi-

cal coherence is associated with both short-term and

long-term improvement in several objective health-

related measures, including enhanced humoral im-

munity

29, 30

and an increased DHEA/cortisol ratio.

17

Increased physiological coherence is similarly

associated with psychological benefits, including

improvements in cognitive performance and mental

clarity as well as increased emotional stability and

well-being.20, 31 Studies conducted in diverse popula-

tions have documented significant reductions in

stress and negative affect and increases in positive

mood and attitudes in individuals using coherence-

building techniques.17, 19, 29, 31, 32

Improvements in clinical status, emotional

well-being and quality of life have also been demon-

strated in various medical patient populations in in-

tervention programs using coherence-building ap-

proaches. For example, significant blood pressure

reductions have been demonstrated in individuals

with hypertension;33 improved functional capacity

and reduced depression in congestive heart failure

patients;34 improved psychological health and qual-

ity of life in patients with diabetes;35 and improve-

ments in asthma.36 Another study reported reduc-

tions in pathological symptoms and anxiety and sig-

nificant improvements in positive affect, physical

vitality, and general well-being in individuals with

HIV infection and AIDS.37

Additionally, patient case history data provided

by numerous health care professionals report sub-

stantial improvements in health and psychological

status and frequent reductions in medication require-

ments in patients with such medical conditions as

cardiac arrhythmias, chronic fatigue, environmen-

tal sensitivity, fibromyalgia, and chronic pain.38 Fi-

nally, techniques that increase physiological coher-

ence have been used effectively by mental health

professionals in the treatment of emotional disor-

ders, including anxiety, depression, panic disorder,

and post-traumatic stress disorder.38

Drivers of Physiological Coherence

Although physiological coherence is a natural

state that can occur spontaneously during sleep and

deep relaxation, sustained episodes during normal

daily activities are generally rare. While specific

rhythmic breathing methods can induce coherence

for brief periods, cognitively directed, paced breath-

ing is difficult for many people to maintain. On the

other hand, our findings indicate that individuals can

produce extended periods of physiological coherence

by actively generating and sustaining a feeling of ap-

preciation or other positive emotions. Sincere posi-

tive feelings appear to excite the system at its reso-

nant frequency, allowing the coherent mode to

emerge naturally. This typically makes it easier for

people to sustain a positive emotion for much longer

periods, thus facilitating the process of establishing

and reinforcing coherent patterns in the neural ar-

chitecture as the familiar reference. Once a new pat-

tern is established, the brain strives to maintain a

match with the new program, thus increasing the

probability of maintaining coherence and reducing

stress, even during challenging situations.12

Doc Childre, founder of the Institute of Heart-

Math, has developed a number of practical positive

emotion refocusing and emotional restructuring tech-

niques that allow people to quickly self-generate co-

herence at will.39, 40 Known as the HeartMath system,

these techniques utilize the heart as a point of entry

into the psychophysiological networks that connect

the physiological, mental, and emotional systems.

In essence, because the heart is a primary generator

of rhythmic neural and energetic patterns in the

body—influencing brain processes that control the

ANS, cognitive function and emotion—it provides an

access point from which system-wide dynamics can

be quickly and profoundly affected. Research stud-

ies and the experience of numerous health care pro-

© Copyright 2003 Institute of HeartMath

6

fessionals indicate that HeartMath coherence-build-

ing techniques are easily learned, have a high rate of

compliance, and are highly adaptable to a wide range

of demographic groups.

Promoting Physiological Coherence Through Heart

Rhythm Coherence Feedback Training

Used in conjunction with positive emotion-

based coherence-building techniques, heart rhythm

feedback training can be a powerful tool to assist

people in learning how to self-generate increased

physiological coherence.41 We have developed a por-

table heart rhythm monitoring and feedback system

that enables physiological coherence to be objectively

monitored and quantified. Known as the Freeze-

Framer® coherence-building system (HeartMath

LLC, Boulder Creek, CA), this interactive hardware/

software system monitors and displays individuals’

heart rate variability patterns in real time as they

practice the positive emotion refocusing and emo-

tional restructuring techniques taught in an on-line

tutorial. Using a fingertip sensor to record the pulse

wave, the Freeze-Framer plots changes in heart rate

on a beat-to-beat basis. As people practice the co-

herence-building techniques, they can readily see and

experience the changes in their heart rhythm pat-

terns, which generally become more ordered,

smoother, and more sine wave-like as they experi-

ence positive emotions. This process reinforces the

natural association between the physiological coher-

ence mode and positive feelings. The software also

analyzes the heart rhythm patterns for coherence

level, which is fed back to the user as an accumu-

lated numerical score or success in playing one of

three on-screen games designed to reinforce the co-

herence-building skills. The real-time physiological

feedback essentially takes the guesswork and ran-

domness out of the process of self-inducing a coher-

ent state, resulting in greater consistency, focus, and

effectiveness in shifting to a beneficial psychophysi-

ological mode.

Heart rhythm coherence feedback training has

been successfully used in clinical settings by physi-

cians, mental health professionals and neurofeedback

therapists to facilitate health improvements in pa-

tients with numerous physical and psychological dis-

orders. It is also increasingly being utilized in corpo-

rate, law enforcement, and educational settings to

enhance physical and emotional health and improve

performance.

Heart Rhythms and Bioelectromagnetism

The first biomagnetic signal was demonstrated

in 1963 by Gerhard Baule and Richard McFee in a

magnetocardiogram (MCG) that used magnetic in-

duction coils to detect fields generated by the hu-

man heart.42 A remarkable increase in the sensitiv-

ity of biomagnetic measurements was achieved with

the introduction of the Superconducting Quantum

Interference Device (SQUID) in the early 1970s, and

the ECG and MCG have since been shown to closely

parallel one another.43

The heart generates a series of electromagnetic

pulses in which the time interval between each beat

varies in a complex manner. These pulsing waves of

electromagnetic energy create fields within fields and

give rise to interference patterns when they interact

with magnetically polarizable tissues and substances.

Figure 4 shows two different power spectra

derived from an average of 12 individual 10-second

epochs of ECG data recorded during differing psy-

chophysiological modes. The plot on the left was

produced while the subject was in a state of deep

appreciation, whereas the plot on the right was gen-

erated while the subject experienced recalled feel-

ings of anger. The difference in the patterns, and thus

the information they contain, can be clearly seen.

There is a direct correlation between the patterns in

the heart rate variability rhythm and the frequency

patterns in the spectrum of the ECG or MCG. Ex-

periments such as these indicate that psychophysi-

ological information can be encoded into the elec-

tromagnetic fields produced by the heart.14, 44

Bioelectromagnetic Communication Between People

The human body is replete with mechanisms

for detecting its external environment. Sense organs,

the most obvious example, are specifically geared to

react to touch, temperature, select ranges of light and

sound waves, etc. These organs are acutely sensitive

to external stimuli. The nose, for example, can de-

tect one molecule of gas, while a cell in the retina of

the eye can detect a single photon of light; and if the

ear were any more sensitive, it would pick up the

sound of the random vibrations of its own molecules.

45

© Copyright 2003 Institute of HeartMath

7

The interaction between two human beings—

for example, the consultation between a patient and

her clinician—is a very sophisticated dance that in-

volves many subtle factors. Most people tend to think

of communication solely in terms of overt signals

expressed through facial movements, voice qualities,

gestures and body movements. However, evidence

now supports the perspective that a subtle yet influ-

ential electromagnetic or “energetic” communica-

tion system operates just below our conscious level

of awareness. The following section will discuss data

suggesting that this energetic system contributes to

the “magnetic” attractions or repulsions that occur

between individuals. It is also quite possible that

these energetic interactions can affect the therapeu-

tic process.

The concept of energy or information exchange

between individuals is central to many of the East-

ern healing arts, but its acceptance in Western medi-

cine has been hampered by the lack of a plausible

mechanism to explain the nature of this “energy in-

formation” or how it is communicated. However,

numerous studies investigating the effects of heal-

ers, Therapeutic Touch practitioners, and other in-

dividuals have demonstrated a wide range of signifi-

cant effects including the influence of “energetic”

approaches on wound healing rates,46, 47 pain,48, 49

hemoglobin levels,50 conformational changes of DNA

and water structure,51-52 as well as psychological

states.53 Although these reports show beneficial re-

sults, they have been largely ignored because of the

lack of any scientific rationale to explain how the

effects are achieved.

Physiological Linkage and Empathy

The ability to sense what other people are feel-

ing is an important factor in allowing us to connect

or communicate effectively with others. The smooth-

ness or flow in any social interaction depends to a

great extent on the establishment of a spontaneous

entrainment or linkage between individuals. When

people are engaged in deep conversation, they begin

to fall into a subtle dance, synchronizing their move-

ments and postures, vocal pitch, speaking rates, and

length of pauses between responses,54 and, as we are

now discovering, important aspects of their physiol-

ogy can also become linked and entrained.

Several studies have investigated different

types of physiological synchronization or entrain-

ment between individuals during empathetic mo-

ments or between clinician and patient during thera-

peutic sessions. One study by Levenson and Gottman

at the University of California at Berkeley looked at

Figure 4. ECG spectra during different emotional states.

The above graphs are the average power spectra of 12 individual 10-second epochs of ECG data, which reflect information patterns

contained in the electromagnetic field radiated by the heart. The lefthand graph is an example of a spectrum obtained during a period

of high heart rhythm coherence generated during a sustained heartfelt experience of appreciation. The graph on the right depicts a

spectrum associated with a disordered heart rhythm generated during feelings of anger.

© Copyright 2003 Institute of HeartMath

8

physiological synchronization in married couples

during empathetic interactions. Researchers exam-

ined couples’ physiological responses during two dis-

cussions: a neutral “How was your day?” conversa-

tion, to establish a baseline, and a second conversa-

tion containing more emotional content in which the

couples were asked to spend fifteen minutes discuss-

ing something about which they disagreed. After the

disagreement, one partner was asked to leave the

room while the other stayed to watch a replay of the

talk and identify portions of the dialogue where he

or she was actually empathizing but did not express

it. Both spouses individually engaged in this proce-

dure. Levenson was then able to identify those seg-

ments of the video where empathy occurred and

match the empathetic response to physiological re-

sponses in both partners. He found that in partners

who were adept at empathizing, their physiology

mimicked their partner’s while they empathized. If

the heart rate of one went up, so did the heart rate

of the other; if the heart rate slowed, so did that of

the empathic spouse.55 Other studies observing the

psychophysiology of married couples while interact-

ing were able to predict the probability of divorce.56

Although studies that have examined physi-

ological linkages between therapists and patients

have suffered from methodological challenges, they

do support a tendency to autonomic attunement

during periods of empathy between the therapist and

patient.57 Dana Redington, a psychophysiologist at

the University of California, San Francisco, analyzed

heart rate variability patterns during therapist-pa-

tient interactions using a nonlinear dynamics ap-

proach. Redington and colleagues used phase space

maps to plot changes in the beat-to-beat heart rate

of both the therapist and patient during psycho-

therapy sessions. They found that the trajectories in

the therapist’s patterns often coincided with the

patient’s during moments when the therapist expe-

rienced strong feelings of empathy for the patient.58

Carl Marci at Harvard University found evidence of

a more direct linkage between patients and thera-

pists using skin conductance measures. During ses-

sions of psychodynamic psychotherapy, Marci ob-

served a quantifiable fluctuation and entrainment in

the pattern of physiological linkage within patient-

therapist dyads, which was related to patient per-

ception of the therapist’s empathy. In addition, the

preliminary results of his studies indicate that dur-

ing periods of low physiological linkage there are

fewer empathetic comments, more incidents of in-

correct interpretations, less shared affect, and fewer

shared behavioral responses when compared to epi-

sodes of high physiological linkage.59

Cardioelectromagnetic Communication

An important step in testing our hypothesis

that the heart’s electromagnetic field could transmit

signals between people was to determine if the field

and the information modulated within it could be

detected by other individuals.

In conducting these experiments, the question

being asked was straightforward. Namely, can the

electromagnetic field generated by the heart of one

individual be detected in physiologically relevant

ways in another person, and if so does it have any

discernible biological effects? To investigate these

possibilities, we used signal-averaging techniques to

detect signals that were synchronous with the peak

of the R-wave of one subject’s ECG in recordings of

another subject’s electroencephalogram (EEG) or

brain waves. My colleagues and I have performed

numerous experiments in our laboratory over a pe-

riod of several years using these techniques,60 and

several examples are included below to illustrate

some of these findings. In the majority of these ex-

periments, subjects were seated in comfortable, high-

back chairs to minimize postural changes with the

positive ECG electrode located on the side at the

left sixth rib and referenced to the right supraclav-

icular fossa according to the International 10-20 sys-

tem. The ECG and EEG were recorded from both

subjects simultaneously so that the data (typically

sampled at 256 hertz or higher) could be analyzed

for simultaneous signal detection in both.

To clarify the direction in which the signal flow

was analyzed, the subject whose ECG R-wave was

used as the time reference for the signal averaging

procedure is referred to as the “signal source,” or

simply “source.” The subject whose EEG was ana-

lyzed for the registration of the source’s ECG signal

is referred to as the “signal receiver,” or simply “re-

ceiver.” The number of averages used in the major-

ity of the experiments was 250 ECG cycles (~ 4 min-

utes). The subjects did not consciously intend to send

or receive a signal and, in most cases, were unaware

of the true purpose of the experiments. The results

© Copyright 2003 Institute of HeartMath

9

of these experiments have led us to conclude that

the nervous system acts as an antenna, which is tuned

to and responds to the magnetic fields produced by

the hearts of other individuals. My colleagues and I

call this energetic information exchange

cardioelectromagnetic communication and believe

it to be an innate ability that heightens awareness

and mediates important aspects of true empathy and

sensitivity to others. Furthermore, we have observed

that this energetic communication ability can be

enhanced, resulting in a much deeper level of non-

verbal communication, understanding, and connec-

tion between people. We also propose that this type

of energetic communication between individuals may

play a role in therapeutic interactions between cli-

nicians and patients that has the potential to pro-

mote the healing process.

From an electrophysiological perspective, it

appears that sensitivity to this form of energetic com-

munication between individuals is related to the abil-

ity to be emotionally and physiologically coherent.

The data indicate that when individuals are in the

coherent mode, they are more sensitive to receiving

information contained in the fields generated by oth-

ers. In addition, during physiological coherence, in-

ternal systems are more stable, function more effi-

ciently, and radiate electromagnetic fields contain-

ing a more coherent structure.14

The Electricity of Touch

The first step was to determine if the ECG sig-

nal of one person could be detected in another

individual’s EEG during physical contact. For these

experiments we seated pairs of subjects 4 feet apart,

during which time they were simultaneously moni-

tored. An initial 10-minute baseline period (no physi-

cal contact) was followed by a 5-minute period in

which subjects remained seated but reached out and

held the hand of the other person (like shaking hands).

Figure 5 shows a typical example of the results.

Prior to holding hands, there was no indication

that Subject 1’s ECG signals were detected in Subject

2’s EEG. However, upon holding hands, Subject 1’s

ECG could be clearly detected in Subject 2’s EEG at

all monitored locations. While in most pairs a clear

0 0.125 0.25 0.375 0.5 0.625 0.75

-2

-1

0

1

2

Seconds

-40

-30

-20

-10

0

10

20

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40

0 0.125 0.25 0.375 0.5 0.625 0.75

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-1

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The Electricity of Touch

Heartbeat Signal Averaged Waveforms

Subject B - Heartbeat (ECG)

Holding Hands

Subject A - Brain Wave (EEG)

No Contact

Subject B - Heartbeat (ECG)

Subject A - Brain Wave (EEG)

µ Volts

m Volts

µ Volts

m Volts

Figure 5.

Signal averaged waveforms showing the detection of electromagnetic energy generated by the source’s heart in the receiving

subject’s EEG. The baseline recording (left side) is from a 10-minute period during which time the subjects were seated 4 feet apart

without physical contact. The right column shows the recording from the 5-minute period during which the subjects held hands.

The EEG data shown here were recorded from the C3 site of the EEG.

© Copyright 2003 Institute of HeartMath

10

signal transfer between the two subjects was measur-

able in one direction, it was only observed in both

directions simultaneously in about 30 percent of the

pairs (i.e., Subject 2’s ECG could be detected in Sub-

ject 1’s EEG at the same time that Subject 1’s ECG

was detectable in Subject 2’s EEG). From other ex-

periments we have concluded that this phenomenon

is not related to gender or amplitude of the ECG sig-

nal. As shown later, an important variable appears to

be the degree of physiological coherence maintained.

After demonstrating that the ECG from one

individual could be detected in another’s EEG dur-

ing physical contact, we completed a series of ex-

periments to determine if the signal was transferred

via electrical conduction through the skin alone or

if it was also radiated. In one set of experiments sub-

jects were recorded holding hands under two sets of

conditions: barehanded and wearing form-fitting,

latex lab gloves. The ECG signal of one subject could

be clearly detected in the EEG of the other subject

even when they were wearing the gloves; however,

the signal amplitude was reduced approximately ten-

fold. This suggests that while a significant degree of

the signal transfer occurs through skin conduction,

the signal is also radiated or capacitively coupled

between individuals. When conductive gel was used

to decrease skin-to-skin contact resistance, the sig-

nal amplitude was unaffected. For additional detail,

the protocols and data from these and related ex-

periments are described elsewhere.60

We also conducted several experiments to de-

termine if the transfer of cardiac energy and infor-

mation is affected by the orientation of the subjects’

hand-holding (i.e., source’s left hand holding

receiver’s right hand vs. source’s right hand holding

receiver’s left hand, etc.). The subjects were in-

structed to hold hands in each of the four possible

orientations for 5 minutes. Since we only performed

this experiment with three subject pairs, the results

should be interpreted with a degree of caution; how-

ever, we did find that consistent and measurable dif-

ferences could be observed. The source’s ECG ap-

peared with the largest amplitude in the receiver’s

EEG when the receiver’s right hand was held by ei-

ther the source’s left or right hand. When the

receiver’s left hand was held by the source’s right

hand, the signal appeared at a lower amplitude. Fi-

nally, when the receiver’s left hand was held by the

source’s left hand, the ECG signal was either very

low in amplitude or undetectable.60

The possibility exists that in some cases the sig-

nal appearing in the receiving subject’s recordings could

be the receiver’s own ECG rather than that of the other

subject. Given the signal averaging procedure em-

ployed, this could only occur if the source’s ECG was

continually and precisely synchronized with the

receiver’s ECG. To definitively rule this out, the data

in all experiments were checked for this possibility.

Simultaneously and independently, Russek and

Schwartz at the University of Arizona conducted

similar experiments in which they were also able to

demonstrate the detection of an individual’s cardiac

signal in another’s EEG recording in two people sit-

ting quietly, without physical contact.61 In a publica-

tion entitled “Energy Cardiology,” they discuss the

implications of their findings in the context of what

they call a “dynamical energy systems approach”

describing the heart as a prime generator, organizer,

and integrator of energy in the human body.62

Heart-Brain Synchronization During Nonphysical

Contact

Since the magnetic component of the field pro-

duced by the heartbeat is radiated outside the body

and can be detected several feet away with SQUID-

based magnetometers,

1

we further tested the trans-

ference of signals between subjects who were not in

physical contact. In these experiments, the subjects

were either seated side by side or facing each other at

varying distances. In some cases, we were able to de-

tect a clear QRS-shaped signal in the receiver’s EEG,

but not in others. Although the ability to obtain a clear

registration of the ECG in the other person’s EEG

declined as the distance between subjects was in-

creased, the phenomenon appears to be nonlinear. For

instance, a clear signal could be detected at a distance

of 18 inches in one session but was undetectable in

the very next trial at a distance of only 6 inches. Al-

though transmission of a clear QRS-shaped signal is

uncommon at distances over 6 inches in our experi-

ence, this does not preclude the possibility that physi-

ologically relevant information can be communicated

between people at longer distances.

Because of the apparent nonlinear nature of

the phenomenon and the growing body of data sug-

gesting that the detection of weak periodic signals

can be enhanced in biological systems via a mecha-

© Copyright 2003 Institute of HeartMath

11

nism known as stochastic resonance, we investigated

the possibility that physiological coherence may be

an important variable in determining whether the

cardiac fields are detected past the 6-inch distance.

The nonlinear stochastic resonance model predicts

that under certain circumstances, very weak coher-

ent electromagnetic signals are detectable by biologi-

cal systems and can have significant biological ef-

fects.63-66 Stochastic resonance will be discussed in

more detail in a subsequent section.

Figure 6 shows the data from two subjects

seated facing one another at a distance of 5 feet, with

no physical contact. The subjects were asked to use

the Heart Lock-In technique,39, 40 an emotional re-

structuring exercise that has been demonstrated to

produce sustained states of physiological coherence

when properly applied.17 There was no intention to

“send energy” and participants were not aware of

the purpose of the experiment. The top three traces

show the signal-averaged waveforms derived from

the EEG locations along the medial line of the head.

Note that in this example, the signal averaged

waveforms do not contain any semblance of the QRS

complex shape as seen in the physical contact ex-

periments; rather they reveal the occurrence of an

alpha wave synchronization in the EEG of one sub-

ject that is precisely timed to the R-wave of the other

subject’s ECG. Power spectrum analysis of the sig-

nal averaged EEG waveforms was used to verify that

it is the alpha rhythm that is synchronized to the

other person’s heart. This alpha synchronization does

not imply that there is increased alpha activity, but

it does show that the existing alpha rhythm is able

to synchronize to extremely weak external electro-

magnetic fields such as those produced by another

person’s heart. It is well known that the alpha rhythm

can synchronize to an external stimulus such as

sound or light flashes, but the ability to synchronize

to such a subtle electromagnetic signal is surprising.

As mentioned, there is also a significant ratio of al-

pha activity that is synchronized to one’s own heart-

beat, and the amount of this synchronized alpha ac-

tivity is significantly increased during periods of

physiological coherence.20, 21

Figure 7 shows an overlay plot of one of Sub-

ject 2’s signal averaged EEG traces and Subject 1’s

signal averaged ECG. This view shows an amazing

degree of synchronization between the EEG of Sub-

ject 2 and Subject 1’s heart. These data show that it

is possible for the magnetic signals radiated by the

heart of one individual to influence the brain rhythms

of another. In addition, this phenomenon can occur

at conversational distances. As yet, we have not

tested this effect at distances greater than 5 feet.

Figure 6. Heart-brain synchronization between two people.

The top three traces are Subject 2’s signal averaged EEG

waveforms, which are synchronized to the R-wave of Subject

1’s ECG. The lower plot shows Subject 2’s heart rate variability

pattern, which was coherent throughout the majority of the

record. The two subjects were seated at a conversational distance

without physical contact.

Figure 7. Overlay of signal averaged EEG and ECG.

This graph is an overlay plot of the same EEG and ECG data

shown in Figure 6. Note the similarity of the wave shapes,

indicating a high degree of synchronization.

© Copyright 2003 Institute of HeartMath

12

Figure 8 shows the data from the same two

subjects during the same time period, only it is ana-

lyzed for alpha synchronization in the opposite di-

rection (Subject 1’s EEG and Subject 2’s ECG). In

this case, we see that there is no observable syn-

chronization between Subject 1’s EEG and Subject

2’s ECG. The key difference between the data shown

in Figure 6 and Figure 8 is the high degree of physi-

ological coherence maintained by Subject 2. In other

words, the degree of coherence in the receiver’s heart

rhythms appears to determine whether his/her brain

waves synchronize to the other person’s heart.

This suggests that when one is in a physiologi-

cally coherent mode, one exhibits greater sensitiv-

ity in registering the electromagnetic signals and in-

formation patterns encoded in the fields radiated by

the hearts of other people. At first glance these data

may be mistakenly interpreted as suggesting that we

are more vulnerable to the potential negative influ-

ence of incoherent patterns radiated by those around

us. In fact, the opposite is true, because when people

are able to maintain the physiological coherence

mode, they are more internally stable and thus less

vulnerable to being negatively affected by the fields

emanating from others. It appears that it is the in-

creased internal stability and coherence that allows

for the increased sensitivity to emerge.

This fits quite well with our experience in train-

ing thousands of individuals in how to self-generate

and maintain coherence while they are listening to

others during conversation. Once individuals learn

this skill, it is a common experience that they be-

come much more attuned to other people and are

able to detect and understand the deeper meaning

behind spoken words. They are often able to sense

what someone else really wishes to communicate

even when the other person may not be clear about

that which he is attempting to say. This technique,

called Intuitive Listening, helps people to feel fully

heard and promotes greater rapport and empathy

between people.67

Our data are also relevant to Russek and

Schwartz’s findings that people who are more accus-

tomed to experiencing positive emotions such as love

and care are better receivers of cardiac signals from

others.61 In their follow-up study of 20 college stu-

dents, those who had rated themselves as having been

raised by loving parents exhibited significantly

greater registration of an experimenter’s ECG in their

EEG than others who had perceived their parents as

less loving. Our findings, which show that positive

emotions such as love, care, and appreciation are

associated with increased physiological coherence,

suggest the possibility that the subjects in Russek

and Schwartz’s study had higher ratios of physiologi-

cal coherence, which could explain the greater reg-

istration of cardiac signals.

Heart Rhythm Entrainment Between Subjects

When heart rhythms are more coherent, the

electromagnetic field that is radiated outside the body

correspondingly becomes more organized, as shown

in Figure 4. The data presented thus far indicate that

signals and information can be communicated ener-

getically between individuals, but so far have not

implied a literal entrainment of two individuals’ heart

rhythm patterns. We have found that entrainment

of heart rhythm patterns between individuals is pos-

sible, but usually occurs only under very specific

conditions. In our experience, true heart rhythm

entrainment between individuals is very rare during

Figure 8.

The top three traces are the signal averaged EEG waveforms for

Subject 1.There is no apparent synchronization of Subject 1’s

alpha rhythm to Subject 2’s ECG. The bottom plot is a sample

of Subject 1’s heart rate variability pattern, which was incoherent

throughout the majority of the record.

© Copyright 2003 Institute of HeartMath

13

normal waking states. We have found that individu-

als who have a close living or working relationship

are the best candidates for exhibiting this type of

entrainment. Figure 9 shows an example of heart

rhythm entrainment between two women who have

a close working relationship and practice coherence-

building techniques regularly. For this experiment,

they were seated 4 feet apart, and, although blind to

the data, were consciously focused on generating feel-

ings of appreciation for each other.

A more complex type of entrainment can also

occur during sleep. Although we have only looked at

couples who are in long-term stable and loving rela-

tionships, we have been surprised at the high degree

of heart rhythm synchrony observed in these couples

while they sleep. Figure 10 shows an example of a

small segment of data from one couple. These data

were recorded using an ambulatory ECG (Holter)

recorder with a modified cable harness that allowed

the concurrent recording of two individuals on the

same tape. Note how the heart rhythms simulta-

neously change in the same direction and how heart

rates converge. Throughout the recording, clear tran-

sition periods are evident in which the heart rhythms

move into greater synchronicity, maintain the en-

trainment for some time, and then drift out again.

This implies that unlike in most wakeful states, en-

trainment between the heart rhythms of individuals

can and does occur during sleep.

We have also found that a type of heart rhythm

entrainment or synchronization can occur in inter-

actions between people and their pets. Figure 10

shows the results of an experiment looking at the

heart rhythms of my son Josh (15 years old at the

time of the recording) and his dog, Mabel. Here we

used two Holter recorders, one fitted on Mabel and

the other on Josh. We synchronized the recorders

and placed Mabel in one of our labs. Josh then en-

tered the room and sat down and proceeded to con-

sciously feel feelings of love towards Mabel. Note the

synchronous shift to increased coherence in the heart

rhythms of both Josh and Mabel as Josh consciously

feels love for his pet.

40

60

80

100

120

810 830 850 870 890 910

Time

(

seconds

)

Subject A (female) Subject B (female)

Heart Rate (BPM)

Figure 9. Heart rhythm entrainment between two people.

These data were recorded while both subjects were practicing

the Heart Lock-In emotional restructuring technique and

consciously feeling appreciation for each other. It should be

emphasized that in typical waking states, entrainment between

people such as in this example is rare.

60

62

64

66

68

70

72

74

76

78

80

01:49:58 AM 01:50:58 AM 01:51:58 AM 01:52:58 A

M

Clock Time

Subject A (male) Subject B (female)

Heart Rate (BPM)

Figure 10. Heart rhythm entrainment between husband and wife during sleep.

© Copyright 2003 Institute of HeartMath

14

Influence of the Heart’s Bioelectromagnetic Field on

Cells

The idea that information can be communi-

cated between biological systems and cause an effect

in another living system is far from a new concept.

This phenomenon has been examined in many dif-

ferent biological systems. A review of this literature

is beyond the scope of this paper, but the subject has

been reviewed recently by Marilyn Schlitz, Director

of Research at the Institute of Noetic Sciences. In

her review, both intention and how it is focused (i.e.,

attitude) are considered important variables in affect-

ing outcomes.

68

Further, studies conducted in our

laboratory suggest that emotional state and the de-

gree of coherence in the electromagnetic fields pro-

duced by the heart are also important variables.

We have long suspected that one aspect of the

heart’s electromagnetic field acts as a carrier wave

for information that can affect the function of cells

in our own body as well as other biological systems

in proximity. In the early 1990s, we undertook a se-

ries of experiments to test this hypothesis. This

project evolved over several years and extended into

many types of experiments. We were able to demon-

strate that individuals can cause changes in the struc-

ture of water,

51

in cell growth rate, and in the confor-

mational state of DNA.

52

In general, we found that in

order to produce these effects in a reliable manner,

both a high degree of heart rhythm coherence and

an intention to produce a given change were critical.

Much scientific research has attempted to de-

termine the effects, if any, of electromagnetic fields

(particularly the 50 and 60-hertz fields generated by

power lines) on cells, and has yielded largely incon-

clusive results. However, comparatively little effort

has been made to understand the effects of the body’s

Figure 11. Heart rhythm patterns of a boy and his dog.

These data were obtained using ambulatory ECG (Holter) recorders fitted on both Josh, a boy, and Mabel, his pet dog. When Josh entered

the room where Mabel was waiting and consciously felt feelings of love and care towards his pet, his heart rhythms became more

coherent, and this change appears to have influenced Mabel heart rhythms, which then also became more coherent. When Josh left the

room, Mabel’s heart rhythms became much more chaotic and incoherent, suggesting separation anxiety!

© Copyright 2003 Institute of HeartMath

15

endogenous fields, those that actually comprise the

bioelectromagnetic environment in which our cells

are continuously bathed. The most consistent and

strongest source of an endogenous electromagnetic

field is of course the heart.

In order to test the hypothesis that the elec-

tromagnetic field generated by the heart may have

direct effects at the cellular level, we performed a

series of cell culture experiments in which we ex-

posed several different cell lines to simulated heart

fields. To do this, we first acquired ECG data at a 10-

kilohertz sample rate from people in various emo-

tional states, generating correspondingly different

heart rhythm patterns. We then used a digital-to-

analog converter to recreate these ECG signals,

which were fed into a specially built amplifier that

could accurately recreate the low frequency portions

of the ECG along with the higher frequencies. The

output of the amplifier was used to drive a coil in

which cell cultures were placed. For the experiment

described here, a 2-inch diameter solenoid coil 15

inches high was placed vertically inside a 5% carbon

dioxide incubator. Human fibroblasts (skin cells)

were placed in 35-millimeter petri dishes inside the

center section of the coils where the field was uni-

form. Typically, 10 individual petri dishes, each con-

taining the same number of cells, were placed inside

the coils. Identical cells were placed in a mock coil

in a separate incubator and served as controls for

each experiment. The field strength to which the cells

in the human body are exposed from a normal heart-

beat was determined. The output of the amplifier

was adjusted so that the cells placed in the coil were

exposed to approximately the same field strength as

they would be in the body. While the cells were grow-

ing in the incubator over a 6-day period, they were

continuously exposed to the ECG signals.

After exposure, the growth rates of the cells in

the active and control coils were measured using a

colorimetric staining assay. After many trials and

variations of this basic experiment, we found that fi-

broblast cells exposed to the heart’s field exhibited a

mean increase in growth rate of 20% as compared to

the controls. We also performed several trials in which

we exposed the same type cells to a 60-hertz field of

the same average magnitude of the heart’s field. In

this case, there was no significant change in the growth

rate when compared to the controls. We did find a

slight difference in the growth rate in cells exposed to

coherent versus incoherent ECG signals. The coher-

ent field yielded a higher growth rate; however, this

effect did not reach statistical significance in this set

of experiments. Thus, it appears that the presence or

absence of a cardiac field was the primary variable to

influence growth rate in these experiments.

One particularly intriguing experiment was

performed in which healthy human fibroblasts and

human fibrosarcoma cells (tumor cells from the same

lineage) were both exposed to the same coherent

ECG signal. We found that the growth of the healthy

cells was facilitated by 20%, as expected, while the

growth of the tumor cells was inhibited by 20%.

These results may relate to work conducted in Ger-

many by Ulrich Randoll with cancer patients. He has

found that by monitoring a patient’s own heartbeat

and using it to trigger the application of an exter-

nally applied pulsed field, he has been able to suc-

cessfully treat a number of patients with advanced

carcinomas.69 Dr. Randoll’s therapeutic goal is to “re-

generate and stabilize the basic autonomic rhythm

of the organism.” He has also used ultrastructural

tomographic images of living cells to visualize tem-

poral rhythms in the structural elements at the sub-

cellular level. This technique shows clear differences

in the temporal rhythms of cancer cells as compared

to normal cells.70 He is convinced that his treatments

are helping to restore the normal pattern of activity

at the cellular level, which facilitates recovery from

disease, and believes that the rhythm of the heart

and the field it produces are the key to this healing

process.

Mechanisms of Weak Electromagnetic Field Effects in

Biological Systems

A biological response to an external field (sig-

nal) implies that the signal has caused changes in

the system greater than those caused by random fluc-

tuating events, or noise. Theoretical estimates of the

limitations on the detection of very small signals by

sensory systems imposed by the presence of ther-

mal noise (thermal noise limit) were traditionally

made using linear approximation under the assump-

tion that the system is in a state of equilibrium.71

Traditional linear theory predicted that weak, ex-

tremely low frequency electromagnetic fields, such

as that radiated from the human heart, could not

generate enough energy to overcome the thermal

© Copyright 2003 Institute of HeartMath

16

noise limit and thus affect biological systems. How-

ever, more recently it has been recognized that a

linear and equilibrium approach is not appropriate

for modeling biological systems, which are intrinsi-

cally nonlinear, nonequilibrium, and noisy. A num-

ber of experiments have revealed cellular responses

to electromagnetic field magnitudes far smaller than

the theoretical estimates arrived at by linear model-

ing for the minimum field strength required to over-

come the thermal noise limit in these systems.72

It has been proposed that this discrepancy can

in part be accounted for by biological cells’ capacity

to rectify and essentially signal average weak oscil-

lating electromagnetic fields through field-induced

variation in the catalytic activity of membrane-asso-

ciated enzymes or in the conformation of membrane

channel proteins.66, 72 In addition to signal averaging

by the cells, it has also been established that the noise

in biological systems can play a constructive role in

the detection of weak periodic signals via a mecha-

nism known as stochastic resonance.63-66 Stochasm

is a Greek word that describes a system that is ran-

dom but purposeful. In essence, stochastic resonance

is a nonlinear cooperative effect in which a weak,

normally sub-threshold periodic (coherent) stimu-

lus entrains ambient noise, resulting in the periodic

signal becoming greatly enhanced and able to pro-

duce large-scale effects. The signature of stochastic

resonance is noted by the signal-to-noise ratio in the

system rising to a maximum at some optimal noise

intensity, corresponding to the maximum coopera-

tion between the signal and the noise. Essentially,

the noise acts to boost a coherent, sub-threshold sig-

nal to a level above the threshold value, enabling it

to generate measurable effects. Stochastic resonance

is now known to occur in a wide range of biological

systems and processes, including sensory transduc-

tion, neural signal processing, oscillating chemical

reactions,63, 64 and intracellular calcium signaling.73

In addition, coherent electromagnetic fields have

been shown to produce substantially greater effects

than incoherent signals on enzymatic pathways, such

as the ornithine decarboxylase pathway.74 Remark-

ably, experimental studies have documented effects

of subthermal, coherent signals in different biologi-

cal systems for signal amplitudes as small a one-tenth

or even one-hundredth the amplitude of the random

noise component.75-77 As a weak signal becomes more

coherent, the greater its capacity becomes to entrain

ambient noise and thus produce significant effects.

Thus, cellular signal averaging and nonlinear

stochastic resonance provide potential mechanisms

by which increased heart rhythm coherence may pro-

duce significant biological effects, both within and

between people. For example, through such mecha-

nisms, the consistent self-induction of sustained states

of physiological coherence by an individual may give

rise to changes at the cellular level that may enhance

health and healing. Alternatively, a clinician’s coher-

ent cardiac field, which is detected by a patient, may

be amplified in such a way as to positively affect the

patient’s physiology. The importance of signal coher-

ence in this model also suggests that further atten-

tion be given to the contribution of heartfelt positive

emotions and attitudes, as drivers of coherence, in

the healing process. It is possible that the generation

of physiological coherence and biological effects pro-

duced by this beneficial mode may in part explain

the observed relationship between positive emotions

and favorable health outcomes, as well as the em-

phasis that many therapeutic practices place on the

development of a mutually caring relationship be-

tween practitioner and patient.

60

Furthermore, it is

likely that the therapeutic value of interventions that

facilitate the generation and maintenance of sustained

feelings of appreciation, care, and love may derive in

part from bioelectromagnetically-mediated effects on

cellular physiology.

Conclusions and Implications for Clinical Practice

Bioelectromagnetic communication is a real

phenomenon that has numerous implications for

physical, mental, and emotional health. This paper

has focused on the proposition that increasing the

coherence within and between the body’s endogenous

bioelectromagnetic systems can increase physiologi-

cal and metabolic energy efficiency, promote men-

tal and emotional stability, and provide a variety of

health rewards. It is further proposed that many of

the benefits of increased physiological coherence will

ultimately prove to be mediated by processes and

interactions occurring at the electromagnetic or en-

ergetic level of the organism.

With the many physiological and psychologi-

cal benefits that increased coherence appears to of-

fer, helping patients learn to self-generate and sus-

tain this psychophysiological mode with increased

© Copyright 2003 Institute of HeartMath

17

consistency in their day-to-day lives provides a new

strategy for clinicians to assist their patients on

multiple levels. There are several straightforward

ways to help patients increase their physiological

coherence. Teaching and guiding them in the prac-

tice of positive emotion refocusing and emotional

restructuring techniques in conjunction with heart

rhythm feedback has proved to be a simple and cost-

effective approach to improving patient outcomes.

These coherence-building methods are not only ef-

fective therapeutic tools in and of themselves, but

by increasing synchronization and harmony among

the body’s internal systems, may also help increase

a patient’s physiological receptivity to the therapeu-

tic effects of other treatments.

Coherence-building approaches may also help

health care practitioners increase their effectiveness

in working with patients. In self-generating a state

of physiological coherence, the clinician has the po-

tential to facilitate the healing process by establish-

ing a coherent pattern in the subtle electromagnetic

environment to which patients are exposed. Since

even very weak coherent signals have been found to

give rise to significant effects in biological systems,

it is possible that such coherent heart fields may pro-

vide unsuspected therapeutic benefits. Furthermore,

by increasing coherence, clinicians may not only

enhance their own mental acuity and emotional sta-

bility, but may also develop increased sensitivity to

subtle electromagnetic information in their environ-

ment. This, in turn, could potentially enable a deeper

intuitive connection and communication between

practitioner and patient, which can be a crucial com-

ponent of the healing process.

In conclusion, I believe that the electromag-

netic energy generated by the heart is an untapped

resource within the human system awaiting further

exploration and application. Acting as a synchroniz-

ing force within the body, a key carrier of emotional

information, and an apparent mediator of a type of

subtle electromagnetic communication between

people, the cardiac bioelectromagnetic field may have

much to teach us about the inner dynamics of health

and disease as well as our interactions with others.

HeartMath, Freeze-Frame, and Heart Lock-In are registered trademarks

of the Institute of HeartMath. Freeze-Framer is a registered trademark

of Quantum Intech, Inc.

References

1. Stroink G. Principles of cardiomagnetism. In: Williamson

SJ, Hoke M, Stroink G, Kotani M, eds. Advances in

Biomagnetism. New York: Plenum Press, 1989:47-57.

2. Prank K, Schofl C, Laer L, Wagner M, von zur Muhlen A,

Brabant G, Gabbiani F. Coding of time-varying hormonal

signals in intracellular calcium spike trains. Pac Symp

Biocomput 1998:633-644.

3. Schofl C, Prank K, Brabant G. Pulsatile hormone secre-

tion for control of target organs. Wien Med Wochenschr

1995; 145:431-435.

4. Schofl C, Sanchez-Bueno A, Brabant G, Cobbold PH,

Cuthbertson KS. Frequency and amplitude enhancement

of calcium transients by cyclic AMP in hepatocytes. Biochem

J 1991; 273:799-802.

5. Pribram K, Melges F. Psychophysiological basis of emo-

tion. In: Vinken P, Bruyn G, eds. Handbook of Clinical Neu-

rology, Vol. 3. Amsterdam: North-Holland Publishing Com-

pany, 1969:316-341.

6. Coles M, Gratton G, Fabini M. Event-related brain po-

tentials. In: Cacioppo J, Tassinary L, eds. Principles of Psy-

chophysiology: Physical, Social and Inferential Elements.

New York: Cambridge University Press, 1990.

7. Schandry R, Montoya P. Event-related brain potentials

and the processing of cardiac activity. Biol Psychol 1996;

42:75-85.

8. Song L, Schwartz G, Russek L. Heart-focused attention

and heart-brain synchronization: Energetic and physiologi-

cal mechanisms. Altern Ther Health Med 1998; 4:44-62.

9. Armour J, Ardell J. Neurocardiology. New York: Oxford

University Press, 1994.

10. Sandman CA, Walker BB, Berka C. Influence of afferent

cardiovascular feedback on behavior and the cortical evoked

potential. In: Cacioppo JT, Petty RE, eds. Perspectives in

Cardiovascular Psychophysiology. New York: The Guilford

Press, 1982:189-222.

© Copyright 2003 Institute of HeartMath

18

11. Frysinger RC, Harper RM. Cardiac and respiratory cor-

relations with unit discharge in epileptic human temporal

lobe. Epilepsia 1990; 31:162-171.

12. McCraty R. Heart-brain neurodynamics: The making of

emotions. In: Childre D, McCraty R, Wilson BC, eds. Emo-

tional Sovereignty. Amsterdam: Harwood Academic Pub-

lishers, forthcoming.

13. van der Molen M, Somsen R, Orlebeke J. The rhythm of

the heart beat in information processing. In: Ackles P,

Jennings JR, Coles M, eds. Advances in Psychophysiology,

Vol. 1. London: JAI Press, 1985:1-88.

14. Tiller W, McCraty R, Atkinson M. Cardiac coherence: A

new, noninvasive measure of autonomic nervous system

order. Altern Ther Health Med 1996; 2:52-65.

15. McCraty R, Singer D. Heart rate variability: A measure

of autonomic balance and physiological coherence. In:

Childre D, McCraty R, Wilson BC, eds. Emotional Sover-

eignty. Amsterdam: Harwood Academic Publishers, forth-

coming.

16. McCraty R, Atkinson M, Tiller WA, Rein G, Watkins A.

The effects of emotions on short term heart rate variability

using power spectrum analysis. Am J Cardiol 1995;

76:1089-1093.

17. McCraty R, Barrios-Choplin B, Rozman D, Atkinson M,

Watkins A. The impact of a new emotional self-manage-

ment program on stress, emotions, heart rate variability,

DHEA and cortisol. Integr Physiol Behav Sci 1998; 33:151-

170.

18. Collet C, Vernet-Maury E, Delhomme G, Dittmar A.

Autonomic nervous system response patterns specificity

to basic emotions. J Auton Nerv Sys 1997; 62:45-57.

19. McCraty R, Atkinson M, Tomasino D, Goelitz J,

Mayrovitz H. The impact of an emotional self-management

skills course on psychosocial functioning and autonomic

recovery to stress in middle school children. Integr Physiol

Behav Sci 1999; 34:246-268.

20. McCraty R, Atkinson M. Psychophysiological coherence.

In: Childre D, McCraty R, Wilson BC, eds. Emotional Sov-

ereignty. Amsterdam: Harwood Academic Publishers, forth-

coming.

21. McCraty R. Influence of cardiac afferent input on heart-

brain synchronization and cognitive performance. Int J

Psychophysiol 2002; 45:72-73.

22. Baselli G, Cerutti S, Badilini F, Biancardi L, Porta A,

Pagani M, Lombardi F, Rimoldi O, Furlan R, Malliani A.

Model for the assessment of heart period variability inter-

actions of respiration influences. Med Biol Eng Comput

1994; 32:143-152.

23. deBoer RW, Karemaker JM, Strackee J. Hemodynamic

fluctuations and baroreflex sensitivity in humans: A beat-

to-beat model. Am J Physiol 1987; 253:H680-H689.

24. Langhorst P, Schulz G, Lambertz M. Oscillating neu-

ronal network of the “common brainstem system.” In:

Miyakawa K, Koepchen H, Polosa C, eds. Mechanisms of

Blood Pressure Waves.

Tokyo: Japan Scientific Societies

Press, 1984:257-275.

25. Siegel G, Ebeling BJ, Hofer HW, Nolte J, Roedel H,

Klubendorf D. Vascular smooth muscle rhythmicity. In:

Miyakawa K, Koepchen H, Polosa C, eds. Mechanisms of

Blood Pressure Waves. Tokyo: Japan Scientific Societies

Press, 1984:319-338.

26. Danner DD, Snowdon DA, Friesen WV. Positive emo-

tions in early life and longevity: Findings from the nun study.

J Pers Soc Psychol 2001; 80:804-813.

27. Salovey P, Rothman A, Detweiler J, Steward W. Emo-

tional states and physical health. Am Psychol 2000; 55:110-

121.

28. Russek LG, Schwartz GE. Feelings of parental caring

predict health status in midlife: A 35-year follow-up of the

Harvard Mastery of Stress Study. J Behav Med 1997; 20:1-

13.

29. Rein G, Atkinson M, McCraty R. The physiological and

psychological effects of compassion and anger. J Adv Med

1995; 8:87-105.

30. McCraty R, Atkinson M, Rein G, Watkins AD. Music

enhances the effect of positive emotional states on salivary

IgA. Stress Med 1996; 12:167-175.

31. McCraty R, Atkinson M, Tomasino D. Science of the

Heart. Boulder Creek, CA: HeartMath Research Center, In-

stitute of HeartMath, Publication No. 01-001, 2001.

32. Barrios-Choplin B, McCraty R, Cryer B. An inner qual-

ity approach to reducing stress and improving physical and

emotional wellbeing at work. Stress Med 1997; 13:193-201.

33. McCraty R, Atkinson M, Tomasino D. Impact of a work-

place stress reduction program on blood pressure and emo-

tional health in hypertensive employees. In preparation.

34. Luskin F, Reitz M, Newell K, Quinn TG, Haskell W.

A controlled pilot study of stress management training of

elderly patients with congestive heart failure. Prev Cardiol

2002; 5:168-172, 176.

35. McCraty R, Atkinson M, Lipsenthal L. Emotional self-

regulation program enhances psychological health and qual-

ity of life in patients with diabetes. Boulder Creek, CA:

HeartMath Research Center, Institute of HeartMath, Publi-

cation No. 00-006, 2000.

© Copyright 2003 Institute of HeartMath

19

36. Lehrer P, Smetankin A, Potapova T. Respiratory sinus

arrhythmia biofeedback therapy for asthma: A report of 20

unmedicated pediatric cases. Appl Psychophysiol Biofeed-

back 2000; 25:193-200.

37. Rozman D, Whitaker R, Beckman T, Jones D. A pilot

intervention program which reduces psychological symp-

tomatology in individuals with human immunodeficiency

virus. Complemen Ther Med 1996; 4:226-232.

38. McCraty R, Tomasino D, Atkinson M. Research, clinical

perspectives, and case histories. In: Childre D, McCraty R,

Wilson BC, eds. Emotional Sovereignty. Amsterdam:

Harwood Academic Publishers, forthcoming.

39. Childre D, Martin H. The HeartMath Solution. San Fran-

cisco: HarperSanFrancisco, 1999.

40. Childre D, Rozman, D. Overcoming Emotional Chaos:

Eliminate Anxiety, Lift Depression and Create Security in

Your Life. San Diego: Jodere Group, 2002.

41. McCraty R. Heart rhythm coherence – An emerging area

of biofeedback. Biofeedback 2002; 30:17-19.

42. Baule G, McFee R. Detection of the magnetic field of

the heart. Am Heart J 1963; 55:95-96.

43. Nakaya Y. Magnetocardiography: A comparison with

electrocardiography. J Cardiogr Suppl 1984; 3:31-40.

44. McCraty R, Atkinson M, Tiller WA. New electrophysi-

ological correlates associated with intentional heart focus.

Subtle Energies 1993; 4:251-268.

45. Russell P. The Brain Book. New York: Penguin Books

USA, 1979.

46. Wirth DP. The effect of non-contact therapeutic touch

on the healing rate of full thickness dermal wounds. Subtle

Energies 1990; 1:1-20.

47. Grad B. Some biological effects of the laying on of hands:

Review of experiments with animals and plants. J Am Soc

Psychical Res 1965; 59:95-171.

48. Keller E. Effects of therapeutic touch on tension head-

ache pain. Nurs Res 1986; 35:101-105.

49. Redner R, Briner B, Snellman L. Effects of a bioenergy

healing technique on chronic pain. Subtle Energies 1991;

2:43-68.

50. Krieger D. Healing by the laying on of hands as a facili-

tator of bioenergetic change: The response of in-vivo hu-

man hemoglobin. Psychoenerg Syst 1974; 1:121-129.

51. Rein G, McCraty R. Structural changes in water and

DNA associated with new physiologically measurable states.

J Sci Explor 1994; 8:438-439.

52. Rein G, McCraty R. Modulation of DNA by coherent

heart frequencies. Proceedings of the Third Annual Con-

ference of the International Society for the Study of Subtle

Energy and Energy Medicine, Monterey, CA, June 25-29,

1993:58-62.

53. Quinn J. Therapeutic touch as an energy exchange:

Testing the theory. ANS Adv Nurs Sci 1984; 6:42-49.

54. Hatfield E. Emotional Contagion. New York: Cambridge

University Press, 1994.

55. Levenson RW, Ruef AM. Physiological aspects of emo-

tional knowledge and rapport. In: Ickes W, ed. Empathic

Accuracy. New York: Guilford Press, 1997.

56. Levenson R, Gottman J. Physiological and affective pre-

dictors of change in relationship satisfaction. J Pers Soc

Psychol 1985; 49:85-94.

57. Robinson J, Herman A, Kaplan B. Autonomic responses

correlate with counselor-client empathy. J Couns Psychol

1982; 29:195-198.

58. Reidbord SP, Redington DJ. Nonlinear analysis of auto-

nomic responses in a therapist during psychotherapy. J Nerv

Ment Dis 1993; 181:428-435.

59. Marci CD. Psychophysiology and psychotherapy: The

neurobiology of human relatedness. Practical Reviews of

Psychiatry (Audio tape) 2002; 25(3).

60. McCraty R, Atkinson M, Tomasino D, Tiller W. The elec-

tricity of touch: Detection and measurement of cardiac

energy exchange between people. In: Pribram K, ed. Brain

and Values: Is a Biological Science of Values Possible.

Mahwah, NJ: Lawrence Erlbaum Associates, 1998:359-379.

61. Russek L, Schwartz G. Interpersonal heart-brain regis-

tration and the perception of parental love: A 42 year fol-

low-up of the Harvard Mastery of Stress Study. Subtle En-

ergies 1994; 5:195-208.

62. Russek L, Schwartz G. Energy Cardiology: A dynamical

energy systems approach for integrating conventional and

alternative medicine. Advances 1996; 12:4-24.

63. Wiesenfeld K, Moss F. Stochastic resonance and the

benefits of noise: From ice ages to crayfish and SQUIDs.

Nature 1995; 373:33-36.

64. Bulsara AR, Gammaitoni L. Tuning into noise. Physics

Today 1996; March:39-45.

65. Poponin V. Nonlinear stochastic resonance in weak EMF

interactions with diamagnetic ions bound within proteins.

In: Allen MJ, Cleary SF, Sower AE, eds. Charge and Field

Effects in Biosystems. New Jersey: World Scientific,

1994:306-319.

© Copyright 2003 Institute of HeartMath

20

66. Astumian RD, Weaver JC, Adair RK. Rectification and

signal averaging of weak electric fields by biological cells.

Proc Natl Acad Sci USA 1995; 92:740-743.

67. Childre D, Cryer B. From Chaos to Coherence: The

Power to Change Performance. Boulder Creek, CA: Plan-

etary, 2000.

68. Schlitz M, Braud W. Distant intentionality and healing:

Assessing the evidence. Altern Ther Health Med 1997; 3:62-

73.

69. Randoll U. The role of complex biophysical-chemical

therapies for cancer. Bioelectrochem Bioenerg 1992; 27:341-

346.

70. Randoll U, Dehmlow R, Regling G, Olbrich K. Ultra-

structure tomographical observations of life processes as

dependent on weak electromagnetic fields. Dtch Zschr

Onkol 1994; 26:12-14.

71. Bialek W. Physical limits to sensation and perception.

Annu Rev Biophys Biophys Chem 1987; 16:455-478.

72. Weaver JC, Astumian RD. The response of living cells

to very weak electric fields: The thermal noise limit. Sci-

ence 1990; 247:459-462.

73. Walleczek J. Field effects on cells of the immune sys-

tem: The role of calcium signaling. Fed Am Soc Exp Biol

1992; 6:3177-3185.

74. Litovitz TA, Krause D, Mullins JM. Effect of coherence

time of the applied magnetic field on ornithine decarboxy-

lase activity. Biochem Biophys Res Commun 1991; 178:862-

865.

75. Bezrukov SM, Vodyanoy I. Noise-induced enhancement

of signal transduction across voltage-dependent ion chan-

nels. Nature 1995; 378:362-364.

76. Levin JE, Miller JP. Broadband neural encoding in the

cricket cercal sensory system enhanced by stochastic reso-

nance. Nature 1996; 380:165-168.

77. Bezrukov SM, Vodyanoy I. Stochastic resonance in non-

dynamical systems without response thresholds. Nature

1997; 385:319-321.

© Copyright 2003 Institute of HeartMath

The Energetic Heart: Biolectromagnetic Interactions Within and Between People (PDF Download Available). Available from: https://www.researchgate.net/publication/274451622_The_Energetic_Heart_Biolectromagnetic_Interactions_Within_and_Between_People [accessed Feb 09 2018].