BCIA How to Increase the Effectiveness of Your HRV ...€¦ · Using the Lehrer et al. (2013)...

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BCIA Webinar

Fred Shaffer, PhD, BCBTruman State University, Center for Applied [email protected]

How to Increase the Effectiveness of Your HRV Biofeedback Practice

I want to recognize the contributions of several amazing colleagues: Dick Gevirtz, PhD, BCB, Paul Lehrer, PhD, BCB, Donald Moss, PhD, BCB, BCN, and Erik Peper, PhD.

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Inna Khazan, PhD, BCB, David Hagedorn, PhD, BCN, and Rollin McCraty, PhD.

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Thanks to Inna Khazan, the Institute of HeartMath, J & J Engineering, Mind Media,and Thought Technology Ltd., for graphics and adapted figures used in this presentation.

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Thanks to the undergraduates who staff Truman State University’s Center for Applied Psychophysiology.

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Finally, thanks to Lab Managers Christopher Zerr (2011‐2015) and Zachary Meehan (2016).

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1. Attendees will be able to explain how to measure a client’s resonance frequency.

2. Attendees will be able to choose between competing breathing rates and inhalation‐to‐exhalation ratios.

3. Attendees will be able to describe how to structure training sessions to increase heart rate variability.

Educational Objectives

4. Attendees will be able to assess client progress during training.

5. Attendees will be able to evaluate the experimental support for popular HRVB applications.

Educational Objectives

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1. How to measure the resonance frequency

2. How to structure an HRVB training session

3. Clinical efficacy of HRV biofeedback

Webinar Units

Unit 1: How to Measure the Resonance Frequency

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Resonance

Lehrer and colleagues (2004) proposed that each individual’s cardiovascular system has a unique resonance frequency, which is caused by the delay in the baroreflex. Inertia in the blood supply accounts for most of this delay.

How to Measure the Resonance Frequency

Taller people and men have lower resonance frequencies than women and shorter people, because the former have larger blood volumes.


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When clients breathe at their resonance frequency, heart rate and respiration are in perfect phase (0o); their peaks and valleys coincide.

In adults, this frequency varies from 4.5‐6.5 breaths per minute (Gevirtz, Lehrer, & Schwartz, 2016).


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When clients breathe at this rate, they “exercise” the baroreflex.

Resonance frequency (RF) breathing amplifies the swings in heart rate produced by the baroreflex, increasing baroreflex gain and respiratory sinus arrhythmia.


Increased RSA with RF breathing from Gevirtz, Lehrer, and Schwartz (2016)


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RF breathing also modulates blood pressure changes since heart rate (HR) and blood pressure (BP) oscillations are 180o out of phase (DeBoer, Karemaker, & Strackee, 1987; Vaschillo et al., 2002).


RF breathing shifts the peak frequency from the high frequency band (~0.20 Hz) to thecardiovascular system’s resonance frequency (~0.10 Hz).

RF breathing more than doubles the energy in the low frequency band of the ECG (0.04‐0.15 Hz).


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To find the breathing rate that maximizes the baroreflex, instruct your client to breathe at each target rate using a pacer for 3 min followed by a 1‐min buffer period.


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This allows you to delete 1 min of bad data from the start or end of your trial and still have the 2 min required to calculate peak‐to‐trough differences (HR Max – HR Min).

Always visually inspect your data for artifact and don’t be misled by summary statistics.


For adults, start at 7.5 bpm and continue in descending 0.5 bpm steps to 4.5 bpm, regardless of your client’s height.

Consider 9.5 to 6.5 breaths per min for children.

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Since most adults breathe between 12‐16 breaths per min (Fried, 1990), slower breathing may be difficult for some clients. This can be especially true for chronic pain patients, who may breathe faster than 16 bpm.

After each trial, confirm that your client breathed at the required rate and repeat trials where they were 0.25 bpm too fast or slow.


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1. Record breathing at each respiration rate as a separate 3‐min epoch.

2. Take a single screenshot of respirometer and instantaneous HR signals for each trial.

3. Measure HR Max – HR Min, absolute and % LF power, phase angle (of the peaks of the HR and respirometer tracings), and EKG peak frequency mean for each trial.


You can use screenshots of each epoch to visually evaluate synchrony. SnagIt by TechSmith is a powerful utility. Paste the screenshots into PowerPoint and then advance through the slides to see changes in phase.

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Lehrer et al. (2013) developed this protocol, which we have adapted.


Didier Combatalade, Director of Clinical Interface at Thought Technology Ltd., provided invaluable technical support in measuring the phase relationship between respirometer and heart rate signals using BioGraph Infiniti software.

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Christopher Zerr, former Lab Manager for the Truman Center for Applied Psychophysiology,provided technical support and supervised data collection to illustrate this protocol.


The resonance frequency is the breathing rate that satisfies the majority of these parameters:1. synchrony of the respirometer and heart rate

signals2. largest peak‐to‐trough HR differences (HR Max

– HR Min)3. largest absolute and percentage LF power,

and highest LF peak frequency near 0.1 Hz4. smoothest and most regular heart rate

waveforms

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Peaks of the respirometer and HR signals coincide (0 degrees is best)

Largest HR Max – HR Min

Largest absolute and % LF power, and highest LF peak frequency near 0.1 Hz

Smoothest and most regular HR signals

Resonance Frequency

Finding the Resonance Frequency: 7.5

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Using the Lehrer et al. (2013) criteria, we could choose a respiration rate of 5.5 bpm due to its synchrony (7 o), peak‐to‐trough difference (49 bpm), and peak frequency (0.09 Hz).


RR Phase Max-Min LF % Peak SDRR Temp SCL Systolic Diastolic

7.5 25 0 40 83 0.13 122 97 14 103 61

7.0 22 0 38 94 0.11 128 96 14 118 65

6.5 27 0 43 93 0.11 158 96 15 133 56

6.0 13 0 46 95 0.09 154 96 15 106 73

5.5 7 0 49 90 0.09 181 96 16 116 70

5.0 -30 0 53 94 0.08 188 96 19 107 58

4.5 -32 0 51 94 0.08 192 96 20 101 72

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Which breathing rate should you choose if there are two possible resonance frequencies?

Choose the rate that your client prefers.


Resonance frequency measurements using this protocol have a 2‐week test‐retest reliability of 0.73 (Wally et al., 2011).

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Unit 2: How to Structure an HRV Biofeedback Training Session

How to Structure a HRVB Training Session

The aim of heart rate variability biofeedback (HRVB) is to exercise the baroreceptor reflex to enhance homeostatic regulation, improve executive functions, and increase awareness of how a more balanced inner state feels.

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The overarching purpose of HRVB training is to improve your client's ability to self‐regulate and to enhance health, the quality of life, and performance.


Successful HRVB training integrates mindfulness, emotional self‐regulation, and resonance frequency breathing.

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Resonance Frequency Breathing

MindfulnessEmotional

Self‐Regulation



Mindfulness involves "paying attention in a particular way: on purpose, in the present moment, and nonjudgmentally" (Kabat‐Zinn, 1994).

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Mindfulness guides the trial‐and‐error process underlying self‐regulation by helping clients to draw connections between their actions, internal feedback, and results.


Clients discover their unique psychophysiological response patterns and learn which strategies help them to increase HRV.

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Emotional self‐regulation involves the self‐monitoring, initiation, maintenance, and modulation of positive and negative emotions, and the avoidance and reduction of high levels of negative affect (Bridges, Denham, & Ganiban, 2004).


Finally, resonance frequency breathing involves effortless breathing at an individual's unique resonance frequency, which varies in adults from 4.5‐6.5 breaths per min, to exercise the baroreceptor reflex.

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Lehrer et al. (2013) recommend inhaling through the nose and exhaling through pursed lips, since this moistens and heats inhaled air, and enhances sensory feedback.

Which inhalation‐to‐exhalation ratio is best?

Since Zerr et al. (2015) and Meehan et al. (manuscript in preparation) found no advantage for a 1:2 versus a 1:1 inhalation‐to‐exhalation ratio on any time domain or frequency domain HRV measure, you might follow your client's preference.


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Should you encourage your client to increase abdominal excursion?

Abdominal excursion is the degree of respirometer movement from inhalation to exhalation.


Meehan et al. (manuscript in preparation) found that increasing abdominal excursion resulted in significantly greater HR Max – HR Min, SDNN, and pNN50 values in 36 undergraduates aged 19‐26.

The effect sizes, which ranged from 0.34‐0.36 were large.


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Allow your client to effortlessly increase the expansion and contraction of the abdomen, since this may increase heart rate variability.


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Consider starting with HRVB before other modalities, since it can significantly raise hand temperature (4o F/2.2oC) and lower SCL (3.5 μS) (Zerr et al., 2014).


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HRVB TEMPB

Temperature Change

Session 1 Session 4

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0

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HRVB TEMPB

Skin Conductance Level Change

Session 1 Session 4


Gevirtz has suggested using hand temperature as an HRV home practice outcome index.

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Date Time Exercise Length Start Temp

End Temp

How Did You Feel?

What Did You Learn?

5-10-2016

noon RF breathing

15 81o 83o Calm with greater awareness of my body

I breathe in my chest more than I realized

5-11-2016

noon InnerBalance

20 82o 84o Less stressed My heart rhythm becomes more regular when I reduce my effort


Consider using SD1, the standard deviation of the distance of each point from the y = x axis of a Poincaré (pwaⁿ‐ˌkä‐ˈrā) plot, to assess your clients. You can calculate this index using Kubios2.2 software.

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SD1, which is measured in ms, predicted diastolic blood pressure, HR Max – HR Min, RMSSD, pNN50, and SDNN in healthy undergraduates (Zerr et al., 2015).

Clinical tips when you start HRV training:1. Model effortless breathing and positive

emotion for your client throughout eachsession.


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2. The warmth and supportiveness of your relationship with your client is the foundation for successful biofeedback training (Taub &School, 1978).


From a polyvagal theory perspective, it creates a safe environment in which your client can practice alternatives to fight‐or‐flight, freezing, or parasympathetic withdrawal.


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3. For clinical work, consider an ECG sensoron the wrist or a PPG sensor on an earlobeor finger.



ECG wrist placement

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Photoplethysmograph (PPG) sensor

8. Provide HRV biofeedback displays of respirometer movement and instantaneous heart rate.

Analog displays can provide your client with incredibly detailed and intuitive information.


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4. While client preference should guide your selection of feedback displays, you might try feedback of low frequency power and peak‐to‐trough differences first.


The concentration of signal power around 0.1 Hz in the LF band corresponds to Institute of HeartMath's concept of coherence, in which a client produces a "narrow, high‐amplitude, easily visualized peak" from 0.09‐0.14 Hz (Ginsberg, Berry, & Powell, 2010, p. 54; McCraty et al., 2009).


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Which HRV Measures Should You Display?

Meehan et al. (manuscript in preparation) found that low frequency power and peak‐to‐trough differenceswere the best predictors of SDNN and RMSSD in our undergraduates during HRVB training.


Low frequency (LF) power is the amount of HRV signal energy in the 0.04‐0.15 Hz range.

Peak‐to‐trough differences are the mean heart rate differences across breathing cycles, and are indexed by HR Max – HR Min.


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SDNN is the standard deviation of the normal (NN) sinus‐initiated IBIs measured in ms.

RMSSD is the square root of the mean squared difference of adjacent NN intervals.


LF power and peak‐to‐trough differences accounted for 82% and 67% of the variability in SDNN, respectively, during HRVB training.


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LF power and peak‐to‐trough differences accounted for 89% and 67% of the variability in RMSSD, respectively, during HRVB training.


Neither the phase relationship between the peaks of the ECG and respiration waveforms nor the peak ECG frequency (e.g., 0.9 Hz) predicted these time domain measures when subjects breathed around 6 bpm.


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PredictedPeak‐to‐Trough

LF Power Absolute Phase

Peak Frequency

SDNN 67% 82% NS NS

RMSSD 67% 89% NS NS


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5. While it did not predict SDNN or RMSSD, in our undergraduates because they werealready breathing around 6 bpm, some clients may prefer a display of the synchrony between respirometer and instantaneous heart rate signals.



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6. Once your client has mastered resonance frequency breathing, games can motivatepractice and speed skill acquisition.

Well‐designed software suites allow clients to increase the level of game difficulty, which is crucial for transferring resonance frequency breathing to everyday life.



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7. Emotional self‐regulation, using strategies like activating feelings of appreciation, may help to “immunize” clients against the disruptive effects of increased challenge, frustration, and distress, and speed recovery from stressors.


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Resonance frequency breathing

Exercises the baroreflex

Increases HRV and executive

functions


Emotional self‐regulation

Increases resilience and quality of life

May protect HRV

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Each session might be structured as follows:1. 5‐min discussion of practice and progress

during sensor attachment2. 3‐min baseline (no feedback)

3. six 3‐min HRV biofeedback segments,each followed by coaching

4. 3‐min baseline (no feedback)

5. assignment of practice


Introduction “Heart rate variability training depends on your: 1. adopting a passive attitude, where you allow

yourself to breathe,

2. breathing with about 70% of your maximum effort, and

3. gradually slowing your breathing to around 6 breaths per minute.”

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“The computer can help you learn slow effortless breathing. The pink tracing shows your heart rate, while the violet tracing shows the movement of the sensor around your stomach.

As you gradually learn to breathe effortlessly, the two tracings should resemble smooth, repeating, ocean waves.”


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“Since no one should expect to instantly breathe at 6 breaths per minute, we will start your pacer, which located is at the top of the screen, at 12 breaths per minute. Let it guide your inhalation and exhalation.

Allow your stomach to gradually plop out as you inhale and then slowly draw inward as you exhale. As you practice, we will adjust the speed of the pacing display.”


Start recording data for 3 min. At the end of the training segment ask:

”How was the speed of the pacing display? Should we change it? Should we adjust the inhalation and exhalation lengths?

What did you experience as you practiced breathing effortlessly?”

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Training success indicators:1. breathing followed the pacing display2. the two signals were rhythmic and regular3. signal peaks and valleys coincided4. signal energy increased within the low

frequency band, centered around 0.1 Hz


Training difficulty indicators:1. your client could not follow the pacing display2. the two signals were irregular3. signal peaks and valleys were out of phase4. your client used excessive effort 5. signal energy increased in the very low

frequency or high frequency bands6. your client displayed dysfunctional breathing

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Training segment reviewFit the entire 3‐min segment on the screen to review it together. If your client succeeded, you might point out where she succeeded:1. breathing slowed down towards her resonance

frequency

2. the tracings became more like ocean waves


3. the peaks and valleys of the two tracings came closer together

4. the accessory muscles remained relaxed

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Before starting the next segment, you might ask:“What were you doing when the display became wavelike and regular?” “What happened when the display became more jagged and irregular?”

If accessory SEMG exceeded 2 microvolts, point this out on the display, ask her if she felt the heightened breathing effort, and encourage her to “let her shoulders relax and allow herself to breathe.”

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If your client experienced difficulty, find a portion of the 3‐min segment where breathing was better and focus on what she did correctly.

You might ask “What were you doing when the display became wavelike and regular?” “What happened when the display became more jagged and irregular?”


Reassure her that it’s normal for the tracings to be choppy when people start training and that they will gradually become more wavelike as their breathing becomes more rhythmic and regular.

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Instead of overwhelming her with corrections, ask her to experiment with just one change.

For example, “Effortless breathing is rhythmic like ocean waves. Allow your abdomen to gently expand and contract as you follow the pacing display.”


Display entire 3‐min segment on one screen

Highlight what your client did

correctly

Suggest one improvement

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Session review After your client has completed six 3‐min training segments, take a 3‐min post‐baseline without feedback.

After the post‐baseline, ask your client how she felt and what she learned during the training session. Display the entire session on one screen and highlight where she succeeded and where she needs more work.


Display the entire session

Highlight what your client did

correctly

Identify where she needs more work

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How many heart rate variability biofeedback sessions are required?

Many clients start to breathe more effortlessly and increase HRV during their initial training session.


There can be a several‐week lag between increased HRV and improved health or performance.

Clients require this time to consolidate their learning and transfer enhanced skills to the diverse settings of their lives.

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Practice is the bridge between the clinic and everyday life.


Clients may require more than 10 sessions and corresponding weeks of practice to achieve maximum psychological, physiological, and performance gains (Gevirtz, Lehrer, & Schwartz, 2016; Lagos et al., 2011).

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Psychophysiological Change

Improved Health and Performance

Generalization and Maintenance

1‐10+ sessions 2‐6+ months


The most important HRV training elements:1. education about the purpose, benefits, and

process of HRV biofeedback

2. correction of breathing mechanics andmodeling the breathing pattern and positive emotion that you want your client to learn

3. warm and supportive relationship with yourclient

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4. gradual shaping of your client’s respiration rate towards her resonance frequency

5. daily practice of HRVB skills for 20 min

Glossary

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absolute power: the magnitude of HRV within a frequency band measured in milliseconds squared divided by cycles per second (ms2/Hz).

approximate entropy (ApEn): nonlinear index of HRV that measures the regularity and complexity of a time series.

baroreflex: baroreceptor reflex that provides negative feedback control of blood pressure. Elevated blood pressure activates the baroreflex to lower blood pressure and low blood pressure suppresses the baroreflex to raise blood pressure.

blood volume pulse (BVP): the phasic change in blood volume with each heartbeat. It is the vertical distance between the minimum value (trough) of one pulse wave and the maximum value (peak) of the next measured using a photoplethysmograph (PPG).

detrended fluctuation analysis (DFA): nonlinear index of HRV that extracts the correlations between successive R‐R intervals over different time scales and yields estimates of short‐term (α1) and long‐term (α2) fluctuations.

Glossary

electrocardiogram (ECG): recording of the electrical activity of the heart using an electrocardiograph.

frequency domain measures of HRV: calculation of the absolute or relative power of the HRV signal within four frequency bands.

high frequency (HF) band: ECG frequency range from 0.15‐.40 Hz that represents the Inhibition and activation of the vagus nerves by breathing (respiratory sinus arrhythmia).

HR Max – HR Min: index of heart rate variability that calculates the difference between the highest and lowest heart rates during each respiratory cycle.

HRV triangular index: geometric measure based on 24‐hour recordings that divides the number of NN intervals by the number of NN intervals found within the modal 8‐millisecond bin.

interbeat interval (IBI): the time interval between the peaks of successive R‐spikes (initial upward deflections in the QRS complex). This is also called the NN (normal‐ to‐normal) interval.

Glossary

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low frequency (LF) band: ECG frequency range of 0.04‐0.15 Hz that may represent the influence of PNS, SNS, and baroreflex activity (when breathing at resonance frequency).

NN interval: the normal‐to‐normal interval is an interbeat interval after artifact has been removed.

NN50: the number of adjacent NN intervals that differ from each other by more than 50 milliseconds.

nonlinear measurements: indices that quantify the unpredictability of a time series, which results from the complexity of the mechanisms that regulate the measured variable.

parasympathetic vagus (X) nerves: cranial nerves that arise from the medulla’s cardiovascular center, decrease the rate of spontaneous depolarization in SA and AV nodes, and slow the heart rate from the SA nodes intrinsic rate of 100 beats per minute.

photoplethysmograph (PPG): device that measures the relative amount of blood flow through tissue using a photoelectric transducer.

Glossary

pNN50: the percentage of adjacent NN intervals that differ from each other by more than 50 milliseconds.

quantitative EEG (QEEG): digitized statistical brain mapping using at least a 19‐channel montage to measure EEG amplitude within specific frequency bins.

relative power: the percentage of total HRV.

resonance frequency: frequency at which a system, like the cardiovascular system, can be activated or stimulated.

respiratory sinus arrhythmia (RSA): respiration‐driven heart rhythm that contributes to the high frequency (HF) component of heart rate variability. Inhalation inhibits vagal nerve slowing of the heart (increasing heart rate), while exhalation restores vagal slowing (decreasing heart rate).

R‐spike: initial upward deflection in the QRS complex of the ECG.

RMSSD: the square root of the mean squared difference of adjacent NN intervals.

Glossary

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S: nonlinear index of HRV that measures the area of the ellipse, which represents total HRV.

sample entropy (SampEn): nonlinear index of HRV that was designed to provide a less biased measure of signal regularity and complexity than ApEn.

SD1: the standard deviation of the distance of each point from the y = x axis that measures short‐term HRV.

SD2: the standard deviation of each point from the y = x + average RR interval that measures short‐ and long‐term HRV.

SD1/SD2: ratio that measures the unpredictability of the R‐R time series and autonomic balance under appropriate monitoring conditions.

SDANN: the standard deviation of the average NN intervals. This index is usually calculated over 5 minutes.

Glossary

SDNN: the standard deviation of the interbeat interval measured in milliseconds, which predicts both morbidity and mortality.

SDNN index: the average of 5‐minute standard deviations of NN intervals across a 24‐hour period that measures the contribution of rhythms briefer than 5 minutes to heart rate variability.

SDRR: the standard deviation of the interbeat interval for all sinus beats measured in milliseconds, which predicts both morbidity and mortality.

spectral analysis: division of heart rate variability into its component rhythms that operate within different frequency bands.

ultra low frequency (ULF) band: ECG frequency range below 0.003 Hz Very slow biological processes that include circadian rhythms, core body temperature, metabolism, and the renin‐angiotensin system, and possible PNS and SNS contributions.

Glossary

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very low frequency (VLF): ECG frequency range of 0.003‐0.04 Hz that may represent temperature regulation, plasma renin fluctuations, endothelial, and physical activity influences, cardiac afferent sensory neuron stimulation, and possible PNS and SNS contributions.

Glossary

Recommended Reading and References

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Recommended Reading

www.aapb.org

Lehrer, P. M., & Gevirtz, R. (2014). Heart rate variability: How and why does it work?Frontiers in Psychology. doi:10.3389/fpsyg.2014.00756

McCraty, R., & Shaffer, F. (2015). Heart rate variability: New perspectives on physiological mechanisms, assessment of self‐regulatory capacity, and health risk. Global Advances in Health and Medicine, 4(1), 46‐61. doi:10.7453/gahmj.2014.073

Shaffer, F., McCraty, R., & Zerr, C. L. (2014). A healthy heart is not a metronome: An integrative review of the heart’s anatomy and heart rate variability. Frontiers in Psychology. doi:10.3389/fpsyg.2014.01040

Recommended Reading

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Berntson, G. G., Quigley, K. S., & Lozano, D. (2007). Cardiovascular psychophysiology. In J. T. Cacioppo, L. G. Tassinary, & G. G. Berntson, (Eds.). Handbook of psychophysiology (3rd ed.). New York: Cambridge University Press.

Bridges, L. J., Denham, S. A., & Ganiban, J. M. (2004). Definitional issues in emotion regulation research. Child Development, 75(2), 340‐345.

Fuller, J., Wally, C., Westermann‐Long, Korenfeld, D., & Carrell, D. (2011). Resonance frequency measurements are reliable [Abstract]. Applied Psychophysiology and Biofeedback, 36, 219.

Gevirtz, R. N., Lehrer, P. M., & Schwartz, M. S. (2016). Cardiorespiratory biofeedback. In M.S. Schwartz & F. Andrasik (Eds.). Biofeedback: A practitioner’s guide (4th ed.). New York: The Guilford Press.

Gilbert, C. (2012). Pulse oximetry and breathing training. Biofeedback, 40(4), 137‐141.

Ginsberg, J. P., Berry, M. E., & Powell, D. A. (2010). Alternative Therapies, 16(4), 52‐60.

References

Hagedorn, D. (2014). Infection risk mitigation for biofeedback providers. Biofeedback, 42(3), 93‐95.

Kabat‐Zinn, J. (1994). Wherever you go, there you are: Mindfulness mediation in everyday life. New York: Hyperion Books.

Lagos, L., Vaschillo, E., Vaschillo, B., Lehrer, P., Bates, M., & Pandina, R. (2011). Virtual reality assisted heart rate variability biofeedback as a strategy to improve golf performance: A case study. Biofeedback, 39(1), 15‐20.

Lehrer, P., Vaschillo, B., Zucker, T., Graves, J., Katsamanis, M., Aviles, M., & Wamboldt, F. (2013). Protocol for heart rate variability biofeedback training. Biofeedback, 41, 98–109. doi: 10.5298/1081‐5937‐41.3.08

Lehrer, P. M. (2007). Biofeedback training to increase heart rate variability. In P. M. Lehrer, R. M. Woolfolk, & W. E. Sime (Eds.). Principles and practice of stress management (3rd ed.). New York: The Guilford Press.

References

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Lehrer, P. M. (2013). How does heart rate variability biofeedback work? Resonance, the baroreflex, and other mechanisms. Biofeedback, 41(1), 26‐31.

Lehrer, P. M., & Vaschillo, E. (2008). The future of heart rate variability biofeedback. Biofeedback, 36(1), 11‐14.

Lehrer, P. M., Vaschillo, E., & Vaschillo, B. (2000). Resonant frequency biofeedback training to increase cardiac variability: Rationale and manual for training. Applied Psychophysiology and Biofeedback, 25(3), 177‐191.

McCraty, R., Atkinson, M., Tiller, W. A. (1995). The effects of emotion on short term heart rate variability using power spectrum analysis. American Journal of Cardiology, 76.

McCraty, R., Atkinson, M., Tomasino, D, & Bradley, R. T. (2006). The coherent heart. Boulder Creek, CA: Institute of HeartMath.

McCraty, R., Atkinson M, Tomasino, D., & Bradley, R. T. (2009). The coherent heart: Heart‐brain interactions, psychophysiological coherence, and the emergence of system‐wide order. Integral Review, 5(2), 10‐115.

References

Nunan, D., Sandercock, G. R. H., & Brodie, D. A. (2010). A quantitative systematic review of normal values for short‐term heart rate variability in healthy adults. Pacing and Clinical Electrophysiology, 33, 1407–1417.

Peper, E., Gibney, K. H., Tylova, H., Harvey, R., & Combatalade, D. (2008). Biofeedback mastery: An experiential teaching and self‐training manual. Wheat Ridge, CO: AAPB.

Shaffer, F., Mayhew, J. L., Bergman, S., Dougherty, J., Koester, A. (1999). Effortfulbreathing may lower end‐tidal CO2 through increased tidal volume [Abstract].Applied Psychophysiology and Biofeedback, 24(2), 124.

Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology (1996). Heart rate variability: Standards of measurement, physiological interpretation, and clinical use. Circulation, 93, 1043‐1065.

Taub, E., & School, P. J. (1978). Some methodological considerations in thermal biofeedback training. Behavior Research Methods & Instrumentation, 10(5), 617‐622.

References

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Umetami, K., Singer, D. H., McCraty, R., & Atkinson, M. (1998). Twenty‐four hour time domain heart rate variability and heart rate: Relations to age and gender over nine decades. Journal of the American College of Cardiology, 31(3), 593‐601.

Vaschillo, E., Lehrer, P., Rishe, N., & Konstantinov, M. (2002). Heart rate variability biofeedback as a method for assessing baroreflex function: A preliminary study of resonance in the cardiovascular system. Applied Psychophysiology and Biofeedback, 27(1), 1‐27.

Zerr, C., Kane, A., Vodopest, T., Allen, J., Fluty, E., Gregory, J., . . . Shaffer, F. (2014). Heart rate variability norms for healthy undergraduates [Abstract]. Applied Psychophysiology and Biofeedback, 39, 300. doi:10.1007/s10484‐014‐9254‐9

Zerr, C., Kane, A., Vodopest, T., Allen, J., Fluty, E., Gregory, J., . . . Shaffer, F. (2014). HRV biofeedback training raises temperature and lowers skin conductance [Abstract]. Applied Psychophysiology and Biofeedback, 39(3). doi: 10.1007/s10484‐014‐92549

References

Zerr, C., Kane, A., Vodopest, T., Allen, J., Hannan, J., Fabbri, M., . . . Shaffer, F. (2015). Does inhalation‐to‐exhalation ratio matter in heart rate variability biofeedback? [Abstract]. Applied Psychophysiology and Biofeedback, 40(2), 135. doi:10.1007/s10484‐015‐9282‐0

Zerr, C., Kane, A., Vodopest, T., Allen, J., Hannan, J., Fabbri, M., . . . Shaffer, F. (2015).The nonlinear index SD1 predicts diastolic blood pressure and HRV time and frequency domain measurements in healthy undergraduates [Abstract]. Applied Psychophysiology and Biofeedback, 40(2), 134. doi:10.1007/s10484‐015‐9282‐0

References

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Unit 3: HRV Biofeedback Applications

Credit

I want to recognize the contributions of Dick Gevirtz, PhD, BCB, Donald Moss, PhD, BCB, BCN, and Angele McGrady, PhD, LPC, BCB, to this presentation.

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Credit

McGrady and Moss’ (2013) Pathways to Illness, Pathways to Health was an invaluable resource for this presentation.

The Clinical Efficacy of Established Medical Practices

Prasad et al. (2013) examined 363 studies of an accepted drug or medical procedure published in The New England Journal of Medicine from 2001 to 2010.

Clinical Efficacy of HRV Biofeedback

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How efficacious were they?

More than 40% were ineffective or harmful, 38% were beneficial, and 22% had uncertain value.


Unknown value

Beneficial

Ineffective or harmful

Unknown value Beneficial Ineffective or harmful

Examples of ineffective or harmful practices included hormone replacement therapy in postmenopausal women and aggressive blood sugar reduction in Type 2 diabetics treated in intensive care, which increased mortality rates.


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The authors observed:

“Nevertheless, the reversals we have identified at the very least call these practices into question. Some practices ought to be abandoned, whereas others warrant retesting in more powerful investigations. One of the greatest virtues of medical research is our continual quest to reassess it.” (p. 796)


Currie, Stabile, and Jones (2013) studied the educational outcomes and medication use of almost 4,000 children in Quebec from 1994‐2008. They evaluated the effect of increased drug insurance coverage, which was associated with a significant rise in Ritalin use.


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The authors reported:

“Overall, we find considerable evidence of a decline in both behavioral and educational outcomes following the increase in prescription drug coverage and the corresponding increase in Ritalin use. The effects are, in a number of cases, both statistically significant and large.” (p. 21)


Criteria for Clinical Efficacy

The major membership organizations in our field have developed efficacy guidelines and have engaged in an ongoing assessment of clinical and optimal performance practices.


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The third edition of Evidence‐Based Practice in Biofeedback and Neurofeedback is now available. This reference was preceded by literature reviews of HRVB applications by Wheat and Larkin (2010) and Gevirtz (2013).


Guidelines for evaluating the clinical efficacy of biofeedback and neurofeedback interventions were recommended by a joint Task Force and adopted by the Boards of Directors of the Association for Applied Psychophysiology (AAPB) and the International Society for Neuronal Regulation (ISNR) (LaVaque et al., 2002).


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Tan, Shaffer, Lyle, and Teo (2016) evaluated a wide variety of biofeedback and neurofeedback applications using these guidelines in Evidence‐Based Practice in Biofeedback and Neurofeedback (3rd ed.).


Level 1: Not Empirically SupportedSupported only by anecdotal reports and/or case studies in non‐peer reviewed venues.


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Level 2: Possibly EfficaciousAt least one study of sufficient statistical power with well identified outcome measures, but lacking randomized assignment to a control condition internal to the study.


Level 3: Probably Efficacious Multiple observational studies, clinical studies, wait list controlled studies, and within subject and intrasubject replication studies that demonstrate efficacy.


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Level 4: EfficaciousIn a comparison with a no‐treatment control group, alternative treatment group, or sham (placebo) control utilizing randomized assignment, the investigational treatment is shown to be statistically significantly superior.


The studies have been conducted with a population treated for a specific problem, for whom inclusion criteria are delineated in a reliable, operationally defined manner.


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The study used valid and clearly specified outcome measures related to the problem being treated.

The data are subjected to appropriate data analysis.


The diagnostic and treatment variables and procedures are clearly defined in a manner that permits replication of the study by independent researchers.

The superiority or equivalence of the investigational treatment has been shown in at least two independent research settings.


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Part 1: Psychological DisordersAnxiety, PTSD, and Depression

Anxiety Disorders

HRVB is a potential treatment for anxiety, phobia, and post‐traumatic stress disorder.


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Generalized anxiety disorder (GAD) is defined by disproportionate anxiety and worry the majority of the time for at least 6 months (DSM‐V, 2013).

Chronic over‐arousal results in fatigue and insomnia, which can be worsened by changes in their circadian rhythm due to their job ortravel (McGrady & Moss, 2013).


Patients perceive their worrying as outside their control. They present with physical (muscle tension) and cognitive symptoms (belief that worrying can prevent a negative event).

They are usually diagnosed with a second disorder (Beidel, Bulik, & Stanley, 2014).


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Specific phobia involves significant emotional distress, excessive anxiety or fear about an object or situation, that disrupts everyday performance.


DSM‐V lists five specifiers: animal phobias, natural environment phobias, blood/injection/ injury phobias, situational phobias, and other phobias (Beidel, Bulik, & Stanley, 2014).


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Post‐traumatic stress disorder (PTSD) is a response to a traumatic event like assault, military combat, or rape that may be experienced firsthand or observed.


PTSD is characterized by intrusion (patient re‐experiences the traumatic event), negative alterations in cognitions and mood (they cannot feel emotions like joy or sadness), hyperarousal, hypervigilance, an exaggerated startle response, and avoidance (evasion of stimuli linked to the trauma) (Beidel, Bulik, & Stanley, 2014).


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Biofeedback is efficacious for anxiety (Moss, 2016) and possibly efficacious for PTSD (Ginsberg et al., 2016).

Gevirtz, Lehrer, and Schwartz (2016) theorized that GAD results from deficient vagal tone and ineffective inhibition.


They also proposed that PTSD involves cortical overload, dominance of the unmyelinated vagus, and limbic plasticity that amplifies perception of threats.


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HRVB may produce clinical gains in these disorders by increasing vagal afferent nerve firing (Gevirtz, 2013).



Problem Study Design OutcomeAnxiety Reiner (2008) Single group pilot study that

examined HRVB + CBT, N = 24HRVB + CBT reduced anxiety, anger, and sleep latency

McCraty et al. (2009)

RCT that compared HRVB + stress management vs. wait list control, N = 65

HRVB + stress management improved cholesterol, glucose, heart rate, blood pressure, positive outlook, and overall psychological distress

Henriques etal. (2011)

RCT that compared HRVB vs. delayed treatment, N = 35

HRVB reduced anxiety on MASQ subscales

CBT = Cognitive Behavior Therapy, MASQ = Mood and Anxiety Symptom Questionnaire

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Problem Study Design OutcomePhobia Prigatano

(1973)Case study that examined the effectiveness of HRVB on spider phobia

Patient reduced spider avoidance

CBT = Cognitive Behavior Therapy, MASQ = Mood and Anxiety Symptom Questionnaire


Problem Study Design OutcomePTSD Zucker et al.

(2009)RCT that compared HRVB using a StressEraser + 6 BPM breathing vs. progressive muscle relaxation CD, N = 38 residents treated for substance abuse disorders

Both groups reduced PTSD symptoms on the PTSD and Posttraumatic stress Checklist-Civilian version

HRV + 6 BPM breathing reduced BDI compared to PMR

Ginsberg et al. (2010)

Pre-post study that evaluatedHRVB for veterans with and without PTSD (N = 10)

HRVB resulted in better informationprocessing

Tan et al. (2010)

RCT that compared HRV + TAU vs. TAU, N = 30 veterans with PTSD.

HRV + TAU increased HRV and reduced PTSD symptoms on the CAPS and PCL-S, while TAU did not improve on any measure

Reyes (2014) Case study PTSD symptoms on PCL scale improved 21%

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Depression

Major depressive disorder is diagnosed when five or more depressive symptoms, including sadness or loss of pleasure, are present for 2 weeks.


Depressed patients may sleep too much or too little, display psychomotor retardation or agitation, show change in weight or appetite, experience loss of energy, feel worthless or guilty, are unable to concentrate, think, or make decisions, and think repeatedly about death or suicide (DSM‐5, 2013).


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Multiple pathways to depression include polygenic, dysfunction involving the medial prefrontal cortex and limbic system, and environmental factors (McGrady & Moss, 2013).


Biofeedback is efficacious for depression (Shaffer & Zerr, 2016).

The effects may be mediated by the diaphragm's stimulation of vagal afferent nerves (Gevirtz, 2013).

This hypothesis is supported by findings that vagal nerve stimulation in some studies improved intractable depression.


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Problem Study Design OutcomeDepression Karavidas et al.

(2007)Single group study with no control, N = 11 with major depression

50% reduction in depressivesymptoms with an effect size comparable to antidepressants

Zucker et al. (2009)

Controlled pilot study, N = 38 with PTSD symptoms; HRVB (Stress Eraser) + DBT vs. DBT + relaxation

HRVB group achieved lower depression scores

Siepmann et al. (2008)

Open-label controlled study, N = 38; HRVB vs. active control

Depressed patients in the HRVB reduced depression scores, while healthy subjects in this group and the control condition showed no change

Patron et al. (2013)

RCT, N = 26 with depressive symptoms following cardiac surgery; HRVB vs. TAU

HRVB was superior to TAU and improvement was correlated with increased RSA

DBT = Dialectical Behavior Therapy, RCT = randomized controlled trialTAU = treatment as usual

Part 2: Blood PressureHypertension, Prehypertension,Preeclampsia

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Hypertension and Pre‐Hypertension

Hypertension (elevated blood pressure) is defined when systolic blood pressure is 140 mm Hg or higher and diastolic blood pressure is 90 mm Hg or higher.


The NIH Systolic Blood Pressure Intervention Trial (SPRINT) treatment of high‐risk hypertensive patients 50 years or older to a systolic blood pressure of 120 mmHg reduced cardiovascular events by 30% and all‐cause mortality by almost 25%, compared to a target of 140 mmHg (Medscape, 2015).


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About 90% of all cases of hypertension are primary hypertension, which is chronically elevated blood pressure not due to an identifiable cause. The remaining 10% are classified as secondary hypertension, which has an identifiable cause (Marieb & Hoehn, 2012).


The National Heart, Lung, and Blood Institute (NHLBI) advised that for adults over 50, systolic blood pressure is considerably greater risk factor for cardiovascular disease (CVD) than diastolic blood pressure.


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The NHLBI (2003) defined blood pressures between 120‐139 mmHg systolic and 80‐89 mmHg diastolic as prehypertensive.


Autonomic imbalance, involving sympathetic overactivity and parasympathetic underactivity, plays an important role in the development of essential hypertension.

Demographic factors (age, gender, and ethnicity) and psychological factors (depression, anger, and anxiety) influence blood pressure (McGrady & Moss, 2013).


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Biofeedback is efficacious for hypertension and prehypertension (McGrady, 2016).

Gevirtz, Lehrer, and Schwartz (2016) proposed that labile hypertension is mediated by a deficient baroreflex.

Improvement may be mediated by restored autonomic balance and increased baroreceptor reflex sensitivity (Gevirtz, 2013).


Device‐guided breathing is not empirically supported for hypertension (Zerr, Allen, & Shaffer, 2015).

A total of 10 randomized controlled studies were selected for analysis, which featured 573 hypertensive patients (56% male, average age of 56.6 years) training for an average of 7.7 weeks.


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Eight studies used a device known as RESPeRATE, while two used a Breathe with Interactive Music (BIM) device (both developed by InterCure Ltd., Israel).


Compared with controls, DGB resulted in non‐significant reductions with trivial effect sizes in both systolic (Cohen’s d = ‐0.12, SE = 0.09, z = ‐1.39, p = 0.16, 95% C.I. = ‐0.29 to 0.05) and diastolic (Cohen’s d = ‐0.16, SE = 0.09, z = ‐1.89, p = 0.06, 95% C.I. = ‐0.33 to 0.01) BP measures.


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Problem Study Design Outcome

Hypertension Elliott et al. (2004)

RCT that compared practice using a respiration device with conventional medical care, N = 149

15 mm Hg systolic reduction for slow breathing vs. 9 mm Hg reduction for control group after 8 weeks

Reinke et al. (2007)

RCT that compared HRVB vs. sham EEG attention control, N = 45

The HRVB group maintained blood pressure with less medication

Prehypertension Wang et al. (2009)

RCT that compared 0.1 Hz abdominal breathing + frontal SEMGB vs. 0.1 Hz breathing alone, N = 22 prehypertensive postmenopausal women

The combined group lowered SBP and DBP while the 0.1 Hz control only lowered SBP. The combined group lowered SBP more than the control group. SDNN significantly increased in both groups

Lin et al. (2012)

RCT that compared HRVB, slow abdominal breathing, and control, N = 43 prehypertensive young adults

The HRVB group reduced SBP and DBP more than the slowly abdominal breathing group. The HRVB group significantly increased BRS and SDNN

DBP = diastolic blood pressure, RCT = randomized controlled trial, SBP = systolic blood pressure, SEMGB = surface EMG biofeedback

Preeclampsia

Preeclampsia, also called pregnancy‐induced hypertension (PIH), is characterized by elevated blood pressure and proteinuria (abnormal levels of protein in the urine) following the 20th‐week of gestation.


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This disorder affects between 6‐8% of pregnancies and is one of the leading causes of fetal morbidity and mortality in the United States (Walling, 2004).


Preeclampsia is associated with the increased risk of acute renal failure, cerebrovascular and cardiovascular complications, separation of the placenta from the uterus, widespread formation of clots in small blood vessels, and maternal death (MacKay, Berg, & Atrash, 2001).


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While electrodermal biofeedback for preeclampsia is efficacious (Shaffer & Meehan, 2016), HRVB warrants a rating of possibly efficacious due to limited research.



Preeclampsia Cullin et al. (2013)

Nonrandom assignment in a multi-group study that compared bed rest, antihypertensive medication, and HRVB vs. historical control that included bed rest and antihypertensive medication, N = 47

No changes in DBP or SBP for either group. The HRVB group had fewer labor and delivery complications, and higher birth weight and gestational age than the TAU group.

DBP = diastolic blood pressure, SBP = systolic blood pressure,

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Part 3: Cardiovascular DisordersCongestive Heart Failure Coronary Artery Disease

Cardiovascular Disorders

HRV biofeedback shows promise in congestive heart failure and coronary artery disease.


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Congestive Heart Failure

Congestive heart failure involves dysfunction of the coronary ventricles or lower chambers.Failure of the left ventricle results in shortness of breath and fatigue, while failure in the right causes fluid to accumulate in the periphery and abdomen.



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Congestive heart failure involves dysfunction of one or both of the coronary ventricles or lower chambers.

Failure of the left ventricle results in shortness of breath and fatigue, while failure in the right causes fluid to accumulate in the periphery and abdomen.


Congestive heart failure is caused by cardiac factors, like myocardial damage, valvular disorders, arrhythmias, conduction defects, ischemia, and systemic factors, like disorders that increase CO2 demand and increase resistance to cardiac output (The Merck Manual, 2013).


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Coronary Artery Disease (CAD)

Coronary artery disease is characterized by reduced coronary artery circulation, whichis most often due to atheromas, deposits of lipid‐containing plaques on the inside lining of arteries.


HRVB is possibly efficacious for congestive heart failure and coronary artery disease (Moravec & McKee, 2016).

There is increasing evidence that HRVB may improve cardiac function by restoring autonomic balance (Gevirtz, 2013).


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This represents a paradigm shift from the earlier model of reducing SNS activation (Moravec & McKee, 2013).

Several studies have demonstrated the promise of HRVB in the treatment of congestive heart failure and coronary artery disease.



Congestive Heart failure

Swansonet al. (2009)

RCT that compared HRVB vs.quasi-false alpha-theta biofeedback, N = 29

Increased exercise tolerance for patients with left ventricular ejection fraction (LVEF) > 30%; no change in SDNN or quality of life

Moravec(2008); Moravec & McKee (2013)

Case studies in which patients received HRVB with stress management

viability of harvested cardiac tissue was equivalent to changes produced by LVAD

Coronary Artery Disease

Cowan et al. (2001)

RCT that compared HRV biofeedback + CBT vs. TAU, N = 129 ventricular fibrillation or asystole survivors

HRVB+ CBT reduced mortality 86%

Del Pozo et al. (2004)

RCT that compared HRVB vs. TAU, N = 63

SDNN increased for HRVB group, but did not change in the TAU group

Nolan et al. (2005)

RCT that compared HRVB + CBT vs. relaxation, N = 46

While both groups improved stress and depression scores, only the HRVB group’s improvement was correlated with vagal tone

CBT = Cognitive Behavioral Therapy, LVAD = left ventricular assist device, RCT = randomized controlled trial, and TAU = treatment as usual

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Part 4: Functional Gastrointestinal Disorders: Irritable Bowel Syndrome Recurrent Abdominal Pain

Functional Gastrointestinal Disorders

Functional gastrointestinal disorders are diverse and diagnosed by their symptoms.


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These patients show heightened visceral pain receptor sensitivity, so normal contraction or distention of the stomach produces discomfort.

They also show increased sensitivity to stressors. This should be expected since the same pathways transmit information about visceral pain and stress (McGrady & Moss, 2013).


Gevirtz, Lehrer, and Schwartz (2016) hypothesized that irritable bowel syndrome and recurrent abdominal pain are mediated by excessive sympathetic nervous system activity and extended parasympathetic withdrawal.

Gains from HRVB may be mediated by increased autonomic balance due to improved vagal tone (Gevirtz, 2013).


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HRVB has been successfully used to treat cyclic vomiting, irritable bowel syndrome, and recurrent abdominal pain.


Cyclic Vomiting

Cyclic vomiting syndrome (CVS) is relatively rare and is characterized by severe episodes of vomiting or nausea that are separated by periods of healthy GI function. CVS is most often seen in children and remits by adulthood. Adult CVS is associated withchronic marijuana use (The Merck Manual, 2013).


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Irritable Bowel Syndrome (IBS)

Irritable bowel syndrome (IBS) involves stomach discomfort or pain associated with a minimum of two additional symptoms: relief by bowel movements or changes in stool frequency or consistency (The Merck Manual, 2013).


Recurrent Abdominal Pain (RAP)

Chronic abdominal pain (CAP) occurs either continuously or periodically for more than 3 months.

Intermittent CAP is termed recurrent abdominal pain (RAP) and is seen in up to 10% of children and 2% of adults, mostly women.


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Almost all of these patients were undiagnosed following previous assessment (The Merck Manual, 2013).


Biofeedback is efficacious for IBI (Stern et al., 2016) and possibly efficacious for recurrent abdominal pain (Guiles et al., 2016). HRVB is not empirically supported for cyclic vomiting due to limited research.


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Problem Study Design OutcomeCyclicvomiting

Slutsker et al. (2010)

Case study in which HRVB was used

Vomiting was greatly reduced

Irritablebowel syndrome (IBS)

Dobbin et al. (2013)

RCT that compared HRVB vs. hypnosis

The HRVB groups was superior at 12 weeks post-treatment. For 61 refractory patients, both groups showed comparable improvement at 24 weeks follow-up

Recurrentabdominal pain (RAP)

Humphreys & Gevirtz (2000)

RCT that compared HRVB vs. CBT and family therapy, N = 64 children and adolescents

HRV biofeedback alone produced the strongest outcomes

Masters (2006) Case study in which HRVB was integrated into other interventions

Symptom log ratings significantly improved

Sowder et al. (2010)

HRVB vs. control, N = 30(20 HRVB and 10 comparison without FAP)

Improvement of symptom ratings was correlated with reductions in LF/HF ratio used to measure vagal tone

CBT = Cognitive Behavioral Therapy, RCT = randomized controlled trial

Part 5: Pain Disorders

Chronic Muscle Pain andFibromyalgia

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Chronic Muscle Pain

Chronic myofascial pain syndrome is a regional pain disorder that is characterized by trigger points, which are hyperirritable regions of taut bands of skeletal muscle in the muscle belly or associated fascia (connective tissue).



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Pressure on trigger points is painful. Trigger points can produce referred (remote) pain and tenderness, motor dysfunction, and autonomic changes.


Trigger points cannot be detected using SEMG electrodes, but can be identified using needle EMG electrodes and palpation (examination by feeling or pressing with the hand).


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Hubbard and Gevirtz have proposed that sympathetically‐mediated muscle spindle spasm may be the major local mechanism in myofascial pain.

An important implication of this theory is that muscle spindles may be activated by stress and anxiety.


Gevirtz's (2003) mediational model of muscle pain proposes that lack of assertiveness and resultant worry each trigger sympathetic activation.


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Gevirtz, Lehrer, and Schwartz (2016) hypothesized that fibromyalgia is mediated by dopamine depletion in afferent limbic projections to the hippocampus and substance P depletion in nociceptive afferents that project to the the dorsal horn of the spinal cord.


Increased sympathetic efferent signals to muscle spindles and overexertion can produce a spasm in the intrafusal fibers of the muscle spindle, increasing muscle spindle capsule pressure and causing myofascial pain.


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Biofeedback is efficacious for chronic muscle pain (Sherman, Tan, & Wei, 2016).


Problem Study Design OutcomeChronic Muscle Pain

Hallman et al.(2011)

RCT that compared HRVB to TAU, N = 24 diagnosed with stress-related chronic neck-shoulder pain

HRVB resulted in improved ratings of health (vitality, pain, and social functioning)

Vagedes et al. (2012)

RCT that compared stabilization exercise, HRVB, myofascial release, and a combination of all three treatments, N = 109diagnosed with musculoskeletal pain

Combined treatment produced greater improvements in pain and function than the separate interventions

TAU = treatment as usual

Gevirtz (2013) hypothesizes that HRVB improvement in autonomic balance may interfere with SNS innervation of trigger points through the mechanism of accentuated antagonism (Olshansky, Sabbah, Hauptman, & Colucci, 2008).


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Fibromyalgia (FM)

Fibromyalgia (FM) is a chronic benign pain disorder that involves pain, tenderness, and stiffness in the connective tissue of muscles, tendons, ligaments, and adjacent soft tissue.


The American College of Rheumatology (ACR) adult criteria include widespread pain for at least 3 months on both sides of the body and pain during gentle palpation on 11 of 18 tender points on neck, shoulder, chest, back, arm, hip, and knee sites.


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Patients also present with attentional deficits, depression, severe fatigue, headaches, impaired multitasking, irritable bowel syndrome, memory deficits, sleep disturbance, and temporomandibular muscle and joint pain (Donaldson & Sella, 2003; Tortora & Derrickson, 2014).


McGrady and Moss (2013) conceptualize FM as a “pain amplification disorder” produced by the twin mechanisms of allodynia and hyperalgesia (p. 187).

Allodyniameans that patients experience previously benign stimuli as painful.

Hyperalgesiameans patients experience mildly painful stimuli as severely painful.


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While an initial injury that damages tissue may sensitize the body through peripheral and central sensitization, in other cases there may be no identifiable precipitating event.

Sequelae of negative emotion and sleep deprivation amplify pain and impair cognitive performance.


Patients present with multiple tender points, which are distinct from trigger points. Tender points are located at a muscle's insertion (the tendinous attachment to a movable bone) instead of the muscle belly or associated fascia.


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Tender points are associated with local tenderness. When compressed, they produce local pain, but not the referred pain associated with trigger points. Pressure on tender points may increase overall pain sensitivity.


Fibromyalgia is sometimes confused with Myofascial Pain Syndrome (MPS) because both syndromes involve muscle tenderness and local pain during palpation.


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Trigger Points Tender Points

Local tenderness, taut band, local twitchresponse, jump sign

Local tenderness

Singular or multiple Multiple

May occur in any skeletal muscle Occurs in specific locations that are symmetrically positioned

May cause a specific referred pain pattern

Do not cause referred pain, but often increase total body pain sensitivity

Source: Alvarez & Rockwell (2002)

Patients may present with both fibromyalgia and MPS, and have both tender points and trigger points. Accurate diagnosis requires careful examination by an experienced clinician (Alvarez & Rockwell, 2002).


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Biofeedback is probably efficacious for fibromyalgia (Donaldson, 2016). HRVB is possibly efficacious due to limited research (Gevirtz, 2013).


Problem Study Design OutcomeFibromyalgia Hassett et al.

(2007)Open label trial with no control group, N = 12 diagnosed with FM

HRVB improved depression, pain, and sleep

Research has included HRVB as a treatment component in addition to exercise, cognitive therapies (Acceptance and Commitment Therapy and Cognitive Behavioral Therapy), and interventions to improve sleep habits.

The putative mechanism may be increased autonomic balance (Gevirtz, 2013).


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Part 6: Respiratory Disorders:

Asthma and COPD

Asthma

Asthma involves episodic reversible airway obstruction, chronic airway inflammation and hypersensitivity to stimuli (like allergens, cold air, exercise, and viral infection).


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The early phase response features smooth muscle spasm and excessive mucus secretion, which obstruct the airways.



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The late phase response involves inflammation, scar tissue formation, fluid accumulation, and death of the epithelial cells that line the bronchioles (Fox, 2016; Tortora & Derrickson, 2014).


While allergens, exercise, and drugs like aspirin can trigger asthma attacks, both acute and chronic stress can also precipitate asthma attacks in children diagnosed with this disorder.


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Attacks by bullies, family conflict, and academic difficulties can increase the risk of asthma attacks eight times (Sandberg et al., 2000).


Gevirtz, Lehrer, and Schwartz (2016) hypothesized that asthma may be mediated by hyperactivity of smooth pulmonary muscle, excessive parasympathetic tone, and inflammation ofthe airway (p. 201).


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While HRV biofeedback is probably efficacious for the treatment of asthma, there is a need for long‐term follow‐up data (Lehrer, 2016).

The mechanism may be increased autonomic balance, which reduces contraction of the bronchioles and mucus secretion (Gevirtz, 2013).




Asthma Lehrer et al., 2000;Lehrer et al., 2004

Randomized controlled design with placebo and wait-list controls, N = 94

reduced asthma medication,improved pulmonary function, fewer asthma symptoms and episodes, improved one full level of asthma severity

HRVB superior to control

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Chronic Obstructive Pulmonary Disease (COPD)

Chronic obstructive pulmonary disease (COPD) is a family of lung diseases that interfere with air flow. This is a progressive disorder and almost 50% of severe cases die within 10 years of initial diagnosis.


Chronic obstructive bronchitis and emphysema comprise COPD.


EMPHYSEMA

CHRONICBRONCHITIS

COPD

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Chronic obstructive bronchitis persists for at least 3 months and involves airway obstruction. Patients present with a productive cough and wheezing.


Emphysema involves damage and destruction of the air sac walls. The few surviving air sacs are larger and are less able to exchange gas. Patients present with wheezing and coughing(The Merck Manual, 2013).


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HRVB is possibly efficacious for COPD (Gilbert, 2016).

HRVB may produce functional gains by increasing autonomic balance (Gevirtz, 2013).


Problem Study Design OutcomeCOPD Giardino et al.

(2004)Multiple case study HRV biofeedback with pulse oximetry biofeedback, N = 20

HRVB superior to TAU. Improved exercise tolerance, gas exchangeefficiency, and quality of life.

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Part 7: Optimal Performance

Optimal Performance Applications

Biofeedback and neurofeedbackwarrant a rating of probably efficacious (Sherlin & Larson Ford, 2016).


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HRVB is possibly efficacious in baseball, basketball, dance, golf, and music.

The hypothetical mechanism might be increased vagal tone (Gevirtz, 2013).


Performance Study Design Outcome

Baseball Strack (2003) RCT that compared HRVB vs. control, N = 42 high school baseball players

HRVB group improved batting (60%) more than the control group (21%)

Basketball Paul & Garg (2012)

RCT that compared HRVB vs. placebo and control, N = 30 basketball players, university level and above

HRVB group improved on anxiety, coping self-efficacy, and performance compared to the placebo and control groups

Dance Raymond et al.(2005)

RCT that compared HRVB vs. alpha-theta neurofeedback and control, N = 24 ballroom and Latin dancers

HRVB and alpha-theta groups improved more than the control group, overall, and on different subscales

Gruzelier et al. (2014)

RCT that compared HRVB vs.alpha-theta neurofeedback, choreology instruction, and control; subjects were first-year contemporary dance conservatoire students

No improvement of dance performance, HRVB reduced anxiety, and this reduction was correlated with improvement in ratings of dance technique and artistry

Golf Lagos et al. (2008; 2011)

Two single case studies of resonance frequency HRVB, the second case was treated at a virtual reality golf center

Increase in golf performance and HRV (total, LF, and 0.1 Hz); decrease in anxiety, stress, and sensation-seeking symptoms after 10 weeks

Music Thurber (2006) RCT that compared HRVB + emotional self-regulation vs. control, N = 14 student musicians

HRVB group improved on the Music Performance Anxiety scale

RCT = randomized controlled trial

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Application Rating Hypothetical Mechanism

Psychological DisordersAnxietyPTSDDepression

EfficaciousProbably efficaciousEfficacious

Increased vagal toneIncreased vagal toneIncreased vagal tone

Blood Pressure HypertensionPrehypertensionPreeclampsia

Efficacious

Efficacious

Increased baroreceptor reflex sensitivityImproved autonomic balanceImproved autonomic balance

Cardiovascular DisordersCongestive Heart FailureCoronary Artery Disease

Possibly efficaciousPossibly efficacious

Improved autonomic balanceImproved autonomic balance

Functional gastrointestinal disorders Irritable bowel syndrome (IBS)Recurrent abdominal pain

EfficaciousPossibly efficacious


Pain DisordersChronic muscle painFibromyalgia (FM)

EfficaciousProbably efficacious


Respiratory DisordersAsthmaCOPD

Probably efficaciousPossibly efficacious


Application Rating Hypothetical Mechanism

Optimal PerformanceBaseballBasketballDanceGolfMusic

Possibly efficacious Increased vagal tone

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anxiety disorders: psychological disorders that include generalized anxiety disorder (GAD), panic states, phobia, and post‐traumatic stress disorder (PTSD).

asthma: episodic reversible airway obstruction, chronic airway inflammation and hypersensitivity to stimuli (like allergens, cold air, exercise, and viral infection). Chronic inflammation may scar the airway resulting in obstruction that does not reverse with medication.

chronic muscle pain: persistent localized pain that may be mediated by autonomic imbalance resulting in excessive sympathetic outflow to muscle spindles, resulting in trigger points.

chronic obstructive pulmonary disease (COPD): progressive respiratory disorder that is mainly caused by smoking tobacco, additional causes include cystic fibrosis, alpha‐1 antitrypsin deficiency, bronchiectasis (chronic abnormal bronchiole dilation), and rare bullous lung diseases (featuring thin‐walled sacs that contain air).

Glossary

congestive heart failure: condition where the heart cannot pump sufficient blood to meet the body's needs and can result in exercise intolerance, leg swelling, and shortness of breath.

coronary artery disease: progressive inflammatory disorder characterized by plaque build‐up in the coronary arteries, which restricts blood flow to the heart and causes heart attacks.

cyclic vomiting syndrome: recurring episodes of intense nausea and vomiting with periodic abdominal pain and headaches.

depression: psychological disorder characterized by sadness, loss of appetite, energy, and interests, and problems with concentration.

functional gastrointestinal disorders: persistent and recurring GI complaints, including abnormal GI muscular activity and discomfort or pain when digesting a meal due to abnormal GI tract functioning.

hypertension: elevated blood pressure where systolic blood pressure exceeds 140 mmHg and/or diastolic blood pressure exceeds 90 mmHg.

Glossary

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irritable bowel syndrome (IBS): functional syndrome characterized by cramping, abdominal pain, bloating, diarrhea, constipation, and changes in bowel habits.

prehypertension: systolic blood pressure from 130‐139 mmHg and/or diastolic blood pressure from 80‐89 mmHg.

recurrent abdominal pain (RAP): at least 3 episodes of often severe abdominal pain over a 3‐month period; diagnosed in up to 30% of children ages 4 to 12.

Glossary

Beidel, D. C., Bulik, C. M., & Stanley, M. A. (2014). Abnormal psychology. Upper Saddle River, NJ: Pearson Education, Inc.

Botha, C. A., Naqvi, H., Chua, Y. C., Knowles, C. H., & Aziz, Q. (2012). The effect of psychophysiological autonomic modulation on human oesophageal pain hypersensitivity. Gut, 60, A26 [abstract]. doi:10.1136/gut.2011.239301.53

Ching, J., Khan, S., White, P., Reed, J., Ramnarine, D., Sieradzan, K., & Sandeman, D. (2012). Long‐term effectiveness and tolerability of vagal nerve stimulation in adults with intractable epilepsy: A retrospective analysis of 100 patients. British Journal of Neurosurgery, 27(2), 228‐234.

Christopher, P. P., Leykin, Y., Appelbaum, P. S., Holtzheimer, P. E., 3rd, Mayberg, H. S., & Dunn, L. B. (2012). Enrolling in deep brain stimulation research for depression: Influences on potential subjects' decision making. Depression and Anxiety, 29(2), 139‐146.

Cullin, S., Gevirtz, R., Poelter, D., Cousins, L., Harpin, E., & Muench, F. (2013). An exploratory analysis of the utility of adding cardiorespiratory biofeedback in the standard care of pregnancy‐induced hypertension. Applied Psychophysiology and Biofeedback, 38(3), 161‐170. doi:10.1007/s10484‐013‐9219‐4

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