What’s New in HRV Biofeedback? IIIMay 20, 2015 · Acceptance and CommitmentTherapy ... SD1:the...

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What’s New in HRV Biofeedback?Part III

Truman State University and Saybrook [email protected]

Fred Shaffer, PhD, BCB

Unit 4: Effective Home Practice Assignments

Effective Home Practice Assignments

Practice AssignmentAssign 20 minutes of practice a day and ask her to bring her weekly practice diary to your next session.

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Date Time Exercise Length How did you feel? What did you learn?12-10-2012

noon Lock-In 15 minutes

calm with greater awareness of my body

I can center myself by evokingfeelings of appreciation

12-11-2012

noon RF breathing 20 minutes

less stressed I should loosen my belt before starting breathing practice

12-12-2012

noon RF breathing 15 minutes

energized Breathing becomes more rhythmicwhen I reduce my effort


Explain the purpose of the exercise, demonstrate the skill in the clinic, and confirm that she can correctly perform it and agrees to practice it.

To build a collaborative relationship and empower your client, encourage her to find ways to improve the exercise or develop a different one.


Explain the purpose of the

exercise

Demonstrate the exercise

Ensure that your client can

perform it


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1. encourage clients to practice resonance frequency breathing during commonplace activities in diverse settings (commuting, at work, and at home)



RESPeRATE

iPhones Android phones

Breathing Zone MyCalmBeat


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http://www.heartmathstore.com/Mac OSX or Windows $19.95


http://bfe.org/new/try-our-breath-pacer-ez-air-plus/ Windows 32‐bit $19.95 after 30 days


2. assign 20 minutes a day of appropriate‐intensity aerobic activity, especially if yourclient is sedentary


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3. invite clients to monitor heart rate during daily activities and emotional states to increase mindfulness of stressors and theirphysiological responses to these challenges



Instant Heart Rate and What’s My Heart Rate (Android).


iCardio for the iPhone

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4. encourage emotional regulation practice to reduce parasympathetic withdrawal, cultivate the tend‐and‐befriend response, and increase resilience (e.g., the Instituteof HeartMath’s Lock‐In Technique®)


Institute of HeartMath Lock‐In Technique ® Instructions

“Try to focus your attention on the area around your heart. Maintain your heart focus and, while breathing, imagine that your breath is flowing in and out through the heart area. Breathe casually, just a little deeper than normal.”


“Now try to recall a positive emotion or feeling that makes you relaxed and comfortable. Find a positive feeling like appreciation, care, joy, kindness, or compassion. You can recall a time you felt appreciation or care. This could be the appreciation or care you feel towards a special person, a pet, a place you enjoy, or an activity that was fun for you.”


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“If you can’t feel anything it’s ok, just try to find a sincere attitude of appreciation or care. Continue to think of this positive feeling or emotion.”


5. Acceptance and Commitment Therapy (ACT) and compassion meditation may also aid emotionalregulation



6. computers, smartphones, and iPads can provide HRVB outside of the clinic

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7. portable HRV biofeedback devices allowpersonal training anywhere your client wants

Unit 5: BCIA Certificate of Completion in HRV Biofeedback

BCIA Certificate of Completion

BCIA offers a 15‐hour certificate of completion in HRV biofeedback that covers:

1. Cardiac Anatomy and Physiology2. Respiratory Anatomy and Physiology3. Autonomic Nervous System Anatomy

and Physiology4. Heart rate Variability5. HRV Instrumentation

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6. HRV Measurements7. HRV Biofeedback Strategies8. HRV Biofeedback Applications


A certificate of completion demonstrates that an applicant has successfully completed an approved and standardized didactic workshop based on fundamental science that meets rigorous academic standards.

Learn more about this new credential on BCIA’s website.

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

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

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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

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

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.

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.

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

References

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.

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

References

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

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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

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. Applied Psychophysiology and Biofeedback, 39, 300.

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

References

What’s New in HRV Biofeedback? IIIMay 20, 2015 · Acceptance and CommitmentTherapy ... SD1:the...

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