Unit 2: How to Measure the Resonance Frequency

Transcription

1 How to Increase the Impact of HRV Biofeedback Training Part 2 Fred Shaffer, PhD, BCB Truman State University Center for Applied Psychophysiology fredricshaffer@gmail.com Unit 2: How to Measure the Resonance Frequency How to Measure the Resonance Frequency Each individual has a unique resonance frequency caused by the delay in the baroreflex, which is a homeostatic mechanism that regulates blood pressure. 1

2 How to Measure the Resonance Frequency How to Measure the Resonance Frequency When clients breathe at this rate, which varies in adults from breaths/minute, they exercise the baroreflex. Heart rate (HR) and blood pressure (BP) oscillations are 180 o out of phase, the baroreflex is strongest, and RSA is greatest (DeBoer, Karemaker, & Strackee, 1987; Vaschillo et al., 2002). How to Measure the Resonance Frequency To find the breathing rate that maximizes the baroreflex, instruct your client to breathe at each target rate using a pacer for 3 minutes followed by a 1 minute buffer period. 2

3 How to Measure the Resonance Frequency How to Measure the Resonance Frequency This allows you to delete 1 minute of bad data from the start or end of your trial and still have the 2 minutes required to calculate peak totrough differences (HR Max HR Min). Always visually inspect your data for artifact and don t be misled by summary statistics. How to Measure the Resonance Frequency 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 minute for children. 3

4 How to Measure the Resonance Frequency Since most adults breathe between breaths per minute (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. How to Measure the Resonance Frequency How to Measure the Resonance Frequency 1. Record breathing at each respiration rate as a separate 3 minute 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. 4

5 How to Measure the Resonance Frequency 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. How to Measure the Resonance Frequency Lehrer et al. (2013) developed this protocol, which we have adapted. How to Measure the Resonance Frequency 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. 5

6 How to Measure the Resonance Frequency Christopher Zerr, former Lab Manager for the Truman Center for Applied Psychophysiology, provided technical support and supervised data collection to illustrate this protocol. How to Measure the Resonance Frequency The resonance frequency is the breathing rate that satisfies the majority of these parameters: 1. synchrony of the respirometer and heart rate signals 2. 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 Hz 4. smoothest and most regular heart rate waveforms How to Measure the Resonance Frequency 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 6

7 Finding the Resonance Frequency: 7.5 Finding the Resonance Frequency: 7.0 Finding the Resonance Frequency: 6.5 7

8 Finding the Resonance Frequency: 6.0 Finding the Resonance Frequency: 5.5 Finding the Resonance Frequency: 5.0 8

9 Finding the Resonance Frequency: 4.5 How to Measure the Resonance Frequency 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). How to Measure the Resonance Frequency RR Phase Max-Min LF % Peak SDRR Temp SCL Systolic Diastolic

10 How to Measure the Resonance Frequency Resonance frequency measurements using this protocol have a2 week test retest reliability of 0.73 (Wally et al., 2011). Unit 3: 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 and increase awareness of how a more balanced inner state feels. 10

11 The overarching purpose of HRVB training is to improve your client's ability to self regulate and to enhance both the quality of life and performance. Successful HRVB training integrates mindfulness, emotional self regulation, and resonance frequency breathing. Resonance Frequency Breathing Emotional Self Regulation Mindfulness 11

12 Mindfulness involves "paying attention in a particular way: on purpose, in the present moment, and nonjudgmentally" (Kabat Zinn, 1994). 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. 12

13 Emotional self regulation involves the selfmonitoring, 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 breaths per minute, to exercise the baroreceptor reflex. 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. 13

14 Consider HRVB instead of skin conductance or temperature biofeedback, since it can significantly lower SCL and raise hand temperature (Zerr et al., 2014). 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 Kubios 2.2 software. 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). 14

15 Infection Risk Mitigation: 1. Both the clinician and client should wash their hands before starting a session. 2. Clinicians should disinfect chair or recliner surfaces using wipes impregnated with biocidal agents that control bacteria and spores like Freshnit or Virusolve instead of ineffective 20% isopropyl alcohol (Hagedorn, 2014). 3. Liquid chemical sterilization should be used before and after each training session. Lowlevel disinfectants like Protex Disinfectant Spray can destroy a broad spectrum of bacteria, viruses, and fungi, including herpes, MRSA, and VRE. 15

16 4. The risk of infection transmission can be reduced by using disposable sensors. Clinical tips when you start HRV training: 1. Model effortless breathing and positive emotion for your client throughout each session. 2. The warmth and supportiveness of your relationship with your client is the foundation for successful biofeedback training (Taub & School, 1978). 16

17 From a polyvagal theory perspective, it creates a safe environment in which your client can practice alternatives to fight orflight, freezing, or parasympathetic withdrawal. 3. Emphasize passive volition (allowing) and effortlessness (your body feels as if it is breathing itself). 4. Allow your client to effortlessly increase the expansion and contraction of the abdomen, since this may increase heart rate variability. 17

18 Meehan et al. (manuscript in preparation) found that increasing abdominal excursion resulted in significantly greater HR Max HR Min, SDNN, and pnn50 values in undergraduates aged Effect of Abdominal Excursion on HRV Time Domain Measurements p =.03, η 2 = HR Max Min SDNN pnn50 Normal Excursion Increased Excursion 5. Since Zerr et al. (2015) 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. 18

19 6. Discourage effortful breathing that lowers end tidal CO2, because this can lower hand temperature, raise skin conductance, and reduce oxygen delivery to the brain. 7. For clinical work, consider an ECG sensor on the wrist or a PPG sensor on an earlobe or finger. Wrist placement 19

20 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. 20

21 9. 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 Hz (Ginsberg, Berry, & Powell, 2010, p. 54; McCraty et al., 2009). 21

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23 Meehan et al. (manuscript in preparation) found that low frequency power and peak to trough differences were the best predictors of SDNN and RMSSD in our undergraduates. 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. Index Peak to Trough LF Power Absolute Phase Peak Frequency SDNN 67% 82% NS NS RMSSD 67% 89% NS NS SDNN is the standard deviation of the normal (NN) sinus initiated IBI measured in ms. RMSSD is the square root of the mean squared difference of adjacent NN intervals. 23

24 The next two slides show a direct linear relationship between low frequency power (ms 2 ) and peak to trough differences and SDNN. Greater low frequency power and peak to trough differences were associated with higher SDNN values. 24

25 10. While it did not predict SDNN or RMSSD, in our undergraduates, some clients may prefer a display of the synchrony between respirometer and instantaneous heart rate signals. 11. You can provide SEMG biofeedback to reduce use of accessory muscles. 25

26 12. Once your client has mastered resonance frequency breathing, games can motivate practice 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. 26

27 13. 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. 27

28 Resonance Frequency Breathing Exercises the Baroreflex Increases HRV Emotional Self Regulation Increases Resilience Protects HRV 14. You can use sound with or without an animated pacer. The following selection is one of Wayne Martin s free HRV biofeedback ( 28

29 Each session might be structured as follows: 1. 5 minute discussion of practice and progress during sensor attachment 2. 3 minute baseline (no feedback) 3. six 3 minute HRV biofeedback segments, each followed by coaching 4. 3 minute baseline (no feedback) 5. assignment of practice How to select the starting respiration rate Based on your client s resonance frequency and the resting baseline, select an initial respiration rate for the animated pacing display. Since shaping is crucial to ensuring client success and motivation, choose a respiration rate within 1 or 2 breaths per minute of her baseline mean. 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. 29

30 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. 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. 30

31 Start recording data for 3 minutes. 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? Training success indicators: 1. breathing followed the pacing display 2. the two signals were rhythmic and regular 3. signal peaks and valleys coincided 4. signal energy increased within the low frequency band, centered around 0.1 Hz Training difficulty indicators: 1. your client could not follow the pacing display 2. the two signals were irregular 3. signal peaks and valleys were out of phase 4. your client used excessive effort 5. signal energy increased in the very low frequency or high frequency bands 6. your client displayed dysfunctional breathing 31

32 Training segment review Fit the entire 3 minute 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 32

33 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. If your client experienced difficulty, find a portion of the 3 minute 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. 33

34 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 Session review After your client has completed six 3 minute training segments, take a 3 minute 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. 34

35 Display the entire session Highlight what your client did correctly Identify where she needs more work How to Interpret HRV Measurements Brief Measurement Norms Nunan et al. (2010) reviewed normative data from short term HRV studies published after the Task Force report (1996). The 44 selected studies meeting their criteria involved 21,438 healthy adult participants. How to Interpret HRV Measurements LFnu and HFnu are normalized values calculated for brief measurements by dividing LF power or HF power by the sum of LF power + HF power. 35

36 How to Interpret HRV Measurements HRV Measure Mean (SD) Range Studies IBI (ms) 926 (90) SDNN (ms) 50 (16) RMSSD (ms) 42 (15) LF (ms 2 ) 519 (291) LFnu 52 (10) HF (ms 2 ) 657 (777) HFnu 40 (10) LF/HF 2.8 (2.6) Source: Nunan et al. (2010) N = 21,438 from 44 studies that reported short-term HRV in normally healthy adults How to Interpret HRV Measurements Optimal performance professionals should be interested in the Berkoff et al. (2007) short term norms from 145 elite track and field athletes who were measured before the 2004 U.S.A. Olympic Trials. How to Interpret HRV Measurements HRV Measure Men Women SDNN (ms) (28.03) (29.13) RMSSD (ms) (35.99) (35.82) pnn (9.46) (10.27) LF (ms 2 ) (915.31) (901.30) LFnu 0.48 (0.19) 0.38 (0.18) HF (ms 2 ) ( ) ( ) HFnu 0.52 (0.19) 0.82 (0.18) LF/HF 1.29 (1.17) 0.83 (0.85) LF/HFnu 1.29 (1.17) 0.83 (0.85) Source: Berkoff et al. (2007) N = 145 elite track-and-field athletes 36

37 How to Interpret HRV Measurements Zerr et al. (2014) reported 7 minute baseline measurements on 29 healthy undergraduates (18 male and 14 female), years of age. How to Interpret HRV Measurements Table 1. Cardiorespiratory measurements Measure Mean (SD) Systolic blood pressure (mmhg) (11.54) Diastolic blood pressure (mmhg) (11.64) Heart rate (beats/min) (11.42) Respiration rate (breaths/min) (2.96) Abdominal amplitude 1.07 (0.61) Accessory semg ( V) (6.30) Source: Zerr et al. (2015) N = 29 How to Interpret HRV Measurements Table 2. Time domain measurements Measure Mean (SD) HR Max HR Min (beats) (8.69) SDNN (ms) (34.70) NN (7.33) pnn50 (%) 0.12 (0.01) RMSSD (ms) (34.20) HRV triangular index (7.54) TINN (ms) (154.04) Source: Zerr et al. (2015) N = 29 37

38 How to Interpret HRV Measurements Table 3. Frequency domain measurements Measure Mean (SD) VLF power (ms 2 ) (310.04) LF power (ms 2 ) ( ) Ln LF power 6.22 (1.75) LFnu 0.61 (0.22) HF power (ms 2 ) (993.16) Ln HF power (ms 2 ) 5.69 (1.60) HFnu 0.40 (0.22) LF/HF 4.11 (4.77) Total power (ms 2 ) ( ) Source: Zerr et al. (2015) N = 29 How to Interpret HRV Measurements Table 4. Nonlinear measurements Measure Mean (SD) SD1 (ms) (26.89) SD2 (ms) (44.99) RPA: mean line length (6.16) RPA: maximum line length (159.65) RPA: recurrence rate (%) (11.79) RPA: determinism (%) (0.91) RPA: Shannon entropy 3.23 (0.29) Source: Zerr et al. (2015) N = 29 How to Interpret HRV Measurements Table 5. Nonlinear measurements Measure Mean (SD) DFA: (0.26) DFA: (0.19) Approximate entropy 1.05 (0.17) Sample entropy 1.20 (0.29) Source: Zerr et al. (2015) N = 29 38

39 How to Interpret HRV Measurements Umetani et al. (1998) published 24 hour norms for 260 healthy participants who ranged from years old. They reported that several HRV time domain indices declined with age. How to Interpret HRV Measurements Age (yr) SDNN (ms) SDANN (ms) SDNN Index (ms) pnn50 (%) RMSSD (ms) HR (beats/min) (38) 159 (35) 81 (20) 25 (13) 53 (17) 80 (10) (44) 137 (43) 72 (22) 18 (13) 43 (19) 79 (10) (32) 130 (33) 64 (15) 13 (9) 35 (11) 78 (7) (30) 116 (31) 60 (13) 10 (9) 31 (11) 78 (7) (27) 106 (27) 52 (15) 6 (6) 25 (9) 76 (9) (32) 111 (31) 42 (13) 4 (5) 22 (6) 77 (9) (22) 114 (20) 43 (11) 4 (5) 24 (7) 72 (9) (23) 95 (24) 37 (12) 3 (3) 21 (6) 73 (10) Source: Umetani et al. (1998) 24-hour norms N = 260 healthy adults How to Interpret HRV Measurements The Task Force report (1996) reported 24 hour norms for 144 healthy subjects and included cutoffs for increased risk of mortality. 39

40 How to Interpret HRV Measurements HRV Measure Mean (SD) Highly Depressed HRV Moderately Depressed HRV SDNN (ms) 141 (39) < 50 < 100 SDANN (ms) 127 (35) RMSSD (ms) 27 (12) HRV Triangular Index 37 (15) < 15 < 20 Source: Task Force (1996) 24-hour norms N = 144 healthy subjects How many heart rate variability biofeedback sessions are required? Many clients start to breathe effortlessly, increase parasympathetic activity, and improve autonomic balance within four 30 minute HRV biofeedback training sessions. However, they may require extended training and practice (10 or more sessions) to achieve maximum psychological, physiological, and performance gains (Lagos et al., 2011). 40

41 The most important HRV training elements: 1. education about the purpose, benefits, and process of HRV biofeedback 2. correction of breathing mechanics and modeling the breathing pattern and positive emotion that you want your client to learn 3. warm and supportive relationship with your client 4. gradual shaping of your client s respiration rate towards her resonance frequency 5. daily practice of HRVB skills for 20 minutes 41