ANALYSIS OF FACTORS INFLUENCING THE USE OF HEART

ANALYSIS OF FACTORS INFLUENCING THE USE OF HEART

ANALYSIS OF FACTORS INFLUENCING THE USE OF HEART RATE VARIABILITY FOR EVALUATION OF AUTONOMIC NERVOUS FUNCTION IN MIND/BODY AND ACUPUNCTURE RESEARCH. Shin Lin*#+, Zhong-Yuan Shen*+, Tim Ross*#, Gaetan Chevalier*#, and Kangmin Shu*+. *International Alliance for Mind-Body Signaling & Energy Research # Departments of Developmental & Cell Biology and Biomedical Engineering, and Susan Samueli Center for

Complementary and Alternative Medicine, University of California, Irvine, CA 92697-2300 + Qigong Research Institute, Shanghai University of Traditional Chinese Medicine. ABSTRACT Heart rate variability (HRV) analysis is becoming an increasingly common method to non-invasively evaluate autonomic nervous function. In many studies, low frequency variability (LF, < 0.15 Hz as shown in the power spectrum produced by fast Fourier transformation) is taken as an indicator of sympathetic function and high frequency variability (HF, > 0.15 Hz)

as an indicator of parasympathetic function. To examine how HRV can be applied to the study of physiological changes associated with mind/body practices and acupuncture therapy, we used a custom-made Holter system (made by PI Instruments, Shanghai) with the capability of simultaneous recording of electrocardiography (EKG) and respiratory pattern (measured with chest and abdominal straps with stretch transducers). Based on studies on over 20 control subjects and 15 mind/body practitioners, we found that the following are important factors that influence HRV. First, the frequency of the breathing cycle influences the frequency of the HRV peak produced by respiratory sinus arrhythmia (RSA). Thus, a mind/body practitioner with a heart rate of 60 beats per minute will produce a HF peak at 0.2 Hz by regulating breathing at the rate of 12 cycles per minute, and a LF peak at 0.1 Hz when the breathing rate is slowed down to 6 cycles per minute. This shift from HF to LF is not necessarily a reflection of changing from a state of relaxation to a state of stress (i.e. higher parasympathetic to higher sympathetic function). Furthermore, the appearance of multiple HF peaks may be produced by

uneven breathing patterns during the measurement period (e.g., 3 different peaks produced by breathing at 8, 12, and 16 cycles per minute at different time intervals), thereby complicating the analysis of the power spectrum. On the other hand, we have also found in some cases involving younger subjects what appeared to be harmonics at higher frequencies even though they were strictly controlling their breathing at a single rate. For example, a subject breathing at a steady rate of 6 cycles per minutes (0.1 Hz) could still produce peaks at 0.2, 0.3, 0.4 Hz, etc., with diminishing amplitude in both the power spectra of the HRV and of the breathing pattern. Second, the size of the HRV peak produced by RSA is dependent not just on the tidal volume of each breath, but also on the posture of the subject. For instance, a subject breathing at a controlled rate and volume will show a larger peak in the sitting position compared to the standing position, and an even larger peak in the supine position. Therefore, it is difficult to compare directly the HRV of a subject during standing meditation and during sitting meditation. On the other hand, we did find that for those subjects who were in the sitting position throughout the

experiment, their HF peak tended to increase in size during meditation compared to resting periods before and after the practice. Third, under the same conditions, younger subjects (20-25 year old in this study) generally show a larger RSA peak compared to older subjects (50-70 year old). This effect often overshadows differences based on other considerations, such as years of experience in mind/body practice. In conclusion, this study shows that HRV analysis can be a useful tool for assessing autonomic nervous function in mind/body and acupuncture research, but great care must be taken to control for all of the factors indicated above. (Supported by a grant from the Rockefeller-Samueli Center for Research in Mind-Body Energy, and the Joseph and Sou-Lin Lee Endowment for Traditional Chinese Medicine Research). Introduction Heart rate variability (HRV) analysis of electrocardiogram (EKG) is

becoming an increasingly common method to non-invasively evaluate autonomic nervous function. In many studies, low frequency variability (LF, < 0.15 Hz as shown in the power spectrum produced by fast Fourier transformation) is taken as an indicator of sympathetic function and high frequency variability (HF, > 0.15 Hz) as an indicator of parasympathetic function. To examine how HRV can be applied to the study of physiological changes associated with mind/body practices and acupuncture therapy, we used a custom-made Holter monitor system (developed jointly with the Qigong Research Institute of Shanghai University of Traditional Chinese

Medicine and PI Instruments, Shanghai) with the capability of simultaneous recording of electrocardiography (EKG) and respiratory pattern (measured with chest and abdominal straps with stretch transducers). Hardware and Software Respiration-Dependent Peak at Different Breathing Frequencies 0.1 Hz at 6 cycles/min. , tidal volume of 1000 mL, seated, HR=60

0.2 Hz at 12 cycles/min., tidal volume of 1000mL, seated, HR=60 0.4 Hz at 24 cycles/min., tidal volume of 1000mL, seated, HR=60 Multiple Respiration-Dependent Peaks Generated by Breathing at Two Frequencies

JL Breathing frequencies of 0.1 & 0.2 Hz JT breathing frequencies of 0.1 & 0.2 Hz Multiple Peaks at Single Breathing Frequency

HRV at Lying Position JT JL HRV at Sitting Position JL JT

HRV at Standing Position JL JT HRV at Different Tidal Volume 6 times a min. @ 1L 6 times a min. @ 2L

HRV During Different Stages of Meditation First 5min. Second 5 min. Third 5 min. CONCLUSION Frequency of HRV peaks in power spectrum is dependent

on breathing frequency. Power of HRV peaks in power spectrum is dependent on breathing tidal volume and posture. Other factors such as age, cardiac health, drug addiction, etc., also affect HRV peaks. Careful control of above factors is critical in the use of HRV analysis for monitoring sympathetic and parasympathetic functions in mind-body and acupuncture research.

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