2503: Ch 4: heart rate variability

cardiac cells

• the sympathetic an parasympathetic (ANS) innervates the heart and regular HR

• the balance btw these systems affect the consistency in the heart rhythm

HRV

• increases between successive R-R intervals indicates an increase in parasympathetic stimulation

• decreases between successive R-R intervals indicates higher sympathetic stimulation

with regards to performance, a long-term increase in HRV seems to follow improvements in cardioR fitness

factors influencing HRV

external factors: behavioral factors

• sleep wake cycle, eating meals, mental meals, mental stress, physical stress

internal factors: physiological factors

• respiratory sinus arrhythmia, baroreceptor reflex regulation, thermoregulation, neuroendocrine secretion, circadian rhythms, sleep stages during the night

calculating HRV

time domain analysis

• SDNN- long term recordings- standard deviation of successive N-N intervals

• RMSSD- most common- sq root of the mean squared differences btw N-N intervals

frequency domain analysis

• calculated using the Fast Fourier transforms (FFT)

• very low frequency -.0033- .04 Hz- sympathetic activity

• low frequency -.04 - .15 Hz- sympathetic & parasympathetic activity

• high frequency 15.4 Hz - parasympathetic

clinical implication

HRV has been shown to be useful in identifying risk factors as well as diagnosing:

• diabetic neuropathy

• alcoholic neuropathy

• post cardiac transplant

• depression

• susceptible to SIDS

• poor survival in premature babies

• increased mortality

• risk of sudden cardiac death

• increased mortality post-MI

• congestive heart failure

• poorer survival in CHF

• COPD

measuring HRV in the field

several inexpensive smartphone applications can be used to accurately measure HRV using short

HRV & performance

time domain analysis of HRV has been shown to be an accurate measure of:

• training load

• recovery status

• fatigue

• readiness

• adaptation to training

training load calculated by HRV

• HRV has been shown to be a good indicator of overall training load

• after a single bout of exercise HRV reflects acute fatigue

training status effect on HRV

• after an acute bout of exercise highly trained runners recover HRV faster (<10 min vs >90 min)

• elite athletes show less long-term fluctuations in HRV as well as a higher baseline HRV

tracking perfromance changes

• increases in resting and post exercise HRV are found when positive adaptions in training have occured

identifying overreaching/overtraining

• current research is mixed regarding the use of HRV and diagnosing overtraining status

• with long term HRV collection, overreaching status can be identified by a downward trend in RMSSD or an increase in low frequency spectrum