As shown, the peak value is proportional to the logarithm of the body mass to the ¼ power, log m1/4.
No group × time interaction effects were noted for log SDNN, log RMSSD, log LF power, log total power or resting heart rate (Table 3).
Log SDNN, log RMSSD, pNN50, log LF power, log HF power and log total power were positively, significantly and highly correlated (all p < 0.001; all r ≥0.69).
State anxiety measures in the total cohort at baseline were found to be directly proportional to resting heart rate and inversely proportional to pNN50, log RMSSD, log LF power, log HF power, and log total power (all p < 0.05).
Abbreviations: BPM, beats per minute; CIs, confidence intervals; HF, high frequency power; HRV, heart rate variability; LF, low frequency power; Log, logarithm; RMSSD, square root of the mean of the sum of the squares of differences between adjacent RR intervals; SDNN, standard deviation of all RR intervals; VLF, very low frequency power.
Abbreviations: BPM, beats per minute; HF, high frequency power; HOMA-IR, homeostasis model assessment of insulin resistance; HRV, heart rate variability; LF, low frequency power; Log, logarithm; M, mean; RMSSD, square root of the mean of the sum of the squares of differences between adjacent RR intervals; SDNN, standard deviation of all RR intervals.
Significant correlations were not found between EEG and headache attack duration, headache days last 3 months, phonophobia or photophobia Fig. 3 Linear regression lines are shown for fronto-central (open circles, solid line), parieto-occipital (triangles, broken line) and temporal (inverted triangles, dotted line) delta power (log-transformed y-axis).
For example, the decibel is a unit quantifying signal power log-ratios and amplitude log-ratios (of which sound pressure is a common example).
The relationship between mean values of SI and AIRg across three ethnic groups was assessed using power (log-log) regression analysis.
For linear regression to perform properly, data underwent log-log (power law fitting) or log-linear (exponential fitting) transformation prior to performing the piecewise fit.
Unlike their finite order counterparts, their spectral asymptotics are not of power-log-type but of log-type.
