Heart rate variability (HRV) represents fluctuations in the time intervals between successive heartbeats, which are termed interbeat intervals. HRV is an emergent property of complex cardiac-brain interactions and non-linear autonomic nervous system (ANS) processes. A healthy heart is not a metronome because it exhibits complex non-linear oscillations characterized by mathematical chaos. HRV biofeedback displays both heart rate and frequently, respiration, to individuals who can then adjust their physiology to improve affective, cognitive, and cardiovascular functioning. The central premise of the HRV biofeedback resonance frequency model is that the adult cardiorespiratory system has a fixed resonance frequency. Stimulation at rates near the resonance frequency produces large-amplitude blood pressure oscillations that can increase baroreflex sensitivity over time. The authors explain the rationale for the resonance frequency model and provide detailed instructions on how to monitor and assess the resonance frequency. They caution that patterns of physiological change must be compared across several breathing rates to evaluate candidate resonance frequencies. They describe how to fine-tune the resonance frequency following an initial assessment. Furthermore, the authors critically assess the minimum epochs required to measure key HRV indices, resonance frequency test-retest reliability, and whether rhythmic skeletal muscle tension can replace slow paced breathing in resonance frequency assessment.

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Researchers have investigated whether ultra-short-term (UST) heart rate variability values can replace traditional 5-minute values in clinical and optimal performance settings. Concurrent validity is the extent to which the results of a measurement correspond to a previously validated assessment of the same construct. Several studies either failed to specify their concurrent validity criteria or used an inappropriate statistical test. The authors proposed a rigorous standard and demonstrated that artifacted resting ultra-short-term heart rate variability values can achieve strong concurrent validity for diverse time-domain, frequency-domain, and nonlinear measurements in healthy undergraduates. Based on these findings, resting baselines as brief as 1 minute should be sufficient to measure heart rate, the standard deviation of the interbeat interval for normal beats (SDNN), and the square root of the mean squared difference of adjacent NN intervals (RMSSD) in clinical, optimal performance, and personal health assessment with individuals who resemble Truman State University undergraduates.

Valid electrodermal measurements ensure the integrity of client assessment and biofeedback training. Accurate measurements require understanding of the signal and potential artifacts (sources of contamination) and developing “bulletproof procedures.” Peper, Shaffer, and Lin have recommended the following guidelines for ensuring accurate psychophysiological monitoring: (a) understand the physiological mechanisms that generate the signal, (b) always record and inspect the raw signal because this will allow you to identify artifact, (c) question whether displayed values make sense (e.g., skin conductance levels that rapidly fluctuate, exceed 40 μS/cm2, or fall below 1 μS/cm2 should be suspect in a client who is sitting quietly), (d) recognize the appearance of common artifacts and how they alter derived measurements, and (e) intentionally create artifacts so that you can better recognize them (e.g., rhythmically move the fingers attached to a skin sensor, loosening or tightening the sensors if they are attached with the Velcro® finger straps, and review both the raw signal and calculated skin conductance values). This article reviews the anatomy and physiology, measurement procedures, sources of common artifacts and their control, tracking test for recording electrodermal activity, and common response patterns.

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