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.

Heart rate variability (HRV) is a medical index for morbidity and wellness. Lower HRV accompanies many illnesses; high HRV accompanies healthy states, resilience, and optimal functioning. Heart rate variability biofeedback (HRVB) uses real-time electronic feedback of the moment-to-moment changes in HRV to train patients to produce increases in HRV. Outcome studies on HRVB have shown therapeutic benefit for a wide variety of medical and mental health disorders. Lehrer and colleagues have published evidence-based protocols for HRV assessment and HRV treatment. Here, the authors review outcome studies on a sampling of common disorders: asthma, chronic muscle pain, depression, heart failure, hypertension, and posttraumatic stress disorder. HRVB offers promising therapeutic benefit for any medical or mental health disorder known to be accompanied by autonomic nervous system dysregulation.

Valid peripheral temperature measurements ensure the integrity of client assessment and biofeedback training. Accurate measurements require understanding of the signal and potential influences on measurement fidelity, and developing bulletproof monitoring procedures. In addition to their use in temperature biofeedback, thermistors can assist heart rate variability biofeedback practice and monitor breathing when a respirometer is not available.

The resonance frequency (RF) is the rate at which a system, like the cardiovascular system, can be activated or stimulated for maximal variability. Precise RF measurement is needed to standardize training protocols to help researchers determine the importance of RF breathing in achieving clinical and optimal performance outcomes. Lehrer and colleagues have developed and standardized a psychometrically reliable RF measurement protocol that can facilitate training and replication. This article provides a detailed description of their protocol and explains the nuanced decision-making process involved in identifying the RF. The validity and reproducibility of results using this protocol depend on quality control in (a) confirming that individuals successfully follow a breathing pacer, and (b) manually removing artifacts from data records. While this protocol requires an electrocardiogram or photoplethysmograph sensor and a respirometer, professionals should consider the addition of autonomic, musculoskeletal, and respiratory measures to better understand the patterns of physiological activity produced by different breathing rates.