Purpose
Autonomic nervous system (ANS) functioning has been widely studied in relation to antisocial behavior, such as Conduct Disorder (CD). However, research in females is scarce and findings are inconsistent. This study investigated baseline ANS activity in CD children and adolescents and tested for sex differences. Furthermore, subgroups of CD were investigated: +/‐ Limited Prosocial Emotions (LPE), +/‐ comorbid internalizing disorders (INT).
Methods
Baseline ANS activity was measured by Heart Rate (HR), Heart Rate Variability (HRV; parasympathetic activity), Pre-Ejection Period (PEP; sympathetic activity), and Respiration Rate (RR). 659 females (296 CD, 363 controls) and 351 males (187 CD, 164 controls), aged 9–18 years participated.
Results
Baseline HR, HRV and PEP did not differ between CD subjects and controls in both sexes. RR was higher in CD participants than controls amongst females, but not males. LPE was unrelated to ANS activity, whereas females with CD + INT presented lower HRV.
Conclusions
These results suggest that baseline ANS activity is not a robust indicator for CD. However, deviant ANS activity – especially parasympathetic activity – was observed in CD females with internalizing comorbidity. The psychophysiological abnormalities observed in this subgroup are indicative of emotion regulation problems. Accordingly, this subgroup may require specific interventions.

Ambulatory wearable monitoring of human physiology is increasingly utilized in the fields of psychology, movement sciences, and medicine. With the rapid growth of available consumer- and research-oriented wearables, researchers are faced with a multitude of devices to choose from. It is unfeasible timewise for researchers to determine all relevant technical specifications, available signals, signal sampling details, and (raw) data availability, and conduct a search of studies regarding the reliability, validity, and usability of wearables. Thus, selection of wearables for a given study proves highly challenging and will often be unsystematic and uninformed. The 10-year research program Stress in Action initiated a publicly accessible database of wearable ambulatory monitoring devices. We outline the genesis and final structure of the first version of the Stress in Action Wearables Database (SiA-WD) and a summary of the characteristics of the wearables it currently contains. Furthermore, one short-term (2 days) and one long-term (3 months) scenario from the field of stress research are provided with walkthroughs of how the SiA-WD can help select the optimal wearable for a specific research project. Insights gathered include the scarceness of studies testing wearable user-friendliness, inconsistencies in reported validity statistics, and imprecise manufacturer documentation on recorded physiological data such as sampling rate (or window) of signals and parameter extraction. The SiA-WD is the first open-access database to simultaneously include physiological sampling information and technical specifications along with a systematic reliability, validity, and usability search. It will be iteratively expanded to facilitate informed and time-efficient wearable selection. For access to the database, see the following: https://osf.io/umgvp/.

Speech production interferes with the measurement of changes in cardiac vagal activity during acute stress by attenuating the expected drop in heart rate variability. Speech also induces cardiac sympathetic changes similar to those induced by psychological stress. In the laboratory, confounding of physiological stress reactivity by speech may be controlled experimentally. In ambulatory assessments, however, detection of speech episodes would be necessary to separate the physiological effects of psychosocial stress from those of speech. Using machine learning (https://osf.io/bk9nf), we trained and tested speech classification models on data from 56 participants (ages 18–39) under controlled laboratory conditions. They were equipped with privacy-secure wearables measuring thoracoabdominal respiratory inductance plethysmography (RIP from a single and a dual-band set-up), thoracic impedance pneumography, and an upper sternum positioned unit with triaxial accelerometers and gyroscopes. Following an 80/20 train-test split, nested cross-validations were run with the machine learning algorithms XGBoost, gradient boosting, random forest, and logistic regression on the training set to get generalized performance estimates. Speech classification by the best model per method was then validated in the test set. Speech versus no-speech classification performance (AUC) for both nested cross-validation and test set predictions was excellent for thorax–abdomen RIP (nested cross-validation: 96.6%, test set prediction: 98.5%), thorax-only RIP (97.5%, 99.1%), impedance (97.0%, 97.8%), and accelerometry (99.3%, 99.6%). The sternal accelerometer method outperformed others. These open-access models leveraging biosignals have the potential to also work in daily life settings. This could enhance the trustworthiness of ambulatory psychophysiology, by enabling detection of speech and controlling for its confounding effects on physiology.

Introduction: The resting ECG is the most commonly used tool to assess cardiac electrophysiology. Previous studies have estimated heritability of ECG parameters based on these snapshots of the cardiac electrical activity. In this study we set out to determine whether analysis of heart rate specific data from Holter ECGs allows more complete assessment of the heritability of ECG parameters.Methods and Results: Holter ECGs were recorded from 221 twin pairs and analyzed using a multi-parameter beat binning approach. Heart rate dependent estimates of heritability for QRS duration, QT interval, Tpeak–Tend and Theight were calculated using structural equation modeling. QRS duration is largely determined by environmental factors whereas repolarization is primarily genetically determined. Heritability estimates of both QT interval and Theight were significantly higher when measured from Holter compared to resting ECGs and the heritability estimate of each was heart rate dependent. Analysis of the genetic contribution to correlation between repolarization parameters demonstrated that covariance of individual ECG parameters at different heart rates overlap but at each specific heart rate there was relatively little overlap in the genetic determinants of the different repolarization parameters.Conclusions: Here we present the first study of heritability of repolarization parameters measured from Holter ECGs. Our data demonstrate that higher heritability can be estimated from the Holter than the resting ECG and reveals rate dependence in the genetic—environmental determinants of the ECG that has not previously been tractable. Future applications include deeper dissection of the ECG of participants with inherited cardiac electrical disease.

Respiratory sinus arrhythmia (RSA) is the heart period variability observed in synchrony with respiration. RSA amplitude is widely used in psychophysiological research to non-invasively index cardiac vagal activity. However, RSA measures are significantly affected by respiratory behavior, even in the absence of changes in cardiac vagal activity. Fifty-to-sixty percent of the variation in RSA can be attributed to respiration rate and tidal volume. This poses a notable challenge for ambulatory RSA measurement where respiratory behavior cannot be experimentally controlled and can show substantial variation. This pre-registered two-day ambulatory study (https://osf.io/57es4) compared four approaches to control for respiratory influences on RSA, to make an empirical recommendation on how to best capture cardiac vagal activity in daily life. We evaluated how well the RSA metric of each approach predicted (1) Minute-to-minute heart period, assumed to be predominantly governed by cardiac vagal activity, and (2) Perceived stress, positive affect, negative affect, and safety—states expected to elicit fluctuations in cardiac vagal activity— at smartphone prompts. The tidal volume-normalized RSA approach was optimal, explaining 1.47 times as much within-individual variance in heart period as that explained by uncontrolled-RSA. The need to use respiratory-controlled RSA was further highlighted by results on safety. Perceived safety was associated with uncontrolled-RSA (p = .033) but not with any of the controlled-RSA metrics. This relationship was driven by higher respiration rate co-occurring with lower safety. We recommend using tidal volume-normalized RSA in ambulatory research to avoid reporting spurious within-individual correlations between psychological states and cardiac vagal activity.