Multifractal analysis of heart rate variability in pregnancy during sleep.

Understanding the complex dynamics of heart rate variability (HRV) during pregnancy is crucial for monitoring both maternal well-being and fetal health. In this study, we use the Multifractal Detrended Fluctuations Analysis approach to investigate HRV patterns in pregnant individuals during sleep based on RR interval maxima (MM fluctuations). In addition, we study the type of multifractality within MM fluctuations, that is, if it arises from a broad probability density function or from varying long-range correlations.

A Systematic Comparison of High-End and Low-Cost EEG Amplifiers for Concealed, Around-the-Ear EEG Recordings.

Wearable electroencephalography (EEG) has the potential to improve everyday life through brain-computer interfaces (BCI) for applications such as sleep improvement, adaptive hearing aids, or thought-based digital device control. To make these innovations more practical for everyday use, researchers are looking to miniaturized, concealed EEG systems that can still collect neural activity precisely. For example, researchers are using flexible EEG electrode arrays that can be attached around the ear (cEEGrids) to study neural activations in everyday life situations.

Respiratory Sinus Arrhythmia (RSA) stress response in preschool age varies by serotonin transporter polymorphism (5-HTTLPR): A preliminary report.

The serotonin transporter promoter region polymorphism (5-HTTLPR) has been implicated in stress regulation, with increased stress reactivity often being found in carriers of the low-expressing short (S) allele. Nevertheless, the role of the 5-HTTLPR in influencing parasympathetic stress reactivity, as indexed by Respiratory Sinus Arrhythmia (RSA), is still unknown. This study examined, for the first time, whether the 5-HTTLPR was associated with variations in RSA response to maternal separation in a sample of 69 healthy 5-year-old children.

Information Retrieval from Photoplethysmographic Sensors: A Comprehensive Comparison of Practical Interpolation and Breath-Extraction Techniques at Different Sampling Rates.

The increasingly widespread diffusion of wearable devices makes possible the continuous monitoring of vital signs, such as heart rate (HR), heart rate variability (HRV), and breath signal. However, these devices usually do not record the "gold-standard" signals, namely the electrocardiography (ECG) and respiratory activity, but a single photoplethysmographic (PPG) signal, which can be exploited to estimate HR and respiratory activity. In addition, these devices employ low sampling rates to limit power consumption.

Assessing stress variations in children during the strange situation procedure: comparison of three widely used respiratory sinus arrhythmia estimation methods.

The respiratory sinus arrhythmia (RSA) is a well-known marker of vagal activity that can be exploited to measure stress changes. RSA is usually estimated from heart rate variability (HRV). This study aims to compare the RSA obtained with three widely adopted methods showing their strengths and potential pitfalls.

Exploration of the physiological response to an online gambling task by frequency domain analysis of the electrodermal activity.

Online gambling has dramatically increased over the last decades, thus the study of the underlying physiological mechanisms could be helpful to better understand related disorders. Specifically, physiological arousal is well-known to play a key role in gambling behavior. In the present study, unconventional frequency feature of the electrodermal activity (EDA) was extracted (EDASymp) and compared to the most common heart rate variability (HRV) spectral parameters (LF, HF, HF, LF/HF) to measure arousal during an online gambling session.

Bicoherence Interpretation in EEG Requires Signal to Noise Ratio Quantification: An Application to Sensorimotor Rhythms.

Objective: In the electroencephalogram (EEG) the quadratic phase coupling (QPC) phenomenon indicates the presence of non-linear interactions among brain rhythms that could affect the interpretation of their physiological meaning. We propose the use of the bicoherence as a QPC quantification method to understand the nature of brain rhythm interplay.

Methods: We firstly provide a simulation study to show under which condition of signal to noise ratio (SNR) the bicoherence is a reliable QPC quantifier and how to interpret the results.

Investigating the Optimal Baseline Positioning to Maximize Cognitive Experimental Outcome.

In emotional and cognitive research, the baseline is commonly used for standardization purposes in order to have a reference for the identification of the activation. Since no previous studies have investigated which moment of the experiment could be considered optimal for baseline evaluation, we designed an experimental protocol to analyze which time interval could be considered more effective in highlighting differences between the baseline state and the cognitive effort exhibited during tasks (specifically, reaction and working memory tasks). Several indexes were extracted from EEG signals during the visualization of the considered baseline stimuli and the execution of tasks.

Heart Rate Variability from Wearables: A Comparative Analysis Among Standard ECG, a Smart Shirt and a Wristband.

Heart Rate Variability (HRV) derived from standard one-lead electrocardiography (ECG) was compared with HRV computed by a commercial ECG shirt and with the inter-beat-intervals (IBI) measured by a research-grade photoplethysmographic (PPG) wristband. Signals from 8 subjects were recorded in three experimental phases: during sit; in upright position ("stand"); during controlled respiration. HRV and IBI from both the wearables were computed online (i.

Towards the development of physiological models for emotions evaluation.

In the last decades numerous researches have revealed a strong link between emotions and several physiological responses. However, the automatic recognition of emotions still remains a challenge. In this work we describe a novel approach to estimate valence, arousal and dominance values from various biological parameters (derived from electrodermal activity, heart rate variability signal and electroencephalography), by means of multiple linear regression models.