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.

In vitro study on conditioned dental root surfaces: evaluation of wettability, smear layer, and blood clot adhesion.

Objectives: The aim was to investigate the efficacy of citric acid and ethylenediaminetetraacetic acid (EDTA)-based treatments on smear layer removal and blood clot formation and stabilization.

Method And Materials: After scaling and root planing, 126 root samples were divided into seven groups treated with: deionized water; saline; citric acid solution; Ultradent Citric Acid gel; EDTA solution; EDTA-based PrefGel; or untreated. Each group was divided into three subgroups: I for the evaluation of smear layer removal and surface wettability, II and III for the evaluation of blood clot formation and stabilization in static or dynamic rinsing conditions.

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.

Higher order spectral analysis of scalp EEG activity reveals non-linear behavior during rhythmic visual stimulation.

Objective: Flickering visual stimulation is known to evoke rhythmic oscillations in the electroencephalographic (EEG) activity, called steady-state visually evoked potentials (SSVEP). The presence of harmonic components in the EEG signals during SSVEP suggests the non-linearity of the visual-system response to rhythmic stimulation, but the nature of this behavior has not been deeply understood. The aim of this study is the quantitative evaluation and characterization of this non-linear phenomenon and its interference with the physiological alpha rhythm by means of spectral and higher order spectral analysis.

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.

EEG Analysis During Active and Assisted Repetitive Movements: Evidence for Differences in Neural Engagement.

Two key ingredients of a successful neuro-rehabilitative intervention have been identified as intensive and repetitive training and subject's active participation, which can be coupled in an active robot-assisted training. To exploit these two elements, we recorded electroencephalography, electromyography and kinematics signals from nine healthy subjects performing a 2×2 factorial design protocol, with subject's volitional intention and robotic glove assistance as factors. We quantitatively evaluated primary sensorimotor, premotor and supplementary motor areas activation during movement execution by computing event-related desynchronization (ERD) patterns associated to mu and beta rhythms.

Clinical state assessment in bipolar patients by means of HRV features obtained with a sensorized T-shirt.

The aim of this study is to identify parameters extracted from the Heart Rate Variability (HRV) signal that correlate to the clinical state in patients affected by bipolar disorder. 25 ECG and activity recordings from 12 patients were obtained by means of a sensorized T-shirt and the clinical state of the subjects was assessed by a psychiatrist. Features in the time and frequency domain were extracted from each signal.

Optimization of time-variant autoregressive models for tracking REM-non REM transitions during sleep.

The aim of this study was the optimization of Time-Variant Autoregressive Models (TVAM) for tracking REM-non REM transitions during sleep, through the analysis of spectral indexes extracted from tachograms. A first improvement of TVAM was achieved by choosing the best typology of forgetting factor in the analysis of a tachogram obtained during a sitting-to-standing test; then, a method for improving robustness of AR recursive identification with respect to outliers was selected by analyzing a tachogram with an ectopic beat. A variable forgetting factor according to the Fortescue method and a specific condition on the prediction error for recursive AR identification gave the best performances.