Spectral differences in resting-state EEG associated to individual Emotional Styles.

The ability to manage the emotions has been associated to the Emotional Styles (ES), a set of coherent ways to deal with life's experiences. Recently, the Emotional Style Questionnaire (ESQ) has been proposed as a self-report mea-sure to assess the individual ES. The present study investigates the spectral differences in the resting-state EEG due to the individual ES, in order to support the psychometric reliability of the ESQ with associated neurophysiological measurements. In the alpha and beta band, Social Intuition showed significant and large (d > 0.8) effect sizes on the parietal and parieto-occipital regions, as well as a significant and large effect size in the gamma band on the pre-frontal region. In the beta band, Attention showed a significant and large effect size on the parieto-occipital region.

It's a Question of Methods: Computational Factors Influencing the Frontal Asymmetry in Measuring the Emotional Valence.

The prefrontal asymmetry (FA) in the alpha band is a well-known physiological correlate of the emotional valence. Several methods for assessing the FA have been proposed in literature, but no studies have compared their effectiveness in a comprehensive way. In this study we first investigated whether the association between FA and valence depends on the computational methods and then, we identified the best one, namely the one giving the highest correlation with the self-reports. The investigated factors were the presence of a normalization factor, the computation in time or frequency domain and the cluster of electrodes used. All the analyses were implemented on the validated DEAP dataset. We found that the number and position of the electrodes do not influence the FA, in contrast with both the power computation method and the normalization. By using a spectrogram-based approach and by adding a normalization factor, a correlation of 0.36 between the FA and the self-reported valence was obtained.

Yellow (Lens) Better: Bioelectrical and Biometrical Measures to Assess Arousing and Focusing Effects.

Colours can induce several psychological effects, conditioning perceptions, cognitive/emotional states and human performances. In this exploratory study we investigated the effect of a yellow light exposure, obtained filtering the ambient light with coloured glasses, on the human's psychological functioning. In particular we wanted to assess if people are more able to focus when exposed to a yellow light. We recorded EEG, SC, HR and gaze-related data from 16 subjects (50% split in experimental and control group) during the execution of a reactivity test (the Hazard Perception Test, HPT). Compared with the control group, the experimental group showed increases in concentration, focus, visual attention and arousal, as measured by increases of first fixation duration and Beta over-Alpha ratio (BAR) as well as by decreases of distraction, workload, and number of gaze revisits.

Emotion assessment using Machine Learning and low-cost wearable devices.

The advancement in bioelectrical measurement technologies and the push towards a higher impact of the Brain Computer Interfaces and Affective Computing in the daily life have made non-invasive and low-priced devices available to the large population to record physiological states. The aim of this study is the assessment of the abilities of the MUSE headband, together with the Shimmer GSR+ device, to assess the emotional state of people during stimuli exposure. Twenty-four pictures from the IAPS database were showed to 54 subjects and were evaluated in their emotional values by means of the Self-Assessment Manikin (SAM). Using a Machine Learning approach, fifty-two scalar features were extracted from the signals and used to train 6 binary classifiers to predict the valence and arousal elicited by each stimulus. In all classifiers we obtained accuracies ranging from 53.6% to 69.9%, confirming that these devices are able to give information about the emotional state.

Assessing an Automatic Procedure of Extraction of Physiological Parameters from Skin using Video Photoplethysmography.

Video Photoplethysmography (vPPG) allows for estimation of blood volume pulse (BVP) from the skin by means of a video camera recording at high frequency rate. The estimation procedure presents several drawbacks in its application to real world conditions, such as light changes or movements that often generate artifacts in the extracted BVP waveform. In addition, the process requires a skin segmentation algorithm to distinguish skin pixels from the background. To date, even the most refined skin segmentation algorithms still need a manual definition that could lead to incorrect pixel classification, and consequently to a decrease in the signal-to-noise ratio (SNR). We here propose a fully autonomic procedure able to extract BVP from video recordings of the skin in real world conditions.The experimental protocol is designed to record the signals of interest and to evaluate changes in the Autonomic Nervous System modulation of the heart during a baseline condition and a controlled breathing phase. Video recordings are gathered from 4 young healthy subjects (age: 21±1 years). vPPG signals are processed in order to extract the BVP waveform, and a peak detection algorithm detects pulse wave peaks that are then used to compute specific measures of heart rate variability (HRV).The procedure is successfully validated by comparing the extracted HRV measures against those extracted using a finger photoplethysmograph (fPPG) using three different skin segmentation algorithms from BVP signals.

Identification and Tracking of Physiological Parameters from Skin using Video Photoplethysmography.

In recent years, there has been a growing interest in video Photoplethysmography (vPPG), a technique able to estimate cardiovascular parameters from video recordings of the skin. Despite the growing interest in vPPG technology, there are still problems in extracting the correct waveform of blood volume pulse, mainly due to real world artifacts, such as changes in light condition and movement artifacts. Another important issue is the correct definition of skin against background. Therefore, we propose an algorithm of skin detection that is able to recognize skin pixels solid to variations of luminosity. We recorded the signals of interest during an experimental protocol designed to provide thermal stimulation and observe the resulting Autonomic Nervous System changes. Experimental data were gathered from 10 young healthy subjects (age: 21±2 years). Video recordings are processed using a band-pass filter and then an automatic algorithm of peak detection is applied to detect the pulse wave peaks, then used to estimate heart rate variability (HRV). The efficiency and stability of the algorithm are compared against finger-PPG waveforms. Preliminary results show an overall statistical agreement between time and frequency domain indexes. However, further efforts are required to improve the estimation of frequency components, particularly during rest.

A nonrigid registration of MR breast images using complex-valued wavelet transform.

In this paper, a fast, slice-by-slice, nonrigid registration algorithm of dynamic magnetic resonance breast images is presented. The method is based on a multiresolution motion estimation of the breast using complex discrete wavelet transform (CDWT): the pyramid of oriented complex subimages is used to implement a hierarchical phase-matching-based motion estimation algorithm. The resulting motion estimate is nonrigid and pixel-independent. To assess the method performance, we computed the correlation coefficient and the normalized mutual information between pre- and postcontrast images with and without realignment. The indices increased after using our approach and the improvement was superior to rigid or affine registration. A set of clinical scores was also evaluated. The clinical validation demonstrated an increased readability in the subtraction images. In particular, CDWT registration allowed a best definition of breast and lesion borders and greater detail detectability.

Application of the Ramanujan Fourier Transform for the analysis of secondary structure content in amino acid sequences.

OBJECTIVE: A novel method is presented for the investigation of protein properties of sequences using Ramanujan Fourier Transform (RFT). METHODS: The new methodology involves the preprocessing of protein sequence data by numerically encoding it and then applying the RFT. The RFT is based on projecting the obtained numerical series on a set of basis functions constituted by Ramanujan sums (RS). In RS components, periodicities of finite integer length, rather than frequency, (as in classical harmonic analysis) are considered. RESULTS: The potential of the new approach is documented by a few examples in the analysis of hydrophobic profiles of proteins in two classes including abundance of alpha-helices (group A) or beta-strands (group B). Different patterns are provided as evidence. CONCLUSIONS: RFT can be used to characterize the structural properties of proteins and integrate complementary information provided by other signal processing transforms.

Analysis of heart rate variability to predict patient age in a healthy population.

OBJECTIVES: To estimate age of healthy subjects by means of the heart rate variability (HRV) parameters thus assessing the potentiality of HRV indexes as a biomarker of age. METHODS: Long-term indexes of HRV in time domain, frequency domain and non-linear parameters were computed on 24-hour recordings in a dataset of 63 healthy subjects (age range 20-76 years old). Then, as interbeat dynamics markedly change with age, showing a reduced HRV in older subjects, we tried to capture age-related influence on HRV by principal component analysis and to predict the subject age by means of a feedforward neural network. RESULTS: The network provides good prediction of patient age, even if a slight overestimation in the younger subjects and a slight underestimation in the older ones were observed. In addition, the important contribution of non-linear indexes to prediction is underlined. CONCLUSIONS: HRV as a predictor of age may lead to the definition of a new biomarker of aging.

The importance of the reproducibility of oropharyngeal swallowing in amyotrophic lateral sclerosis. An electrophysiological study.

OBJECTIVE: To investigate electrophysiologically the reproducibility of oropharyngeal swallowing in patients with ALS. METHODS: We enrolled 26 ALS patients, both with and without clinical signs of dysphagia, and 30 age-matched controls. The reproducibility of the electrophysiological signals related to the oral phase (electromyographic activity of the submental/suprahyoid muscles) and the pharyngeal phase (laryngeal-pharyngeal mechanogram) of swallowing across repeated swallows was assessed. To do this we computed two similarity indexes (SI) by using previously described mathematical algorithms. RESULTS: The reproducibility of oropharyngeal swallowing was significantly reduced both in patients with and in those without clinical signs of dysphagia, with more marked alterations being detected in the dysphagic group. The SI of both phases of swallowing, oral and pharyngeal, correlated significantly with dysphagia severity and disease severity. CONCLUSIONS: In ALS different pathophysiological mechanisms can alter the stereotyped motor behaviors underlying normal swallowing, thus reducing the reproducibility of the swallowing act. A decrease in swallowing reproducibility could be a preclinical sign of dysphagia and, beyond a certain threshold, a pathological hallmark of oropharyngeal dysphagia. SIGNIFICANCE: Electrophysiological assessment is a simple and useful tool for the early detection of swallowing abnormalities, and for the management of overt dysphagia in ALS.

Assessment of beat-to-beat heart rate detection method using a camera as contactless sensor.

Video photoplethysmography (videoPPG) has emerged as area of great interest thanks to the possibility of remotely assessment of cardiovascular parameters, as heart rate (HR), respiration rate (RR) and heart rate variability (HRV). The present article proposes a fully automated method based on chrominance model, that selects for each subject the best region of interest (ROI) to detect and evaluate the accuracy of beat detection and interbeat intervals (IBI) measurements. The experimental recordings were conducted on 26 subjects which underwent a rest-to-stand maneuver. The results show that the accuracy of beat detection is slightly better during supine position (95%) compared to the standing one (92%), due to the maintenance of the balance that introduces larger motion artifact in the signal dynamic. The error in the measurement (expressed as mean±sd) of instantaneous heart rate is of +0.04 ±3.29 bpm in rest and +0.01±4.26 bpm in stand.

A method for coronary bifurcation centerline reconstruction from angiographic images based on focalization optimization.

A method for the reconstruction of a vessel centerline from angiographic images is outlined in this work. A typical coronary artery segment with bifurcations was emulated with a 3D printed static phantom and several angiograms were acquired at various angular positions on the C-Arm. The effectiveness of the reconstruction turned out to be largely influenced by the intrinsic parameters of the angiographic system, particularly the homogeneous coordinates system scaling factor λ. Therefore, recourse was made to a heuristic optimization method to estimate the optimal value of λ for each view. We measured the reliability of the reconstruction method by varying the fitness function of the optimization step and measuring the distances of 8 test points in comparison to the corresponding points identified in the µCT centerline. Preliminary results showed that, with an adequate number of views, the adoption of the optimal fitness function allowed the median distance error to be decreased below the acceptance threshold of 10%. As expected, the reliability of the method is improved by increasing the number of processed views.

Assessment of heart rate variability changes during dipyridamole infusion and dipyridamole-induced myocardial ischemia: a time variant spectral approach.

OBJECTIVES: We sought to evaluate changes in RR interval variability during dipyridamole infusion and dipyridamole-induced myocardial ischemia. BACKGROUND: Myocardial ischemia and the autonomic nervous system can be mutually interdependent. Spectral analysis of RR interval variability is a useful tool in assessing autonomic tone. METHODS: We used a time variant autoregressive spectral estimation algorithm that could extract spectral variables even in the presence of nonstationary signals. Two groups were considered: group A (patients with ischemia, n = 15) with effort or mixed angina, angiographically assessed coronary artery disease and positive exercise and dipyridamole echocardiographic test results, and group B (control subjects, n = 10) with normal exercise and dipyridamole echocardiographic test results. We investigated the following variables: RR interval mean and variance, low frequency (LF) and high frequency (HF) power in normalized units, LF ratio (LF/LFbasal power), HF ratio (HF/HFbasal power) and LF/HF ratio. For each test epoch, we calculated for group A and group B the mean value +/- SE of all indexes considered. Differences due to an effect either of group (ischemic vs. control) or of time (including both drug and ischemia effects) were analyzed by using analysis of variance for repeated measurements. RESULTS: Dipyridamole injection was characterized by a reduction of all spectral components in negative test. The LF ratio was the only variable able to discriminate patients with ischemia from control subjects (p < 0.05), whereas a time effect was evident for both mean RR interval and high frequency power in normalized units (p < 0.05). The LF ratio decreased in group B from 1 +/- 0.00 (basal) to 0.31 +/- 0.22 (peak), and increased in group A from 1 +/- 0.00 to 15.41 +/- 6.59, respectively. Results of an unpaired t test comparing the peak values of the two groups were also statistically significant (p < 0.01). CONCLUSIONS: Our data show that time variant analysis of heart rate variability evidences an increase in the low frequency ratio that allows differentiation of positive from negative test results, suggesting that the electrocardiogram may contain ischemia information unrelated to ST-T variations, even if their enhancement requires a more complex data processing procedure.

An averaging technique for the P300 spatial distribution.

INTRODUCTION: This article is part of the Focus Theme of Methods of Information in Medicine on "Biosignal Interpretation: Advanced Methods for Neural Signals and Images". OBJECTIVES: The main objectives of the paper regard the analysis of amplitude spatial distribution of the P300 evoked potential over a scalp of a particular subject and finding an averaged spatial distribution template for that subject. This template, which may differ for two different subjects, can help in getting a more accurate P300 detection for all BCIs that inherently use spatial filtering to detect P300 signal. Finally, the proposed averaging technique for a particular subject obtains an averaged spatial distribution template through only several epochs, which makes the proposed averaging technique fast and possible to use without applying any prior training data as in case of data enhancement technique. METHODS: The method used in the proposed framework for the averaging of spatial distribution of P300 evoked potentials is based on the statistical properties of independent components (ICs). These components are obtained by using independent component analysis (ICA) from different target epochs. RESULTS: This paper gives a novel averaging technique for the spatial distribution of P300 evoked potentials, which is based on the P300 signals obtained from different target epochs using the ICA algorithm. Such a technique provides a more reliable P300 spatial distribution for a subject of interest, which can be used either for an improved spatial selection of ICs, or more accurate P300 detection and extraction. In addition, the experiments demonstrate that the values of spatial intensity computed by the proposed technique for P300 signal converge after only several target epochs for each electrode allocation. Such a speed of convergence allows the proposed algorithm to easily adapt to a subject of interest without any additional artificial data preparation prior the algorithm execution such in case of data enhancement technique. CONCLUSION: The proposed technique averages the P300 spatial distribution for a particular subject over all electrode allocations. First, the technique combines P300-like components obtained by the ICA run within a target epoch in order to obtainan averaged P300 spatial distribution. Second, the technique averages spatial distributions of P300 signals obtained from different target epochs in order to get the final averaged template. Such an template can be useful for any BCI technique where spatial selection is used to detect evoked potentials.

Quantification of ventricular repolarization heterogeneity during moxifloxacin or sotalol administration using [Formula: see text]-index.

Drug-induced alterations of ventricular heterogeneity must be limited to avoid induction of lethal ventricular arrhythmias. In here, a new parameter called [Formula: see text]-index, able to measure the standard deviation of myocites' repolarization times, was evaluated after moxifloxacin and sotalol administration. The two drugs are known to provide different alteration of the QT interval length ranging from subtle (moxifloxacin) to evident (sotalol). In fact, while the former is employed as active-comparator in thorough QT studies, the latter might induce torsades de pointes. 24 h Holter ECGs of 39 (sotalol) and 68 (moxifloxacin) healthy subjects were retrospectively analyzed. The recordings were performed after infusion of the drugs and after the placebo (moxifloxacin) or at baseline (sotalol). The corrected QT interval (QTc) was included as well in the study, for a direct comparison. In both populations, [Formula: see text]-index and QTc increased along with the drugs' serum concentration and were statistically different from values in the placebo arm or at baseline (p < 0.05).With sotalol, the maximum value of [Formula: see text]-index occurred, on average, after 5.64 h from the infusion, whereas for QTc after about 4.27 h. The two metrics displayed evident changes ([Formula: see text]-index: 27.79 ms ± 4.89 ms versus 60.13 ms ± 18.52 ms; QT corrected: 387.07 ms ± 19.84 ms versus 437.76 ± 32.05 ms; p < 0.05). Regarding moxifloxacin, maximum values were reached, on average, 5.01 h after administration for [Formula: see text]-index (30.70 ms ± 8.32 ms versus 40.48 ms ± 7.61 ms; p < 0.05), and 4.37 h for QTc (404.29 ms ± 29.05 ms versus 426.77 ± 36.67 ms; p < 0.05). They were statistically different from baseline values. With both drugs, the maximal percent variation after administration was higher for [Formula: see text]-index than QTc (moxifloxacin: 34.56% ± 24.60% versus 5.56% ± 2.98% ; sotalol: 114.77% ± 33.15% versus 12.13% ± 2.85% ; p < 0.05).The study suggests that the standard deviation of the ventricular repolarization times, as quantified by the [Formula: see text]-index, might be an effective measure of spatial heterogeneity.

Tuning of a deformable image registration procedure for skin component mechanical properties assessment.

Several studies report the mechanical properties of skin tissues but their values largely depend on the measurement method. Therefore, we investigated the feasibility of recognizing the cellular constituents mechanical properties of pigmented skin by Confocal Laser Scanner Microscopy (CLSM). With this purpose, an healthy volunteer was examined in three areas nearby a pigmented skin lesion in two configurations: deforming and non deforming the nevus. The tissue displacement of the nevus was then assessed by means of deformable registration of the images in these two configurations. There are several registration strategy able to overcome this task, among them, we proposed two methods with different deformation models: a Free Form Deformation (FFD) model based on b-spline and a second one based on Demons Registration Algorithm (DRA). These two strategies need the definition of several parameters in order to obtain optimal registration performances. Thus, we tuned these parameters by means of simulated data and evaluated their registration abilities on the real in vivo CLSM acquisitions in the two configurations. The results showed that the registration using DRA had a better performance in comparison to the FFD one, in particular in two out of the three areas the DRA performance was significantly better than the FFD one. The registration procedure highlighted deformation differences among the chosen areas.

Prognostic implications of detection of troponin I in patients with unstable angina pectoris.

In our study, troponin I was not a predictor of cardiac events and a negative troponin I test did not exclude the presence of severe coronary artery disease. A positive troponin I test in patients with unstable angina identified a subgroup with probable, more active coronary disease (with higher levels of C-reactive protein).

The therapeutic activity of diftalone in rheumatoid arthritis: crossover comparison with indomethacin.

A multi-centre double-blind crossover study was carried out in 70 hospitalised patients with rheumatoid arthritis to compare the activity of diftalone, a new anti-inflammatory agen, with that of indomethacin. Patients received either 750 mg. diftalone or 100 mg. indomethacin daily for 2 weeks and were then crossed over to the alternative treatment for a further 2 weeks. Routine clinical and laboratory assessments of disease activity were carried out before the start of the trial and after each treatment period. The results indicate that both drugs produced a favourable response and that there was no statistically significant difference between them in the parameters measure, except for the erythrocyte sedimentation rate which fell only after the administration of diftalone. Patient and physician assessments on the course of the disease were in general agreement and were favourable to the same extent for both treatments. Both products were well tolerated and there were few reports of side-effects.

Pole-tracking algorithms for the extraction of time-variant heart rate variability spectral parameters.

Various algorithms of autoregressive (AR) recursive identification make it possible to evaluate power spectral distribution in correspondence with each sample of a time series, and time-variant spectral parameters can be calculated through the evaluation of the pole positions in the complex z-plane. In traditional analysis, the poles are obtained by zeroing the denominator of the model transfer function, expressed as a function of the AR coefficients. In this paper, two algorithms for the direct updating and tracking of movements of poles of an AR time-variant model on the basis of the innovation given to the coefficients are presented and investigated. The introduced algorithms are based upon 1) the classical linearization method and 2) a recursive method to compute the roots of a polynomial, respectively. In the present paper, applications in the field of heart rate variability (HRV) signal analysis are presented and efficient tools are proposed for quantitative extraction of spectral parameters (power and frequency of the low-frequency (LF) and high-frequency (HF) components) for the monitoring of the action of the autonomic nervous system in transient patho-physiological events. These computational methods seem to be very attractive for HRV applications, as they inherit the peculiarity of recursive time-variant identification, and provide a more immediate comprehension of the spectral process characteristics when expressed in terms of poles and AR spectral components.

Time-variant power spectrum analysis for the detection of transient episodes in HRV signal.

A time-variant algorithm of autoregressive (AR) identification is introduced and applied to the heart rate variability (HRV) signal. The power spectrum is calculated from the AR coefficients derived from each single RR interval considered. Time-variant AR coefficients are determined through adaptive parametric identification with a forgetting factor which obtains weighed values on a running temporal window of 50 preceding measurements. Power spectrum density (PSD) is hence obtained at each cardiac cycle, making it possible to follow the dynamics of the spectral parameters on a beat-by-beat basis. These parameters are mainly the LF (low frequency) and the HF (high frequency) powers, and their ratio LF/HF. These together account for the balanced sympatho-vagal control mechanism affecting the heart rate. This method is applied to subjects suffering from transient ischemic attacks. The time variant spectral parameters suggest an early activation of LF component in the HRV power spectrum. It precedes by approximately 1.5-2 min the tachycardia and the ST displacement, generally indicative of the onset of an ischemic episode. The results suggest an arousal of sympathetic system before the acute attack.