Contactless measurements of liquid sample electrical conductivity for estimating specific absorption rate in MR applications

Specific Absorption Rate (SAR) is the dosimetric parameter currently used as standard in the safety recommendation reports [1] for Magnetic Resonance Imaging (MRI) procedures. With the employment of MR systems with high field strengths (from 3T up to 8T), the study of the potential radiofrequency (RF) effects on the biological tissues due to higher radiofrequency, has a particular relevance [2]. Bottomley et al. [3] described a theoretical method to estimate the radiofrequency power deposition during MR exams, based on the sample geometry, the magnetic field radiofrequency, the MR sequence used (its pulse width, repetition time and flip angle) and, finally, the sample electrical conductivity. In this work we develop a liquid sample dielectric properties measurement system based on the evaluation of the resonance frequency and quality factor of a resonant circuit composed by a home-made coil. The major advantage of this method is the contactless between the liquid sample and the measurement electrode. We perform the measurement at 63.85MHz, corresponding to a 1.5T clinical MR environment, but this method can be used for measurements in the whole RF range, tuning the resonant circuit on the desired frequency

Automatic analysis of speech F0 contour for the characterization of mood changes in bipolar patients

da inserireBipolar disorders are characterized by a mood swing, ranging from mania to depression. A system that could monitor and eventually predict these changes would be useful to improve therapy and avoid dangerous events. Speech might convey relevant information about subjects' mood and there is a growing interest to study its changes in presence of mood disorders. In this work we present an automatic method to characterize fundamental frequency (F0) dynamics in voiced part of syllables. The method performs a segmentation of voiced sounds from running speech samples and estimates two categories of features. The first category is borrowed from Taylor's Tilt intonational model. However, the meaning of the proposed features is different from the meaning of Taylor's ones since the former are estimated from all voiced segments without performing any analysis of intonation. A second category of features takes into account the speed of change of F0. In this work, the proposed features are first estimated from an emotional speech database. Then, an analysis on speech samples acquired from eleven psychiatric patients experiencing different mood states, and eighteen healthy control subjects is introduced. Subjects had to perform a text reading task and a picture commenting task. The results of the analysis on the emotional speech database indicate that the proposed features can discriminate between high and low arousal emotions. This was verified both at single subject and group level. An intra-subject analysis was performed on bipolar patients and it highlighted significant changes of the features with different mood states, although this was not observed for all the subjects. The directions of the changes estimated for different patients experiencing the same mood swing, were not coherent and were task-dependent. Interestingly, a single-subject analysis performed on healthy controls and on bipolar patients recorded twice with the same mood label, resulted in a very small number of significant differences. In particular a very good specificity was highlighted for the Taylor-inspired features and for a subset of the second category of features, thus strengthening the significance of the results obtained with patients. Even if the number of enrolled patients is small, this work suggests that the proposed features might give a relevant contribution to the demanding research field of speech-based mood classifiers. Moreover, the results here presented indicate that a model of speech changes in bipolar patients might be subject-specific and that a richer characterization of subject status could be necessary to explain the observed variability

QRS Complex Separation from Convolutive Mixtures of Biolectrical Signals Acquired by Wearable Systems

Independent component analysis (ICA) has been widely used to remove artefacts from multichannel biomedical signal acquisitions under the hypothesis that there is statistical independence among the original sources. However, the basic ICA model does not take into account the influence on the mixing process of the different paths from the signal sources to the sensors In this study we propose a convolutive mixtures model in order to overcome the limitations of the basic ICA approach. The independent components are estimated in the frequency domain, where the convolutive model can be solved through an instantaneous mixing model. The signals are reconstructed back to the observation space resolving the ICA model ambiguities. Simulations are carried out to optimize of the proposed method for convolutive mixtures of electrocardiographic (ECG) and motion artefacts signals. The algorithm is tested on real ECG signals acquired by wearable systems in order to preserve the QRS complex when the signals are degraded by real life conditions of acquisition

Computational Analysis of a Radiofrequency Knee Coil for Low-Field MRI Using FDTD

Magnetic resonance imaging (MRI) is essential for the diagnosis and treatment of musculoskeletal conditions. Low-field (< 0.5T) imaging is a cost-effective alternative to more expensive high-field strength imaging due to the inexpensive setting, greater patient comfort and better safety profile. On the other hand, if compared with high-field body scanners, the low-field scanners produce poor-quality images with lower signal-to-noise ratio. Especially in low-field MR, receiver coil performance plays a significant role in image quality. Coil performance is generally evaluated using classical electromagnetic theory, but when the coil is loaded with a sample, an analytical solution is extremely difficult to derive, so that a trial-and-error approach is often followed. Numerical methods have been proposed in literature as good alternatives to predict MRI coil performance. In this study the performance of a knee coil for low-field (0.5 T) MR scanners is analyzed using workbench tests and numerical simulation with a software program based on the finite difference time domain method. Parameter performances measured using the classical workbench test are compared with those obtained using numerical simulations. Finally, the knee coil performance is validated with images acquired in a commercial low-field MR system. RI Positano, Vincenzo/A-6953-2008 OI Positano, Vincenzo/0000-0001-6955-957

Analyzing the interaction between the reader's voice and the linguistic structure of the text: a preliminary study

In this study, we present a preliminary analysis of the relationship between the linguistic profile of a text and the voice properties of the reader aiming to improve the speech-based emotion recognition systems. To this aim, we recorded the speech signals from a group of 32 healthy volunteers reading aloud neutral and affective texts and used the BioVoice toolbox to compute some of the main speech features. The selected texts were analyzed to quantify their lexical, morpho-syntactic, and syntactic content. Correlation and Support Vector Regressor analyses between linguistic and speech features have shown a significant modulation of some voice acoustic properties performed by the linguistic structure of the text. Particularly, a significant effect was shown on some specific speech features often used for the assessment of human emotional state (e.g., F0). This suggests that the lexical, morpho-syntactic, and syntactic properties could play an important role in the emotional dynamics of a person

Computational Analysis of a Radiofrequency Knee Coil for Low-Field MRI Using FDTD

Magnetic resonance imaging (MRI) is essential for the diagnosis and treatment of musculoskeletal conditions. Low-field

Human body odors of happiness and fear modulate the late positive potential component during neutral face processing: a preliminary ERP study on healthy subjects

Human body odors (HBOs) are powerful stimuli that can affect emotional, cognitive and behavioral processes. However, the characterization of the physiological response to HBOs is still to be fully investigated. Here, we analyzed the self-assessed emotion perception and the EEG event-related potentials (ERP) on 17 healthy young women during a simultaneous visual-olfactory stimulation. Particularly, we evaluated the effect of happiness and fear HBO on the amplitude of ERP waveforms elicited by neutral face processing. In addition, we evaluated the subjective valence and arousal perception of the presented neutral faces by means of the self-assessment-manikin test. We observed a significant increase in the amplitude of the late positive potential (LPP) for central left sites (i.e., C3) during the administration of HBOs with respect to clean air. On the other hand, we did not observe any significant change in the subjective valence and arousal scores as well as for the early components of the ERP (i.e., P100, N170, Vertex-Positive-Potential). Our preliminary results suggest that fear and happiness HBO can induce a protracted increase in the LPP, and possibly reflect an automatic and sustained engagement with emotionally significant content

Spatiotemporal dynamics of single-letter reading: a combined ERP-FMRI study

This work investigates the neural correlates of single-letter reading by combining event-related potentials (ERPs) and functional magnetic resonance imaging (fMRI), thus exploiting their complementary spatiotemporal resolutions. Three externally-paced reading tasks were administered with an event-related design: passive observation of letters and symbols and active reading aloud of letters. ERP and fMRI data were separately recorded from 8 healthy adults during the same experimental conditions. Due to the presence of artifacts in the EEG signals, two subjects were discarded from further analysis. Independent Component Analysis was applied to ERPs, after dimensionality reduction by Principal Component Analysis: some independent components were clearly related to specific reading functions and the associated current density distributions in the brain were estimated with Low Resolution Electromagnetic Tomography Analysis method (LORETA). The impulse hemodynamic response function was modeled as a linear combination of linear B-spline functions and fMRI statistical analysis was performed by multiple linear regression. fMRI and LORETA maps were superimposed in order to identify the overlapping activations and the activated regions specifically revealed by each modality. The results showed the existence of neuronal networks functionally specific for letter processing and for explicit verbal-motor articulation, including the temporo-parietal and frontal regions. Overlap between fMRI and LORETA results was observed in the inferior temporal-middle occipital gyrus, suggesting that this area has a crucial and multifunctional role for linguistic and reading processes, likely because its spatial location and strong interconnection with the main visual and auditory sensory systems may have favored its specialization in grapheme-phoneme matching

The Effect of Visual Experience on the Development of Functional Architecture in hMT+

We investigated whether the visual hMT+ cortex plays a role in supramodal representation of sensory flow, not mediated by visual mental imagery. We used functional magnetic resonance imaging to measure neural activity in sighted and congenitally blind individuals during passive perception of optic and tactile flows. Visual motion–responsive cortex, including hMT+, was identified in the lateral occipital and inferior temporal cortices of the sighted subjects by response to optic flow. Tactile flow perception in sighted subjects activated the more anterior part of these cortical regions but deactivated the more posterior part. By contrast, perception of tactile flow in blind subjects activated the full extent, including the more posterior part. These results demonstrate that activation of hMT+ and surrounding cortex by tactile flow is not mediated by visual mental imagery and that the functional organization of hMT+ can develop to subserve tactile flow perception in the absence of any visual experience. Moreover, visual experience leads to a segregation of the motion-responsive occipitotemporal cortex into an anterior subregion involved in the representation of both optic and tactile flows and a posterior subregion that processes optic flow only

Human body odour modulates neural processing of faces: effective connectivity analysis using EEG

Facial emotion processing by the brain plays a decisive role in human social interactions. This signal helps us interpret and predict people's behaviours. However, other social signals such as human voices or human body odours may facilitate or impair the identification of facial expressions. Here we studied the effects of emotional human body odours on face processing by measuring evoked neural responses and brain connectivity using the electroencephalogram (EEG). We used an emotion recognition task in which the participants attributed an emotion (i.e. happy vs fearful) to a presented face image while simultaneously exposed to emotional body odours. First, we measured face related potentials (FRP)s including P100 and N170 components. Statistical analyses revealed significant differences among FRPs recorded in different odour conditions. Second, we used a hierarchical Bayesian approach including a group dynamic causal model (DCM) followed by parametric empirical Bayes (PEB) to characterize the brain network explaining differences between FRPs. Our preliminary results suggested that different brain networks contribute to neutral face processing in the presence of different emotional body odours