1,721,173 research outputs found
Advances in Wearable Photoplethysmography Applications in Health Monitoring
Full text linkIn the last few years, interest in wearable technology for physiological signal monitoring is rapidly growing, especially during and after the COVID-19 pandemic [1,2,3]. Specifically, considering that heart disease is the leading cause of death globally, continuous monitoring of cardiovascular dynamics has crucial relevance to improving prevention and diagnosis. Photoplethysmography (PPG) is a popular, non-invasive, and low-cost optical technique that can provide useful information about the cardiovascular system, aiming to reveal autonomic dysfunctions and peripheral vascular diseases during daily life. In fact, due to its simplicity and versatility, this technology can be used to develop wearable and wireless devices for out-of-hospital monitoring of both healthy and pathological subjects.
Even if technology has successfully increased the comfort of PPG sensors, in terms of wearability, dimensions and battery life, scientific research is still working on several issues, e.g., poor sensor contact, which leads to acquiring signals corrupted by noise and motion artifacts, especially during physical activity [4]. In this context, there are still many challenges related to PPG wearable device design and signal processing techniques to derive robust indices. Furthermore, recent studies have shed light on the possibility of extracting a good surrogate of PPG signal from face RGB video processing, opening the door to not only wireless but also contactless monitoring. For this reasons, the investigation of reliable PPG-derived parameters, including rhythm and morphology features, but also heart rate variability descriptors, is growing in interest, comprising novel signal processing methodologies for artifact removal and feature extraction.
This Special Issue focused on original research papers dealing with hardware and software advances in the development of robust and reliable biomarkers for the non-invasive monitoring of cardiovascular dynamics based on PPG signal acquisition. Topics of interest for PPG signal applications included clinical pathologies, biometry, sleep and sport monitoring
Warehousing of genomic and proteomic distributed information: integration, management and interrogation
No full textSimulation of the Electromechanical Behavior of Multiwall Carbon Nanotubes
No full textThe enormous potential of carbon nanotubes (CNTs) as primary components in electronic devices and NEMS necessitates the understanding and predicting of the effects of mechanical deformation on electron transport in CNTs. In principle, detailed atomic/electronic calculations can provide both the deformed configuration and the resulting electrical transport behavior of the CNT. However, the computational expense of these simulations limits the size of the CNTs that can be studied with this technique and a direct analysis of CNTs of the dimension used in nano-electronic devices seems prohibitive at the present. Here a computationally effective mixed finite element/tight-binding approach able to simulate the electromechanical behavior of CNTs devices is presented. The TB code is carefully designed to realize orders-of-magnitude reduction in computational time in calculating deformation-induced changes in electrical transport properties of the nanotubes. The FE-TB computational approach is validated in a simulation of laboratory experiments on a multiwall CNT and then used to demonstrate the role of the multiwall structure in providing robustness to conductivity in the event of imposed mechanical deformations
Nociones respecto al consumo de sustancias como ocupación construidas por los estudiantes avanzados de la Licenciatura en Terapia Ocupacional de la Universidad Nacional de Villa María durante el período 2023
Full text linkActualmente, la Terapia Ocupacional pensada como un campo de conocimiento e intervención en diferentes ámbitos se enriquece y adopta múltiples sustentos teóricos que la configuran en una disciplina minada de saberes y supuestos. La siguiente investigación denominada Nociones respecto al Consumo de Sustancias como Ocupación construidas por los estudiantes avanzados de la Licenciatura en Terapia Ocupacional de la Universidad Nacional de Villa María durante el período 2023 emplea un método descriptivo con el fin de dar a conocer la inmensa variedad de postulaciones e implicancias teórico/prácticas construidas por los estudiantes referidos a la Terapia Ocupacional y el Consumo de Sustancias. Al mismo tiempo, el estudio se encuentra conformado por una muestra por conveniencia de estudiantes avanzados de la Licenciatura en Terapia Ocupacional de la Universidad Nacional de Villa María. La misma fue elegida con el fin de determinar el impacto en la construcción del futuro rol profesional de los conceptos e ideas en relación a Terapia Ocupacional, Ocupación y Consumo de SustanciasFil: Guizzo, Oriana Rosario. Universidad Nacional Villa María; Argentina.Fil: Nardelli, M. Verónica. Universidad Nacional Villa María; Argentina
MIXED FINITE ELEMENT-TIGHT BINDING TECHNIQUE FOR STUDYING THE ELECTROMECHANICAL BEHAVIOR OF SINGLE AND MULTIWALL CARBON NANOTUBES
No full textCross-lattice Behavior of General ACO Folding for Proteins in the HP Model
No full textThe computational investigation of protein folding is one of the most relevant challenges in bioinformatics. In this field, simplified lattice models for proteins like the classical HP model have been proposed, and different lattice types can be employed. A promising approach to find ground state conformations relies on Ant Colony Optimization (ACO), a popular biology-inspired heuristics: several variants have been implemented so far, on square lattices in 2D and 3D.
In this paper we propose a general scheme of ACO for HP on both square and triangular lattices in 2D and 3D, including also a novel initialization procedure for the pheromone matrix according to some pre-computed suboptimal conformations. The algorithm behavior, considering the influence of the optional parts and the required parameter tuning, is investigated for the first time with experiments that systematically span different lattice types. The test outcomes are useful in understanding how to operate on the algorithm parameters.
The presented results are used to sketch out general guidelines for the practical employment of ACO in conformational studies, depending on the chosen sequences and lattice types
Multichannel Complexity Index (MCI) for a multi-organ physiological complexity assessment
No full textQuantitative measurements of multi-organ interplay are crucial for the assessment of multivariate physiological dynamics in health and disease. Nevertheless, current quantification of multivariate complexity for nonlinear physiological processes is limited by reliability issues on short-time series, and parameters sensitivity especially in case of a multiscale analysis. To overcome these limitations, we propose a new tool to characterize the complexity of interacting physiological processes that may have different temporal dynamics: the Multichannel Complexity Index (MCI). This metrics relies on a novel method for the reconstruction of the multivariate phase space, where each series is embedded using its proper time delay. MCI accounts for the estimation of phase space distances using fuzzy rules, and may be computed at two different ranges of time-scale values to investigate short- and long-term dynamics. We validated our algorithm using three-channel white gaussian noise and 1/f noise systems, with different levels of coupling. By applying our approach to these data, we demonstrate that the MCI method allows to discern not only the degree of complexity in the system dynamics, but also the across-channel coupling level. Results on synthetic series from the Henón map and Rössler attractor demonstrate that MCI effectively discerns between different dynamical behaviours, outperforming state of the art metrics such as the Refined Composite Multivariate Multiscale Fuzzy Entropy. On publicly-available physiological series, considering heartbeat dynamics and blood pressure variability, results demonstrate a MCI sensitivity to postural changes(p<10−2 for rest vs. slow-tilt, and p<0.05 for rest vs. rapid-tilt/stand-up conditions), as well as a MCI sensitivity to subjects’ age-range (data gathered while watching Fantasia Disney movie, 1940) with p<10−2 for short scales and p=0.03 for long scales. In conclusion, MCI is a viable tool for an effective multivariate physiological complexity assessment. The Matlab code implementing the proposed MCI algorithm is available online
The dynamics of emotions: a preliminary study on continuously annotated arousal signals
No full textHuman emotions are characterized by a complex interaction between conscious experience, physiological arousal, and social dimension. Although the importance of considering emotion response as a nonlinear dynamical system is widely recognized, mathematical models able to describe the time-varying conscious emotional states are still lacking. In recent literature on Affective Computing, novel annotating tools have been introduced to record continuous self-assessed emotion ratings. These data represent a valuable source to describe the dynamics arising during the conscious experience of emotions. Therefore, in this study, we investigate the trajectories traced in the reconstructed phase space of continuously annotated arousal signals acquired during an experimental protocol of emotion elicitation. We use a subset of the Continuously Anno-tated Signals of Emotions (CASE) dataset, including self-assessed ratings from thirty healthy subjects while watching two video clips: one fear-inducing and one relaxing. We analyse intrinsic irregularity and complexity of arousal time-series, performing Sample Entropy and Distribution Entropy algorithms. Results show a significantly higher complexity of time-varying emotion perception during the scary video compared to the relaxing video. Our findings, although preliminary, highlight a promising field of application of chaos theory methodologies to continuous emotion ratings, which can be exploited for the prediction of pathological moods in ecological settings
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