Search results for "Biomedical engineering"
showing 10 items of 2020 documents
Multiscale analysis of information dynamics for linear multivariate processes.
2016
In the study of complex physical and physiological systems represented by multivariate time series, an issue of great interest is the description of the system dynamics over a range of different temporal scales. While information-theoretic approaches to the multiscale analysis of complex dynamics are being increasingly used, the theoretical properties of the applied measures are poorly understood. This study introduces for the first time a framework for the analytical computation of information dynamics for linear multivariate stochastic processes explored at different time scales. After showing that the multiscale processing of a vector autoregressive (VAR) process introduces a moving aver…
Synergetic and redundant information flow detected by unnormalized Granger causality: application to resting state fMRI
2015
Objectives: We develop a framework for the analysis of synergy and redundancy in the pattern of information flow between subsystems of a complex network. Methods: The presence of redundancy and/or synergy in multivariate time series data renders difficult to estimate the neat flow of information from each driver variable to a given target. We show that adopting an unnormalized definition of Granger causality one may put in evidence redundant multiplets of variables influencing the target by maximizing the total Granger causality to a given target, over all the possible partitions of the set of driving variables. Consequently we introduce a pairwise index of synergy which is zero when two in…
A rule‐based method to model myocardial fiber orientation in cardiac biventricular geometries with outflow tracts
2019
Rule-based methods are often used for assigning fiber orientation to cardiac anatomical models. However, existing methods have been developed using data mostly from the left ventricle. As a consequence, fiber information obtained from rule-based methods often does not match histological data in other areas of the heart such as the right ventricle, having a negative impact in cardiac simulations beyond the left ventricle. In this work, we present a rule-based method where fiber orientation is separately modeled in each ventricle following observations from histology. This allows to create detailed fiber orientation in specific regions such as the endocardium of the right ventricle, the inter…
Multiscale partial information decomposition of dynamic processes with short and long-range correlations: theory and application to cardiovascular co…
2022
Abstract Objective. In this work, an analytical framework for the multiscale analysis of multivariate Gaussian processes is presented, whereby the computation of Partial Information Decomposition measures is achieved accounting for the simultaneous presence of short-term dynamics and long-range correlations. Approach. We consider physiological time series mapping the activity of the cardiac, vascular and respiratory systems in the field of Network Physiology. In this context, the multiscale representation of transfer entropy within the network of interactions among Systolic arterial pressure (S), respiration (R) and heart period (H), as well as the decomposition into unique, redundant and s…
Need for lateral bone augmentation at two narrow-diameter implants: A prospective, controlled, clinical study.
2021
To detect the potential influence of implant diameter and anatomic factors on the need for bone augmentation procedures (BAPs) when replacing congenitally missing lateral incisors (MLIs).Patients with congenitally missing MLIs with a mesio-distal distance between the canine and the central incisor of 5.9-6.3 mm received a Ø2.9 mm implant while Ø3.3 mm implants were placed when the distance was 6.4-7.1 mm. The following linear measurements were recorded using a calliper: width of the alveolar process (WAP), width of the bony alveolar ridge (WAR) and thickness of the facial bone after implant osteotomy (TFB). Guided bone regeneration was performed in case of fenestration- or dehiscence-type d…
Remote heart rate variability for emotional state monitoring
2018
International audience; Several researches have been conducted to recognize emotions using various modalities such as facial expressions , gestures, speech or physiological signals. Among all these modalities, physiological signals are especially interesting because they are mainly controlled by the autonomic nervous system. It has been shown for example that there is an undeniable relationship between emotional state and Heart Rate Variability (HRV). In this paper, we present a methodology to monitor emotional state from physiological signals acquired remotely. The method is based on a remote photoplethysmography (rPPG) algorithm that estimates remote Heart Rate Variability (rHRV) using a …
Facial Expressions to Evaluate Advertising: A Laboratory versus Living Room Study
2017
In recent years researchers have shown growing interest in the impact of emotions in television commercials and in advertising in general (Park and Thorson, 1990). Emotions also influence the attitude towards the brand and to the ad (Batney and Ray, 1986; Edell and Burke, 1987; Derbaix, 1995), increase the attention of the advertisement (Olney, Hobrook and Bartra, 1991), and brand recall (Stayman and Batra, 1991).
General Principles for the Detection of Modified Nucleotides in RNA by Specific Reagents.
2021
Epitranscriptomics heavily rely on chemical reagents for the detection, quantification, and localization of modified nucleotides in transcriptomes. Recent years have seen a surge in mapping methods that use innovative and rediscovered organic chemistry in high throughput approaches. While this has brought about a leap of progress in this young field, it has also become clear that the different chemistries feature variegated specificity and selectivity. The associated error rates, e.g., in terms of false positives and false negatives, are in large part inherent to the chemistry employed. This means that even assuming technically perfect execution, the interpretation of mapping results issuin…
Classification of Heart Sounds Using Convolutional Neural Network
2020
Heart sounds play an important role in the diagnosis of cardiac conditions. Due to the low signal-to-noise ratio (SNR), it is problematic and time-consuming for experts to discriminate different kinds of heart sounds. Thus, objective classification of heart sounds is essential. In this study, we combined a conventional feature engineering method with deep learning algorithms to automatically classify normal and abnormal heart sounds. First, 497 features were extracted from eight domains. Then, we fed these features into the designed convolutional neural network (CNN), in which the fully connected layers that are usually used before the classification layer were replaced with a global averag…
Colourimetric image analysis as a diagnostic tool in female genital schistosomiasis
2015
Female genital schistosomiasis (FGS) is a highly prevalent waterborne disease in some of the poorest areas of sub-Saharan Africa. Reliable and affordable diagnostics are unavailable. We explored colourimetric image analysis to identify the characteristic, yellow lesions caused by FGS. We found that the method may yield a sensitivity of 83% and a specificity of 73% in colposcopic images. The accuracy was also explored in images of simulated inferior quality, to assess the possibility of implementing such a method in simple, electronic devices. This represents the first step towards developing a safe and affordable aid in clinical diagnosis, allowing for a point-of-care approach.