Search results for "Biomedical engineering"

Atrial activity extraction for atrial fibrillation analysis using blind source separation.

2004

This contribution addresses the extraction of atrial activity (AA) from real electrocardiogram (ECG) recordings of atrial fibrillation (AF). We show the appropriateness of independent component analysis (ICA) to tackle this biomedical challenge when regarded as a blind source separation (BSS) problem. ICA is a statistical tool able to reconstruct the unobservable independent sources of bioelectric activity which generate, through instantaneous linear mixing, a measurable set of signals. The three key hypothesis that make ICA applicable in the present scenario are discussed and validated: 1) AA and ventricular activity (VA) are generated by sources of independent bioelectric activity; 2) AA …

An Information-Theoretic Framework to Measure the Dynamic Interaction between Neural Spike Trains

2021

Understanding the interaction patterns among simultaneous recordings of spike trains from multiple neuronal units is a key topic in neuroscience. However, an optimal approach of assessing these interactions has not been established, as existing methods either do not consider the inherent point process nature of spike trains or are based on parametric assumptions that may lead to wrong inferences if not met. This work presents a framework, grounded in the field of information dynamics, for the model-free, continuous-time estimation of both undirected (symmetric) and directed (causal) interactions between pairs of spike trains. The framework decomposes the overall information exchanged dynami…

Toward morphological thoracic EIT: major signal sources correspond to respective organ locations in CT.

2012

Lung and cardiovascular monitoring applications of electrical impedance tomography (EIT) require localization of relevant functional structures or organs of interest within the reconstructed images. We describe an algorithm for automatic detection of heart and lung regions in a time series of EIT images. Using EIT reconstruction based on anatomical models, candidate regions are identified in the frequency domain and image-based classification techniques applied. The algorithm was validated on a set of simultaneously recorded EIT and CT data in pigs. In all cases, identified regions in EIT images corresponded to those manually segmented in the matched CT image. Results demonstrate the abilit…

On Multiple AER Handshaking Channels Over High-Speed Bit-Serial Bidirectional LVDS Links With Flow-Control and Clock-Correction on Commercial FPGAs f…

2017

Address event representation (AER) is a widely employed asynchronous technique for interchanging “neural spikes” between different hardware elements in neuromorphic systems. Each neuron or cell in a chip or a system is assigned an address (or ID), which is typically communicated through a high-speed digital bus, thus time-multiplexing a high number of neural connections. Conventional AER links use parallel physical wires together with a pair of handshaking signals (request and acknowledge). In this paper, we present a fully serial implementation using bidirectional SATA connectors with a pair of low-voltage differential signaling (LVDS) wires for each direction. The proposed implementation …

Combining Biophysical Modeling and Machine Learning to Predict Location of Atrial Ectopic Triggers

2018

The search for focal ectopic activity in the atria triggered from non-standard regions can be time consuming. The use of body surface potential maps to plan the intervention can be helpful, but require an advance processing of the data, that usually involves to solve an ill-posed inverse problem. In addition, changes in maps due to pathological substrate such as fibrosis might affect the expected electrical patterns. In this work, we use a machine learning approach to relate ectopic focus activity in different atrial regions with body surface potential maps, and consider the effects of fibrosis in various densities and distributions. Results show that as fibrosis increases over 15% the syst…

Augmented Reality Visualisation Concepts to Support Intraoperative Distance Estimation

2019

The estimation of distances and spatial relations between surgical instruments and surrounding anatomical structures is a challenging task for clinicians in image-guided surgery. Using augmented reality (AR), navigation aids can be displayed directly at the intervention site to support the assessment of distances and reduce the risk of damage to healthy tissue. To this end, four distance-encoding visualisation concepts were developed using a head-mounted optical see-through AR setup and evaluated by conducting a comparison study. Results suggest the general advantage of the proposed methods compared to a blank visualisation providing no additional information. Using a Distance Sensor concep…

A 3D Network Based Shape Prior for Automatic Myocardial Disease Segmentation in Delayed-Enhancement MRI

2021

Abstract Objectives: In this work, a new deep learning model for relevant myocardial infarction segmentation from Late Gadolinium Enhancement (LGE)-MRI is proposed. Moreover, our novel segmentation method aims to detect microvascular-obstructed regions accurately. Material and methods: We first segment the anatomical structures, i.e., the left ventricular cavity and the myocardium, to achieve a preliminary segmentation. Then, a shape prior based framework that fuses the 3D U-Net architecture with 3D Autoencoder segmentation framework to constrain the segmentation process of pathological tissues is applied. Results: The proposed network reached outstanding myocardial segmentation compared wi…

Concept and setup for intraoperative imaging of tumorous tissue via Attenuated Total Reflection spectrosocopy with Quantum Cascade Lasers

2015

A major challenge in tumor surgery is the differentiation between normal and malignant tissue. Since an incompletely resected tumor easily leads to recidivism, the gold standard is to remove malignant tissue with a sufficient safety margin and send it to pathology for examination with patho-histological techniques (rapid section diagnosis). This approach, however, exhibits several disadvantages: The removal of additional tissue (safety margin) means additional stress to the patient; the correct interpretation of proper tumor excision relies on the pathologist’s experience and the waiting time between resection and pathological result can be more than 45 minutes. This last aspect implies unn…

JABB: Moving Towards The Future.

2012

Periodic Variance Maximization using Generalized Eigenvalue Decomposition applied to Remote Photoplethysmography estimation

2018

International audience; A generic periodic variance maximization algorithm to extract periodic or quasi-periodic signals of unknown periods embedded into multi-channel temporal signal recordings is described in this paper. The algorithm combines the notion of maximizing a periodicity metric combined with the global optimization scheme to estimate the source periodic signal of an unknown period. The periodicity maximization is performed using Generalized Eigenvalue Decomposition (GEVD) and the global optimization is performed using tabu search. A case study of remote photoplethysmography signal estimation has been utilized to assess the performance of the method using videos from public data…