A. M. Hernandez

Development of a wearable vital signs monitor for healthcare

In development countries the vital signs data measurement normally is performed at hospitals or laboratories where patients remain under observation with many electrodes attached on the body. The integration of biomedical data acquisition systems and information technologies (IT) enables continuous real time monitoring of physiological data in daily life, which improves patients medical care and medical research possibilities. To achieve this goal, the research and development of some wearable intelligent sensors, sensors miniaturization, signal processing, wireless transmission, and databases development for these vital data have been done. Our goal is to implement a wearable system that can be used in places located outside of hospitals and medical institutions coverage area. In this paper, we present the current stage of the project where some intelligent modules have been implemented and other are under construction. Preliminary results concerning Non-Invasive Blood Pressure (NIBP), ECG and wireless connection are also presented.

Computational tool for modeling and simulation of mechanically ventilated patients

The mechanical ventilator settings in patients with respiratory diseases like chronic obstructive pulmonary disease (COPD) during episodes of acute respiratory failure (ARF) is not a simple task that in most cases is successful based on the experience of physicians. This paper describes an interactive tool based in mathematical models, developed to make easier the study of the interaction between a mechanical ventilator and a patient. It describes all stages of system development, including simulated ventilatory modes, the pathologies of interest and interaction between the user and the system through a graphical interface developed in Matlab and Simulink. The developed computational tool allows the study of most widely used ventilatory modes and its advantages in the treatment of different kind of patients. The graphical interface displays all variables and parameters in the common way of last generation mechanical ventilators do and it is totally interactive, making possible its use by clinical personal, hiding the complexity of implemented mathematical models to the user. The evaluation in different clinical simulated scenes adjusts properly with recent findings in mechanical ventilation scientific literature.

Successful object encoding induces increased directed connectivity in presymptomatic early-onset Alzheimer's disease

Background: Recent studies report increases in neural activity in brain regions critical to episodic memory at preclinical stages of Alzheimer’s disease (AD). Although electroencephalography (EEG) is widely used in AD studies, given its non-invasiveness and low cost, there is a need to translate the findings in other neuroimaging methods to EEG. Objective: To examine how the previous findings using functional magnetic resonance imaging (fMRI) at preclinical stage in presenilin-1 E280A mutation carriers could be assessed and extended, using EEG and a connectivity approach. Methods: EEG signals were acquired during resting and encoding in 30 normal cognitive young subjects, from an autosomal dominant early-onset AD kindred from Antioquia, Colombia. Regions of the brain previously reported as hyperactive were used for connectivity analysis. Results: Mutation carriers exhibited increasing connectivity at analyzed regions. Among them, the right precuneus exhibited the highest changes in connectivity. Conclusion: Increased connectivity in hyperactive cerebral regions is seen in individuals, genetically-determined to develop AD, at preclinical stage. The use of a connectivity approach and a widely available neuroimaging technique opens the possibility to increase the use of EEG in early detection of preclinical AD.

Device for integration of clinical information of biomedical equipments

There is a death risk that increases with the required time to transport a critical patient to a hospital by ambulance. Effectiveness of medical attention and therefore patients safety will strongly depend on the quickness to determine appropriate actions to be performed when patient arrives to the hospital. It is evident the need of establishing a communication link between monitoring equipment inside the ambulance and the healthcare center. This paper presents a system that automatically integrates, organizes, records and wirelessly transmits patients vital signs in real-time. Physicians and specialists could use this information to make a pre-diagnosis of patients current condition, anticipate possible complications and medical treatment planning before his arrival to the care center.

Neurophysiological correlates in Mild Cognitive Impairment detected using group Independent Component Analysis.

Alzheimers disease is the most prevalent cause of dementia. Mild Cognitive Impairment (MCI) is defined as a grey area between intact cognitive functioning and clinical dementia. Electroencephalography (EEG) has been used to identify biomarkers in dementia. Currently, there is a great interest in translating the study from raw signals to signal generators, trying to keep the relationship with neurophysiology. In the current study, EEG recordings during an encoding task were acquired in MCI subjects and healthy controls. Data was decomposed using group Independent Component Analysis (gICA) and the most neuronal components were analyzed using Phase Intertrial Coherence (PIC) and Phase shift Intertrial Coherence (PsIC). MCI subjects exhibited an increase of PIC in the theta band, while controls showed increase in PsIC in the alpha band. Correlation between PIC and PsIC and clinical scales were also found. Those findings indicate that the methodology proposed based in gICA can help to extract information from EEG recordings with neurophysiological meaning.

System for skills training and competency assessment in neurosurgery

This paper presents a novel approach to simulate neurosurgical interventions, which can be used for training in schools of medicine. It is based on the implementation of a benchtop model as an alternative to reported virtual reality-based approaches. The system includes a surgery planning software, 3D models of skull, an electromagnetic fields navigation system and compatible instrumentation. To our knowledge, the system developed here represents a unique approach to neurosurgery training where trainees are able to experiment with a more realistic model of an intended surgical procedure.

RESPILAB : A VIRTUAL LABORATORY FOR THE ANALYSIS OF HUMAN RESPIRATORY CONTROL SYSTEM

Abstract One of the career areas included in the field of Biomedical Engineering is the application of engineering system analysis: physiologic modeling, simulation and control. This paper describes a Virtual Laboratory for the analysis and the study of Human Respiratory System. The Laboratory is based on the compilation of several models described in the literature. Presented application has been build using MATLAB/Simulink and EJS, so it combines good computation capabilities and it is completely interactive. The Virtual Laboratory is designed in order to understand the operation of respiratory system under normal conditions and pathological situations, and to predict respiratory variables at different levels of stimuli and conditions.

Analysis of respiratory models at different levels of exercise, hypercapnia and hypoxia

The purpose of this work is to evaluate characteristics of five respiratory models under different levels of exercise, hypercapnia and hypoxia. Two of them, RS1 and RS2, have permitted the implementation of a respiratory control system much more complex than the other ones. RS1 considers the integration of cardiorespiratory and mechanical systems. The most important difference in RS2 is the presence of respiratory frequency (f) that changes depending on the level of stimulus as it happens in fact. Tidal volume (V/sub T/) vs. f plots which are very interesting for the physiologists are obtained. A comparative study of the steady-state and transient responses between the five models is performed by simulation analyzing some interesting respiratory variables: expired ventilation, V/sub T/, f and arterial CO/sub 2/ and O/sub 2/ pressures. Finally, the influence of f and the ratio between inspiration and expiration intervals is evaluated.

Optimization techniques in respiratory control system models

Graphical abstractDisplay Omitted HighlightsTwo respiratory control models based on minimizing work of breathing are analyzed.Optimization algorithms and hypercapnic data are used to adjust model parameters.Algorithms are assessed in terms of convergence rate, solution accuracy and precision.Models are evaluated in terms of prediction error and physiological meaning. One of the most complex physiological systems whose modeling is still an open study is the respiratory control system where different models have been proposed based on the criterion of minimizing the work of breathing (WOB). The aim of this study is twofold: to compare two known models of the respiratory control system which set the breathing pattern based on quantifying the respiratory work; and to assess the influence of using direct-search or evolutionary optimization algorithms on adjustment of model parameters. This study was carried out using experimental data from a group of healthy volunteers under CO2 incremental inhalation, which were used to adjust the model parameters and to evaluate how much the equations of WOB follow a real breathing pattern. This breathing pattern was characterized by the following variables: tidal volume, inspiratory and expiratory time duration and total minute ventilation. Different optimization algorithms were considered to determine the most appropriate model from physiological viewpoint. Algorithms were used for a double optimization: firstly, to minimize the WOB and secondly to adjust model parameters. The performance of optimization algorithms was also evaluated in terms of convergence rate, solution accuracy and precision. Results showed strong differences in the performance of optimization algorithms according to constraints and topological features of the function to be optimized. In breathing pattern optimization, the sequential quadratic programming technique (SQP) showed the best performance and convergence speed when respiratory work was low. In addition, SQP allowed to implement multiple non-linear constraints through mathematical expressions in the easiest way. Regarding parameter adjustment of the model to experimental data, the evolutionary strategy with covariance matrix and adaptation (CMA-ES) provided the best quality solutions with fast convergence and the best accuracy and precision in both models. CMAES reached the best adjustment because of its good performance on noise and multi-peaked fitness functions. Although one of the studied models has been much more commonly used to simulate respiratory response to CO2 inhalation, results showed that an alternative model has a more appropriate cost function to minimize WOB from a physiological viewpoint according to experimental data.

Development of a plantar pressure measuring system

This paper presents an electronically enabled system that uses piezoresistive sensor arrays to acquire information from plantar pressure distribution. The system has been designed as a low-cost alternative to diagnostic equipment for orthotic insoles, biomechanical studies, and sports medicine. The system allows autonomous biomechanical analyses that include dynamic and static tests, with similar or even better features than those of commercial devices.