52 resultados para Electrical resistances
Resumo:
OBJECTIVE: In contrast to conventional (CONV) neuromuscular electrical stimulation (NMES), the use of "wide-pulse, high-frequencies" (WPHF) can generate higher forces than expected by the direct activation of motor axons alone. We aimed at investigating the occurrence, magnitude, variability and underlying neuromuscular mechanisms of these "Extra Forces" (EF). METHODS: Electrically-evoked isometric plantar flexion force was recorded in 42 healthy subjects. Additionally, twitch potentiation, H-reflex and M-wave responses were assessed in 13 participants. CONV (25Hz, 0.05ms) and WPHF (100Hz, 1ms) NMES consisted of five stimulation trains (20s on-90s off). RESULTS: K-means clustering analysis disclosed a responder rate of almost 60%. Within this group of responders, force significantly increased from 4% to 16% of the maximal voluntary contraction force and H-reflexes were depressed after WPHF NMES. In contrast, non-responders showed neither EF nor H-reflex depression. Twitch potentiation and resting EMG data were similar between groups. Interestingly, a large inter- and intrasubject variability of EF was observed. CONCLUSION: The responder percentage was overestimated in previous studies. SIGNIFICANCE: This study proposes a novel methodological framework for unraveling the neurophysiological mechanisms involved in EF and provides further evidence for a central contribution to EF in responders.
Resumo:
Electrical impedance tomography (EIT) is a non-invasive imaging technique that can measure cardiac-related intra-thoracic impedance changes. EIT-based cardiac output estimation relies on the assumption that the amplitude of the impedance change in the ventricular region is representative of stroke volume (SV). However, other factors such as heart motion can significantly affect this ventricular impedance change. In the present case study, a magnetic resonance imaging-based dynamic bio-impedance model fitting the morphology of a single male subject was built. Simulations were performed to evaluate the contribution of heart motion and its influence on EIT-based SV estimation. Myocardial deformation was found to be the main contributor to the ventricular impedance change (56%). However, motion-induced impedance changes showed a strong correlation (r = 0.978) with left ventricular volume. We explained this by the quasi-incompressibility of blood and myocardium. As a result, EIT achieved excellent accuracy in estimating a wide range of simulated SV values (error distribution of 0.57 ± 2.19 ml (1.02 ± 2.62%) and correlation of r = 0.996 after a two-point calibration was applied to convert impedance values to millilitres). As the model was based on one single subject, the strong correlation found between motion-induced changes and ventricular volume remains to be verified in larger datasets.
Resumo:
Electrical resistivity tomography (ERT) is a well-established method for geophysical characterization and has shown potential for monitoring geologic CO2 sequestration, due to its sensitivity to electrical resistivity contrasts generated by liquid/gas saturation variability. In contrast to deterministic inversion approaches, probabilistic inversion provides the full posterior probability density function of the saturation field and accounts for the uncertainties inherent in the petrophysical parameters relating the resistivity to saturation. In this study, the data are from benchtop ERT experiments conducted during gas injection into a quasi-2D brine-saturated sand chamber with a packing that mimics a simple anticlinal geological reservoir. The saturation fields are estimated by Markov chain Monte Carlo inversion of the measured data and compared to independent saturation measurements from light transmission through the chamber. Different model parameterizations are evaluated in terms of the recovered saturation and petrophysical parameter values. The saturation field is parameterized (1) in Cartesian coordinates, (2) by means of its discrete cosine transform coefficients, and (3) by fixed saturation values in structural elements whose shape and location is assumed known or represented by an arbitrary Gaussian Bell structure. Results show that the estimated saturation fields are in overall agreement with saturations measured by light transmission, but differ strongly in terms of parameter estimates, parameter uncertainties and computational intensity. Discretization in the frequency domain (as in the discrete cosine transform parameterization) provides more accurate models at a lower computational cost compared to spatially discretized (Cartesian) models. A priori knowledge about the expected geologic structures allows for non-discretized model descriptions with markedly reduced degrees of freedom. Constraining the solutions to the known injected gas volume improved estimates of saturation and parameter values of the petrophysical relationship. (C) 2014 Elsevier B.V. All rights reserved.
Resumo:
Probabilistic inversion methods based on Markov chain Monte Carlo (MCMC) simulation are well suited to quantify parameter and model uncertainty of nonlinear inverse problems. Yet, application of such methods to CPU-intensive forward models can be a daunting task, particularly if the parameter space is high dimensional. Here, we present a 2-D pixel-based MCMC inversion of plane-wave electromagnetic (EM) data. Using synthetic data, we investigate how model parameter uncertainty depends on model structure constraints using different norms of the likelihood function and the model constraints, and study the added benefits of joint inversion of EM and electrical resistivity tomography (ERT) data. Our results demonstrate that model structure constraints are necessary to stabilize the MCMC inversion results of a highly discretized model. These constraints decrease model parameter uncertainty and facilitate model interpretation. A drawback is that these constraints may lead to posterior distributions that do not fully include the true underlying model, because some of its features exhibit a low sensitivity to the EM data, and hence are difficult to resolve. This problem can be partly mitigated if the plane-wave EM data is augmented with ERT observations. The hierarchical Bayesian inverse formulation introduced and used herein is able to successfully recover the probabilistic properties of the measurement data errors and a model regularization weight. Application of the proposed inversion methodology to field data from an aquifer demonstrates that the posterior mean model realization is very similar to that derived from a deterministic inversion with similar model constraints.
Resumo:
Conventional (CONV) neuromuscular electrical stimulation (NMES) (i.e., short pulse duration, low frequencies) induces a higher energetic response as compared to voluntary contractions (VOL). In contrast, wide-pulse, high-frequency (WPHF) NMES might elicit-at least in some subjects (i.e., responders)-a different motor unit recruitment compared to CONV that resembles the physiological muscle activation pattern of VOL. We therefore hypothesized that for these responder subjects, the metabolic demand of WPHF would be lower than CONV and comparable to VOL. 18 healthy subjects performed isometric plantar flexions at 10% of their maximal voluntary contraction force for CONV (25 Hz, 0.05 ms), WPHF (100 Hz, 1 ms) and VOL protocols. For each protocol, force time integral (FTI) was quantified and subjects were classified as responders and non-responders to WPHF based on k-means clustering analysis. Furthermore, a fatigue index based on FTI loss at the end of each protocol compared with the beginning of the protocol was calculated. Phosphocreatine depletion (ΔPCr) was assessed using 31P magnetic resonance spectroscopy. Responders developed four times higher FTI's during WPHF (99 ± 37 ×103 N.s) than non-responders (26 ± 12 ×103 N.s). For both responders and non-responders, CONV was metabolically more demanding than VOL when ΔPCr was expressed relative to the FTI. Only for the responder group, the ∆PCr/FTI ratio of WPHF (0.74 ± 0.19 M/N.s) was significantly lower compared to CONV (1.48 ± 0.46 M/N.s) but similar to VOL (0.65 ± 0.21 M/N.s). Moreover, the fatigue index was not different between WPHF (-16%) and CONV (-25%) for the responders. WPHF could therefore be considered as the less demanding NMES modality-at least in this subgroup of subjects-by possibly exhibiting a muscle activation pattern similar to VOL contractions.
Resumo:
The present study was performed in an attempt to develop an in vitro integrated testing strategy (ITS) to evaluate drug-induced neurotoxicity. A number of endpoints were analyzed using two complementary brain cell culture models and an in vitro blood-brain barrier (BBB) model after single and repeated exposure treatments with selected drugs that covered the major biological, pharmacological and neuro-toxicological responses. Furthermore, four drugs (diazepam, cyclosporine A, chlorpromazine and amiodarone) were tested more in depth as representatives of different classes of neurotoxicants, inducing toxicity through different pathways of toxicity. The developed in vitro BBB model allowed detection of toxic effects at the level of BBB and evaluation of drug transport through the barrier for predicting free brain concentrations of the studied drugs. The measurement of neuronal electrical activity was found to be a sensitive tool to predict the neuroactivity and neurotoxicity of drugs after acute exposure. The histotypic 3D re-aggregating brain cell cultures, containing all brain cell types, were found to be well suited for OMICs analyses after both acute and long term treatment. The obtained data suggest that an in vitro ITS based on the information obtained from BBB studies and combined with metabolomics, proteomics and neuronal electrical activity measurements performed in stable in vitro neuronal cell culture systems, has high potential to improve current in vitro drug-induced neurotoxicity evaluation.
Resumo:
Background: Pulseless electrical activity (PEA) cardiac arrest is defined as a cardiac arrest (CA) presenting with a residual organized electrical activity on the electrocardiogram. In the last decades, the incidence of PEA has regularly increased, compared to other types of CA like ventricular fibrillation or pulseless ventricular tachycardia. PEA is frequently induced by reversible conditions. The "4 (or 5) H" & "4 (or 5) T" are proposed as a mnemonic to asses for Hypoxia, Hypovolemia, Hypo- /Hyperkalaemia, Hypothermia, Thrombosis (cardiac or pulmonary), cardiac Tamponade, Toxins, and Tension pneumothorax. Other pathologies (intracranial haemorrhage, severe sepsis, myocardial contraction dysfunction) have been identified as potential causes for PEA, but their respective probability and frequencies are unclear and they are not yet included into the resuscitation guidelines. The aim of this study was to analyse the aetiologies of PEA out-of-hospital CA, in order to evaluate the relative frequencies of each cause and therefore to improve the management of patients suffering a PEA cardiac arrest. Method: This retrospective study was based on data routinely and prospectively collected for each PEMS intervention. All adult patients treated from January 1st 2002 to December 2012 31st by the PEMS for out-of-hospital cardiac arrest, with PEA as the first recorded rhythm, and admitted to the emergency department (ED) of the Lausanne University Hospital were included. The aetiologies of PEA cardiac arrest were classified into subgroups, based on the classical H&T's classification, supplemented by four other subgroups analysis: trauma, intra-cranial haemorrhage (ICH), non-ischemic cardiomyopathy (NIC) and undetermined cause. Results: 1866 OHCA were treated by the PEMS. PEA was the first recorded rhythm in 240 adult patients (13.8 %). After exclusion of 96 patients, 144 patients with a PEA cardiac arrest admitted to the ED were included in the analysis. The mean age was 63.8 ± 20.0 years, 58.3% were men and the survival rate at 48 hours was 29%. 32 different causes of OHCA PEA were established for 119 patients. For 25 patients (17.4 %), we were unable to attribute a specific cause for the PEA cardiac arrest. Hypoxia (23.6 %), acute coronary syndrome (12.5%) and trauma (12.5 %) were the three most frequent causes. Pulmonary embolism, Hypovolemia, Intoxication and Hyperkaliemia occurs in less than 10% of the cases (7.6 %, 5.6 %, 3.5%, respectively 2.1 %). Non ischemic cardiomyopathy and intra-cranial haemorrhage occur in 8.3 % and 6.9 %, respectively. Conclusions: According to our results, intra-cranial haemorrhage and non-ischemic cardiomyopathy represent noticeable causes of PEA in OHCA, with a prevalence equalling or exceeding the frequency of classical 4 H's and 4 T's aetiologies. These two pathologies are potentially accessible to simple diagnostic procedures (native CT-scan or echocardiography) and should be included into the 4 H's and 4 T's mnemonic.