Annals of biomedical engineering
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We propose a new algorithm for real-time estimation of instantaneous heart rate (HR) from noise-laden electrocardiogram (ECG) waveforms typical of unstructured, ambulatory field environments. The estimation of HR from ECG waveforms is an indirect measurement problem that requires differencing, which invariably amplifies high-frequency noise. We circumvented noise amplification by considering the estimation of HR as the solution of a weighted regularized least squares problem, which, in addition, directly provided analytically based confidence intervals (CIs) for the estimated HRs. ⋯ The simulation results indicated that our algorithm consistently produced more accurate HR estimates, with estimation errors as much as 67% smaller than those attained by the postprocessing methods, while the results with the field-collected data showed that the proposed algorithm produced much smoother and reliable HR estimates than those obtained by the vital-sign monitor. Moreover, the obtained CIs reflected the amount of noise in the ECG recording and could be used to statistically quantify uncertainties in the HR estimates. We conclude that the proposed method is robust to different types of noise and is particularly suitable for use in ambulatory environments where data quality is notoriously poor.
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In this article, we present a point process method to assess dynamic baroreflex sensitivity (BRS) by estimating the baroreflex gain as focal component of a simplified closed-loop model of the cardiovascular system. Specifically, an inverse Gaussian probability distribution is used to model the heartbeat interval, whereas the instantaneous mean is identified by linear and bilinear bivariate regressions on both the previous R-R intervals (RR) and blood pressure (BP) beat-to-beat measures. The instantaneous baroreflex gain is estimated as the feedback branch of the loop with a point-process filter, while the RR-->BP feedforward transfer function representing heart contractility and vasculature effects is simultaneously estimated by a recursive least-squares filter. ⋯ To illustrate the application, we have applied the proposed point process model to experimental recordings from 11 healthy subjects in order to monitor cardiovascular regulation under propofol anesthesia. We present quantitative results during transient periods, as well as statistical analyses on steady-state epochs before and after propofol administration. Our findings validate the ability of the algorithm to provide a reliable and fast-tracking assessment of BRS, and show a clear overall reduction in baroreflex gain from the baseline period to the start of propofol anesthesia, confirming that instantaneous evaluation of arterial baroreflex control of HR may yield important implications in clinical practice, particularly during anesthesia and in postoperative care.
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Intervertebral disks support compressive forces because of their elastic stiffness as well as the fluid pressures resulting from poroelasticity and the osmotic (swelling) effects. Analytical methods can quantify the relative contributions, but only if correct material properties are used. To identify appropriate tissue properties, an experimental study and finite element analytical simulation of poroelastic and osmotic behavior of intervertebral disks were combined to refine published values of disk and endplate properties to optimize model fit to experimental data. ⋯ The relaxation of the force in the three bath concentrations was exponential in form, expressed as mean compressive force loss of 48.7, 55.0, and 140 N, respectively, with time constants of 1.73, 2.78, and 3.40 h. This behavior was analytically well represented by a model having poroelastic and osmotic tissue properties with published tissue properties adjusted by multiplying factors between 0.55 and 2.6. Force relaxation and time constants from the analytical simulations were most sensitive to values of fixed charge density and endplate porosity.
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The purpose of this study was to implement a new lactate-edited 3D 1H magnetic resonance spectroscopic imaging (MRSI) sequence at 3 T and demonstrate the feasibility of using this sequence for measuring lactate in patients with gliomas. A 3D PRESS MRSI sequence incorporating shortened, high bandwidth 180° pulses, new dual BASING lactate-editing pulses, high bandwidth very selective suppression (VSS) pulses and a flyback echo-planar readout was implemented at 3 T. Over-prescription factor of PRESS voxels was optimized using phantom to minimize chemical shift artifacts. ⋯ The normalized SNR of brain metabolites using the flyback encoding were comparable to the SNR of brain metabolites using conventional phase encoding MRSI. The specialized lactate-edited 3D MRSI sequence was able to detect lactate in brain tumor patients at 3 T. The implementation of this technique means that brain lactate can be evaluated in a routine clinical setting to study its potential as a marker for prognosis and response to therapy.
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Cine-phase-contrast-MRI was used to measure the three-dimensional cerebrospinal fluid (CSF) flow field inside the central nervous system (CNS) of a healthy subject. Image reconstruction and grid generation tools were then used to develop a three-dimensional fluid-structure interaction model of the CSF flow inside the CNS. The CSF spaces were discretized using the finite-element method and the constitutive equations for fluid and solid motion solved in ADINA-FSI 8.6. ⋯ The pressure wave speed in the spinal canal was predicted and found to agree closely with values previously reported in the literature. Finally, the forward and backward motion of the CSF in the ventricles was visualized, revealing the complex mixing patterns in the CSF spaces. The mathematical model presented in this article is a prerequisite for developing a mechanistic understanding of the relationships among vasculature pulsations, CSF flow, and CSF pressure waves in the CNS.