IEEE transactions on bio-medical engineering
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The effect of skin, muscle, fat, and bone tissue on simulated surface electromyographic (EMG) signals was examined using a finite-element model. The amplitude and frequency content of the surface potential were observed to increase when the outer layer of a homogeneous muscle model was replaced with highly resistive skin or fat tissue. The rate at which the surface potential decreased as the fiber was moved deeper within the muscle also increased. ⋯ The influence of bone on the surface potential was observed to vary considerably, depending on its location. When located close to the surface of the volume conductor, the surface EMG signal between the bone and the source and directly over the bone increased, accompanied by a slight decrease on the side of the bone distal to the active fiber. The results emphasize the importance of distinguishing between the effects of material properties and the distance between source and electrode when considering the influence of subcutaneous tissue, and suggest possible distortions in the surface EMG signal in regions where a bone is located close to the skin surface.
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IEEE Trans Biomed Eng · May 2002
Comparative StudyThe oral glucose minimal model: estimation of insulin sensitivity from a meal test.
Recently, a new approach has been proposed to estimate insulin sensitivity (S(I)) from an oral glucose tolerance test or a meal using an "integral equation". Here, we improve on the "integral equation" by resorting to a "differential equation" approach. The classic glucose kinetics minimal model was used with the addition of a parametric model for the rate of appearance into plasma of oral glucose (Ra). ⋯ S(I) strongly correlated with the integral-equation index (I) S(I)I: r = 0.99, p < 0.01 for models D and S, and r 0.97, p < 0.01 for P. Also, SI compared well with insulin sensitivity estimated from intravenous glucose tolerance test in the same subjects (r = 0.75, p < 0.01; r = 0.71, p < 0.01; r = 0.73, p < 0.01, respectively, for P, S, and D models versus s(I)IVGTT). Finally, the novel approach allows estimation of SI from a shorter test (120 min): model P yielded S(I)R = 7.16 +/- 1.0 (R for reduced) which correlated very well with S(I)P and S(I)I (respectively, r = 0.94, p < 0.01; r = 0.95, p < 0.01) and still satisfactorily with S(I)IVGTT (r = 0.77, p < 0.01).
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Traditionally, input impedance (Z(in)) has been used to characterize the global dynamic properties of an arterial system independent of properties of the heart. Defined as the relationship of pressure and flow at the entrance of an arterial system, it describes the ability of an arterial system to dynamically impede blood flow. Recently, a new description has been developed that also characterizes the arterial system independent of properties of the heart. ⋯ However, the functional form of Capp lends itself to describing the arterial system in terms of negative feedback. Pulse wave reflection decreases the pulsatile volume stored (gain) at low frequencies, but increases the range of frequencies (bandwidth) in which the pulsatile volume is determined by total arterial compliance. This paper illustrates, by simple analytical formula, large-scale arterial system modeling, and direct analysis of data, how this conceptualization of reflection offers a new means to interpret changes in arterial system dynamics resulting from changes in arterial compliance.