A real-time and convex model for the estimation of muscle force from surface electromyographic signals in the upper and lower limbs

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Abstract

Low-volume lung injury encompasses local concentration of stresses in the vicinity of collapsed regions in heterogeneously ventilated lungs. We aimed to study the effects on ventilation and perfusion distributions of a sequential lateral positioning (30°) strategy using electrical impedance tomography imaging in a porcine experimental model of early acute respiratory distress syndrome (ARDS). We hypothesized that such strategy, including a real-time individualization of positive end-expiratory pressure (PEEP) whenever in lateral positioning, would provide attenuation of collapse in the dependent lung regions. A two-hit injury acute respiratory distress syndrome experimental model was established by lung lavages followed by injurious mechanical ventilation. Then, all animals were studied in five body positions in a sequential order, 15 min each: Supine 1; Lateral Left; Supine 2; Lateral Right; Supine 3. The following functional images were analyzed by electrical impedance tomography: ventilation distributions and regional lung volumes, and perfusion distributions. The induction of the acute respiratory distress syndrome model resulted in a marked fall in oxygenation along with low regional ventilation and compliance of the dorsal half of the lung (gravitational-dependent in supine position). Both the regional ventilation and compliance of the dorsal half of the lung greatly increased along of the sequential lateral positioning strategy, and maximally at its end. In addition, a corresponding improvement of oxygenation occurred. In conclusion, our sequential lateral positioning strategy, with sufficient positive end-expiratory pressure to prevent collapse of the dependent lung units during lateral positioning, provided a relevant diminution of collapse in the dorsal lung in a porcine experimental model of early acute respiratory distress syndrome.

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Shirzadi, M. [et al.]. A real-time and convex model for the estimation of muscle force from surface electromyographic signals in the upper and lower limbs. "Frontiers in physiology", Febrer 2023, vol. 14.

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1664-042X

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