In invasive mechanical ventilation (IMV), it is critical that the flow value is estimated correctly, as it is used as a trigger variable for ventilatory assistance. Furthermore, the numerical integration of the flow a...
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In invasive mechanical ventilation (IMV), it is critical that the flow value is estimated correctly, as it is used as a trigger variable for ventilatory assistance. Furthermore, the numerical integration of the flow allows the calculation of the total volume per breath (tidal volume), which clinicians use to identify trauma or lung capacity in the patient. The current COVID-19 pandemic has demonstrated the need to develop safe and efficient techniques for measuring this spirometry variable because many mechanical ventilators delivered to hospitals were unable to measure it directly. A good device to estimate flow is a D-lite sensor, which works by the Venturi effect, is cheap, reusable, and proximal to the patient. However, the regressions applied to the flow estimation model are limited for use in real conditions. This article presents a flow estimation method that uses a D-Lite device, a fraction of inspired oxygen (FiO(2)) cell, and two pressure sensors as critical items. Our novel method adapts the dichotomous searchalgorithm instead of conventional regression algorithms to estimate flow using a D-lite sensor;this change in the standard procedure allowed us a fast calibration process, a good low-flow estimation, and low computational time for flow estimation. The method was validated experimentally to compute the tidal volume according to the measurement requirement error range of +/-10%. The consideration of FiO(2) percentage in the gas mixture and the good low-flow estimation make this novel method useful for real ventilation conditions. The flow calculations have been performed at different ambient conditions and compared with gas analyzers show an average relative error of up to 4.86%. Finally, we present an analysis of the error flow estimation considering the variation in each variable. Technical recommendations for applying this novel method to achieve IMV safely are presented, based on the capabilities of the embedded system used by developers.
Implementation of the DAC is usually the bottleneck in designing a SAR ADC. Here an innovative DAC-less SAR (DLSAR) ADC architecture is presented which alleviates some drawbacks of the conventional SAR counterpart. Th...
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Implementation of the DAC is usually the bottleneck in designing a SAR ADC. Here an innovative DAC-less SAR (DLSAR) ADC architecture is presented which alleviates some drawbacks of the conventional SAR counterpart. The proposed DLSAR binary search algorithm is comprised of two arithmetic operations of division-by-two and subtraction to emulate the DAC function. The hardware of the DLSAR ADC is implemented using ordinary circuit building blocks of a SAR ADC but with less complexity and more robustness against PVT variations as DAC is removed. The developed DLSAR architecture is versatile so that the converter hardware could be readily reconfigured for different sampling rates and resolutions. Based on post-layout simulations in 0.18 mu m CMOS process, the designed 8-bit DLSAR ADC consumes 150 mu W of power at 2 MS/s including the asynchronous control logic circuit. The SFDR of the converter is up to 62 dB and the ENOB reaches 7.8 bits while it remains above 7.5 bits across most PVT corners without calibration. Also, by reconfiguring the DLSAR ADC to 9-bit resolution at 1 MS/s, the ENOB is generally around 8.2 bits achieving a scaled figure-of-merit (SFoM) better than 3.0 c/c-s.
This paper gives a straightforward method to determine the values of excitation capacitors of a standalone short-shunt six-phase induction generator (SPIG) to maintain the voltage profile within predetermined percenta...
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