SummaryTheoretical modelling predicts that the concentrating effect of nitrous oxide (N 2 O) uptake on alveolar oxygenation is a persisting phenomenon at typical levels of ventilation -perfusion (V ⁄ Q) inhomogeneity under anaesthesia. We sought clinical confirmation of this in 20 anaesthetised patients. Arterial oxygen pressure (P a O 2 ) was measured after a minimum of 30 min of relaxant general anaesthesia with an inspired oxygen (F I O 2 ) of 30%. Patients were randomly allocated to two groups. The intervention group had N 2 O introduced following baseline blood gas measurements, and the control group continued breathing an identical F I O 2 in nitrogen (N 2 ). The primary outcome variable was change in P a O 2 . Mean (SD) in P a O 2 was increased by 1.80 (1.80) kPa after receiving a mean of 47.5 min of N 2 O compared with baseline conditions breathing O 2 ⁄ N 2 (p = 0.01). This change was significantly greater (p = 0.03) than that in the control group: + 0.09 (1.37) kPa, p = 0.83 and confirms the presence of significant persisting concentrating and second gas effects. The concentrating and second gas effects of nitrous oxide (N 2 O) uptake on the alveolar partial pressure of oxygen (O 2 ) and volatile agents were described by Eger and Stoelting [1, 2]. They detailed how these effects are produced by the initial rapid uptake of N 2 O for the first several minutes of an inhalational anaesthetic, during which time the rate of N 2 O uptake sharply declines. Subsequent authors have followed the effect on end-tidal and arterial partial pressures with serial measurements, and some authors have questioned the clinical validity of the phenomenon, at least in relation to its effect on volatile agent concentrations [3]. However, Nishikawa et al. found a measurable effect on end-tidal O 2 concentration and arterial oxygen tension (P a O 2 ) up to 30 min after commencement of N 2 O [4]. These largely descriptive studies have been variously uncontrolled for important physiological factors that might potentially influence the effect, such as cardiac output, ventilation-perfusion matching, or time.More recently, computer modelling of alveolar gas exchange predicted that the better arterial oxygenation that results may not be short lived, but may persist indefinitely [5,6]. This prolonged effect is only predicted to be significant in the presence of moderately severe degrees of ventilation-perfusion (V ⁄ Q) inhomogeneity, and is due to ongoing N 2 O uptake in low V ⁄ Q lung units [6]. These levels of V ⁄ Q inhomogeneity are typical of anaesthetised patients, even those with healthy lungs [7][8][9][10][11]. However, N 2 O accelerates absorption atelectasis in regions of low V ⁄ Q [12,13] and may worsen shunting
The use of speech recognition in noisy environments requires the use of speech enhancement algorithms in order to improve recognition performance. Deploying these enhancement techniques requires significant engineering to ensure algorithms are realisable in electronic hardware. This paper describes the design decisions and process to port the popular spectral subtraction algorithm to a Virtex-4 field-programmable gate array (FPGA) device. Resource analysis shows the final design uses only 13% of the total available FPGA resources. Waveforms and spectrograms presented support the validity of the proposed FPGA design.Index Terms-Field programmable gate arrays, speech enhancement, road vehicles.
The use of speech recognition in noisy automotive environments requires the application of speech enhancement algorithms to improve recognition performance. Deploying these enhancement techniques necessitates significant engineering to ensure algorithms are realisable in electronic hardware. This paper describes advances in porting the popular spectral subtraction algorithm to a Spartan-3A DSP field-programmable gate array (FPGA) device suitable for integration in automotive environments. Resource analysis shows the final design uses only 13% of the total available general logic resources making it suitable for integration with other in-car devices on a single FPGA. Speech recognition experiments have been used to verify the effectiveness of the FPGA implementation for in-car speech recognition in comparison with an equivalent floating-point implementation.
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