Recent development of respiratory rate measurement technologies

Respiratory rate (RR) is an important physiological parameter whose abnormity has been regarded as an important indicator of serious illness. In order to make RR monitoring simple to do, reliable and accurate, many different methods have been proposed for such automatic monitoring. According to the theory of respiratory rate extraction, methods are categorized into three modalities: extracting RR from other physiological signals, RR measurement based on respiratory movements, and RR measurement based on airflow. The merits and limitations of each method are highlighted and discussed. In addition, current works are summarized to suggest key directions for the development of future RR monitoring methodologies

A robust fusion model for estimating respiratory rate from photoplethysmography and electrocardiography

Objective: Respiratory rate (RR) estimation algorithms based on the photoplethymogram (PPG) and electrocardiogram (ECG) lack clinical robustness. This is because the PPG and ECG respiratory modulations are dependent on patient physiology, regardless of general signal quality. The present work describes an RR estimation algorithm using respiratory quality indices (RQIs) which assess the presence or absence of the PPGand ECG-derived respiratory modulations. Methods: Six respiratory waveforms are derived from the amplitude modulation, frequency modulation, and baseline wander of the PPG and ECG. The respiratory quality of each modulation is assessed using RQIs based on the FFT, autoregression, and autocorrelation. The individual RQIs are fused to obtain a single RQI per modulation per time window. Based on a tunable threshold, the RQIs are used to discard poor modulations and weight the remaining modulations to provide a single RR estimation per time window. Results: The proposed method was tested on two independent data sets and found that using a conservative threshold, the mean absolute error (MAE) was 0.71 andplusmn; 0.89 and 3.12 andplusmn; 4.39 brpm while discarding only 1.3% and 23.2% of all time windows, for each data set, respectively. Conclusion: These errors are either better than or comparable to current methods, and the number of windows discarded is far lower demonstrating improved robustness. Significance: This work describes a novel pre-processing algorithm that can be implemented in conjunction with other RR estimation techniques to improve robustness by specifically considering the quality of the respiratory information.</p

Development and validation of early warning score systems for COVID-19 patients

COVID-19 is a major, urgent, and ongoing threat to global health. Globally more than 24 million have been infected and the disease has claimed more than a million lives as of November 2020. Predicting which patients will need respiratory support is important to guiding individual patient treatment and also to ensuring sufficient resources are available. The ability of six common Early Warning Scores (EWS) to identify respiratory deterioration defined as the need for advanced respiratory support (high-flow nasal oxygen, continuous positive airways pressure, non-invasive ventilation, intubation) within a prediction window of 24 h is evaluated. It is shown that these scores perform sub-optimally at this specific task. Therefore, an alternative EWS based on the Gradient Boosting Trees (GBT) algorithm is developed that is able to predict deterioration within the next 24 h with high AUROC 94% and an accuracy, sensitivity, and specificity of 70%, 96%, 70%, respectively. The GBT model outperformed the best EWS (LDTEWS:NEWS), increasing the AUROC by 14%. Our GBT model makes the prediction based on the current and baseline measures of routinely available vital signs and blood tests

Breeding behaviour of Kunzea pomifera (Myrtaceae): self-incompatibility, intraspecific and interspecific cross-compatibility

To examine breeding system characteristics of the endemic Australian prostrate shrub Kunzea pomifera, artificial hybridisations were undertaken using thirteen different genotypes of K. pomifera, to elucidate: (1) self-incompatibility, (2) intraspecific cross-compatibility in the species and (3) interspecific cross-compatibility with each of K. ambigua and K. ericoides. K. pomifera exhibited very low self-compatibility, with the barrier to self-fertilisation being prevention of pollen-tube growth in the style or ovary. Following intraspecific pollination amongst a number of different genotypes of K. pomifera, 38.4% of pollinated flowers developed fruit; arrest of compatible pollen-tubes in the style, preventing fertilisation, contributes to the low fruit set in this species. Interspecific compatibility was examined between K. pomifera (pistillate parent) and K. ambigua (staminate parent) where seed set per pollinated flower (4.47) was not significantly different from intraspecific crosses (4.66). In crosses between K. pomifera (pistillate parent) and K. ericoides as staminate plant, 0.037% of pollinated flowers produced fruit, with 0.0075 seeds per pollinated flower. Reproductive barriers between these two species were evident in the style of K. pomifera, where the growing tips of the K. ericoides pollen-tubes swelled and ceased to grow