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In order to enhance the selectivity of metal oxide gas sensors, we use a flow modulation method to exploit transient sensor information. The method is based on modulating the flow of the carrier gas that brings the species to be measured into the sensor chamber. We present an active perception strategy by using a DQN which can optimize the flow modulation online. The advantage of DQN is not only that the classification accuracy is higher than traditional methods such as PCA, but also that it has a good adaptability under small samples and labeled data. Fromobserved values of the sensors array and its past experiences, the DQN learns an action policy to change the flow speed dynamically that maximizes the total rewards (or minimizes the classification error). Meanwhile, a CNN is trained to predict sample class and reward according to current actions and observation of sensors. We demonstrate our proposed methods on a gases classification problem in a real time environment. The results show that the DQN learns to modulate flow to classify different gas and the correct rates of gases are: sesame oil 100%, lactic acid 80%, acetaldehyde 80%, acetic acid 80%, and ethyl acetate 100%, the average correct rate is 88%. Compared with the traditional method, the results of PCA are: sesame oil 100%, acetic acid 24%, acetaldehyde 100%, lactic acid 56%, ethyl acetate 68%, the average accuracy rate is 69.6%. DQN uses fewer steps to achieve higher recognition accuracy and improve the recognition speed, and to reduce the training and testing costs. [ABSTRACT FROM AUTHOR]

In standard critical care practice, cuff sphygmomanometry is widely used for intermittent blood pressure (BP) measurements. However, cuff devices offer ample possibility of modulating blood flow and pulse propagation along the artery. We explore underutilized arrangements of sensors involving cuff devices which could be of use in critical care to reveal additional information on compensatory mechanisms. In our previous work, we analyzed the response of the vasculature to occlusion perturbations by means of observations obtained non-invasively. In this study, our aim is to (1) acquire additional insights by means of invasive measurements and (2) based on these insights, further develop cuff-based measurement strategies. Invasive BP experimental data is collected downstream from the cuff in two patients monitored in the OR. It is found that highly dynamic processes occur in the distal arm during cuff inflation. Mean arterial pressure increases in the distal artery by 20 mmHg, leading to a decrease in pulse transit time by 20 ms. Previous characterizations neglected such distal vasculature effects. A model is developed to reproduce the observed behaviors and to provide a possible explanation of the factors that influence the distal arm mechanisms. We apply the new findings to further develop measurement strategies aimed at acquiring information on pulse arrival time vs. BP calibration, artery compliance, peripheral resistance, artery-vein interaction. [ABSTRACT FROM AUTHOR]