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Liyuan Ren, Jinjin Yang, Yanshuang Li, Yanping Wang Department of Anesthesiology, Pain and Perioperative Medicine, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, People’s Republic of ChinaCorrespondence: Yanping Wang, Department of Anesthesiology, Pain and Perioperative Medicine, the First Affiliated Hospital of Zhengzhou University, No. 1 East Jianshe Road, Zhengzhou, 450052, People’s Republic of China, Tel +86-371-13526857360, Email 282243756@qq.comPurpose: To investigate and quantify the effect of continuous esketamine infusion at different doses on the bispectral index (BIS) during sevoflurane anesthesia.Methods: A total of 120 patients scheduled for elective laparoscopic renal surgery were randomly divided into three groups. Under steady anesthesia and surgical situations, the patient was started on continuous infusion of the study drug: 0.125 mg/kg/h esketamine (group E1), 0.25 mg/kg/h esketamine (group E2), and the same volume of saline (group C). The primary outcome was changes in BIS value after 15 min (T15), 30 min (T30), 45 min (T45), and 60 min (T60) of drug infusion. The secondary outcomes were 95% spectral edge frequency (SEF95), electromyogram (EMG), heart rate (HR), and mean arterial pressure (MAP) from T0 to T60. Furthermore, postoperative pain, postoperative recovery, and perioperative adverse events were evaluated.Results: Compared with group C, group E1 exhibited significant BIS elevation at T30–T60 and group E2 at T15–T60 (P < 0.001). Compared with group E1, group E2 showed a more significant BIS elevation at T15–T60 (P < 0.001). The area under the curve (AUC) of BIS and SEF95 were significantly higher in group E2 than in groups C and E1 (P < 0.05). BIS value for any of the three groups was significantly correlated with SEF95 (P < 0.001). No significant differences were observed in the AUC of EMG, HR, and MAP among the three groups. Intraoperative remifentanil consumption and postoperative NRS of p

The problem of radar-based counting of multiple individuals moving as a single group is addressed using an mm-wave multiple-input-multiple-output (MIMO) frequency-modulated continuous wave (FMCW) radar. This problem is challenging because the different individuals are closer to each other than the range/azimuth resolution, and their bulk Doppler signatures are difficult to distinguish, as they tend to move together. A processing pipeline is proposed, based on the combination of a multiple target tracking algorithm with a classifier to track each group and count the number of people within. Specific salient features are defined for the classifier and extracted from range-azimuth maps and cadence velocity diagrams (CVDs). The proposed pipeline has been experimentally validated in several outdoor scenarios with grouped people. The results show that the combination of tracking algorithm and classifier in the proposed pipeline outperforms alternative methods from the literature as well as a commercial toolbox for people counting., Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Microwave Sensing, Signals & Systems

For the development of automatic People Counting systems, radar is increasingly becoming a popular technology because of the increasingly stringent privacy requirements for people demographic information and the requirement to operate in a challenging environment. Because of the complexity of multi-target movement and the diversity of application scenarios, Radar-based People Counting methods are required to have sufficient robustness. However, based on the review of the current literature, the grouping phenomenon (i.e., multiple individuals moving close together as a single group) was not often considered in the experimental scenarios. This thesis aims to study one of the most complex motions of individuals, grouping, and address the People Counting problem more in general, including the cases of grouping of multiple individuals. After studying the characteristics of Group People (defined as a group of people sharing neighboring, adjacent locations and moving together), with the help of multiple-input-multiple-output (MIMO) frequency-modulated continuous wave (FMCW) Radar, the combination of the Range-Azimuth map and spectrogram/cadence velocity diagram (CVD) is proposed to solve Group People Counting. Algorithm-wise, there are two categories of existing Radar-based People Counting methods, namely, tracking for counting methods and feature-based counting methods. It was found that these two categories of methods have complementary strengths. Thus, the proposed method combines the tracking for counting approach and feature-based counting approach into a new processing pipeline to estimate the number of people in each group in the scene while tracking each group. Based on it, the proposed method achieves "Beyond classification", which is the output the unlabeled classes not defined at the training stage. Moreover, compared with other state-of-the-art (SOTA) Radar-based People Counting methods, the proposed method outperforms them, and thus it is p, Electrical Engineering