7 research outputs found

    A Novel Respiratory Rate Estimation Algorithm from Photoplethysmogram Using Deep Learning Model

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    Respiratory rate (RR) is a critical vital sign that can provide valuable insights into various medical conditions, including pneumonia. Unfortunately, manual RR counting is often unreliable and discontinuous. Current RR estimation algorithms either lack the necessary accuracy or demand extensive window sizes. In response to these challenges, this study introduces a novel method for continuously estimating RR from photoplethysmogram (PPG) with a reduced window size and lower processing requirements. To evaluate and compare classical and deep learning algorithms, this study leverages the BIDMC and CapnoBase datasets, employing the Respiratory Rate Estimation (RRest) toolbox. The optimal classical techniques combination on the BIDMC datasets achieves a mean absolute error (MAE) of 1.9 breaths/min. Additionally, the developed neural network model utilises convolutional and long short-term memory layers to estimate RR effectively. The best-performing model, with a 50% train–test split and a window size of 7 s, achieves an MAE of 2 breaths/min. Furthermore, compared to other deep learning algorithms with window sizes of 16, 32, and 64 s, this study’s model demonstrates superior performance with a smaller window size. The study suggests that further research into more precise signal processing techniques may enhance RR estimation from PPG signals

    Advancing Retail Operations: A Customizable IoT-Based Smart Inventory System

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    The retail sector has encountered formidable challenges in recent years, particularly concerning food sustainability and the need for reduced manpower, which have been further exacerbated by the COVID-19 pandemic. The inventory management process involves critical tasks such as environment checking, product inspection, and stock arrangement, all of which are essential for maintaining product quality. Price label management is another crucial aspect of retail operations, providing key information to potential customers. However, the labor-intensive process of installing and replacing price labels, as well as adapting to market trends, poses efficiency and sustainability concerns. To address the aforementioned challenges, we have proposed an IoT-based inventory management system that consists of three interconnected components: a smart shelf that keeps real-time track of humidity, temperature, and air index; electronic shelf labeling that allows for easy updating of product information from mobile/PC devices; and RFID-based stock sorting to track product in/out and location. Hence, the proposed integrated solution significantly enhances operational efficiency, reduces overall workload, optimizes inventory management tasks, streamlines operations, and mitigates financial losses associated with inefficient processes

    Impact Comparison of El Niño and Ageing Crops on Malaysian Oil Palm Yield

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    Ageing oil palm crops show a significant correlation with the declining oil palm yield in Malaysia. Not only do aged crops result in lower production, but they are also more costly and difficult to harvest. The Malaysian oil palm yield recovered to the pre-El Niño level after the 1997/98 El Niño event. However, the oil palm yield failed to recover after the recent 2015/16 El Niño. Due to the accumulation of aged oil palm plantations in Malaysia, the financial losses from different magnitudes of El Niño events are increasing. Thirty-four years of monthly oil palm yield trends in Malaysia were compared with the El Niño–free yield dataset to show that the oil palm yield downtrend pattern is the same with or without El Niño events in Malaysia for the most recent 15 years (2005 to 2019). The performance of oil palm yield did not show any significant difference from 2000 to 2019. This study estimates that ageing oil palms would lead to a minimum opportunity loss of USD 431 million by December 2022. Without a proper replanting program, the total combined loss attributable to the ageing crops from 2009 to 2022 is estimated to be USD 3.94 billion, which is more profound than losses due to El Niño events within the same period. This study also concluded that a continuous 7-year replanting scheme of at least 115,000 hectares per year is needed to address the adverse impact of ageing crops on the Malaysian oil palm yield, which accounts for nearly 30% of the global palm oil production

    Is perioperative COVID-19 really associated with worse surgical outcomes? A nationwide COVIDSurg propensity-matched analysis

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    BACKGROUND: Patients undergoing surgery with perioperative COVID-19 are suggested to have worse outcomes, but whether this is COVID-related or due to selection bias remains unclear. We aimed to compare the postoperative outcomes of patients with and without perioperative COVID-19. METHODS: Patients with perioperative COVID-19 diagnosed within 7 days before or 30 days after surgery between February and July 2020 from 68 US hospitals in COVIDSurg, an international multicenter database, were 1:1 propensity score matched to patients without COVID-19 undergoing similar procedures in the 2012 American College of Surgeons National Surgical Quality Improvement Program database. The matching criteria included demographics (e.g., age, sex), comorbidities (e.g., diabetes, chronic obstructive pulmonary disease, chronic kidney disease), and operation characteristics (e.g., type, urgency, complexity). The primary outcome was 30-day hospital mortality. Secondary outcomes included hospital length of stay and 13 postoperative complications (e.g., pneumonia, renal failure, surgical site infection). RESULTS: A total of 97,936 patients were included, 1,054 with and 96,882 without COVID-19. Prematching, COVID-19 patients more often underwent emergency surgery (76.1% vs. 10.3%, p < 0.001). A total of 843 COVID-19 and 843 non-COVID-19 patients were successfully matched based on demographics, comorbidities, and operative characteristics. Postmatching, COVID-19 patients had a higher mortality (12.0% vs. 8.1%, p = 0.007), longer length of stay (6 [2-15] vs. 5 [1-12] days), and higher rates of acute renal failure (19.3% vs. 3.0%, p < 0.001), sepsis (13.5% vs. 9.0%, p = 0.003), and septic shock (11.8% vs. 6.0%, p < 0.001). They also had higher rates of thromboembolic complications such as deep vein thrombosis (4.4% vs. 1.5%, p < 0.001) and pulmonary embolism (2.5% vs. 0.4%, p < 0.001) but lower rates of bleeding (11.6% vs. 26.1%, p < 0.001). CONCLUSION: Patients undergoing surgery with perioperative COVID-19 have higher rates of 30-day mortality and postoperative complications, especially thromboembolic, compared with similar patients without COVID-19 undergoing similar surgeries. Such information is crucial for the complex surgical decision making and counseling of these patients. (J Trauma Acute Care Surg. 2023;94: 513-524. Copyright (C) 2023 American Association for the Surgery of Trauma.)LEVEL OF EVIDENCE: Prognostic and Epidemiologic; Level IV

    Outcomes and Their State-level Variation in Patients Undergoing Surgery With Perioperative SARS-CoV-2 Infection in the USA. A Prospective Multicenter Study

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    Objective: To report the 30-day outcomes of patients with perioperative SARS-CoV-2 infection undergoing surgery in the USA. Background: Uncertainty regarding the postoperative risks of patients with SARS-CoV-2 exists. Methods: As part of the COVIDSurg multicenter study, all patients aged ≥17 years undergoing surgery between January 1 and June 30, 2020 with perioperative SARS-CoV-2 infection in 70 hospitals across 27 states were included. The primary outcomes were 30-day mortality and pulmonary complications. Multivariable analyses (adjusting for demographics, comorbidities, and procedure characteristics) were performed to identify predictors of mortality. Results: A total of 1581 patients were included; more than half of them were males (n = 822, 52.0%) and older than 50 years (n = 835, 52.8%). Most procedures (n = 1261, 79.8%) were emergent, and laparotomies (n = 538, 34.1%). The mortality and pulmonary complication rates were 11.0 and 39.5%, respectively. Independent predictors of mortality included age ≥70 years (odds ratio 2.46, 95% confidence interval [1.65-3.69]), male sex (2.26 [1.53-3.35]), ASA grades 3-5 (3.08 [1.60-5.95]), emergent surgery (2.44 [1.31-4.54]), malignancy (2.97 [1.58-5.57]), respiratory comorbidities (2.08 [1.30-3.32]), and higher Revised Cardiac Risk Index (1.20 [1.02-1.41]). While statewide elective cancelation orders were not associated with a lower mortality, a sub-analysis showed it to be associated with lower mortality in those who underwent elective surgery (0.14 [0.03-0.61]). Conclusions: Patients with perioperative SARS-CoV-2 infection have a significantly high risk for postoperative complications, especially elderly males. Postponing elective surgery and adopting non-operative management, when reasonable, should be considered in the USA during the pandemic peaks
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