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The article discusses the use of artificial intelligence (AI) and Internet of Things (IoT) technology in healthcare. It highlights how intelligent technology can assist clinicians in diagnosis and treatment, and how wearable devices with embedded algorithms can capture patient data. The article emphasizes the importance of sensor technology, body sensor networks, and AI techniques in patient monitoring and healthcare. It also presents several research studies that utilize AI and machine learning for various healthcare applications, such as blood glucose monitoring, tetanus severity detection, esophageal motility disorder diagnosis, and COVID-19 detection. The article concludes by discussing the challenges and future directions in implementing AI and IoT in healthcare. [Extracted from the article]

Heart failure is a prevalent cardiovascular condition with significant health implications, necessitating effective diagnostic strategies for timely intervention. This study explores the potential of continuous monitoring of non-invasive signals, specifically integrating photoplethysmogram (PPG) and electrocardiogram (ECG), for enhancing early detection and diagnosis of heart failure. Leveraging a dataset from the MIMIC-III database, encompassing 682 heart failure patients and 954 controls, our approach focuses on continuous, non-invasive monitoring. Key features, including the QRS interval, RR interval, augmentation index, heart rate, systolic pressure, diastolic pressure, and peak-to-peak amplitude, were carefully selected for their clinical relevance and ability to capture cardiovascular dynamics. This feature selection not only highlighted important physiological indicators but also helped reduce computational complexity and the risk of overfitting in machine learning models. The use of these features in training machine learning algorithms led to a model with impressive accuracy (98%), sensitivity (97.60%), specificity (96.90%), and precision (97.20%). Our integrated approach, combining PPG and ECG signals, demonstrates superior performance compared to single-signal strategies, emphasizing its potential in early and precise heart failure diagnosis. The study also highlights the importance of continuous monitoring with wearable technology, suggesting a significant stride forward in non-invasive cardiovascular health assessment. The proposed approach holds promise for implementation in hardware systems to enable continuous monitoring, aiding in early detection and prevention of critical health conditions. [ABSTRACT FROM AUTHOR]

To control the spread of coronavirus disease 2019 (COVID-19), it is effective to perform a fast screening of the respiratory rate of the subject at the gate before entering a space to assess the potential risks. In this paper, we examine the potential of a novel yet cost-effective solution, called thermopile-based respiratory gating, to contactlessly screen a subject by measuring their respiratory rate in the scenario with an entrance gate. Based on a customized thermopile array system, we investigate different image and signal processing methods that measure respiratory rate from low-resolution thermal videos, where an automatic region-of-interest selection-based approach obtains a mean absolute error (MAE) of 0.8 breaths per minute. We show the feasibility of thermopile-based respiratory gating and quantify its limitations and boundary conditions in a benchmark (e.g., appearance of face mask, measurement distance and screening time). The technical validation provided by this study is helpful for designing and implementing a respiratory gating solution toward the prevention of the spread of COVID-19 during the pandemic. [ABSTRACT FROM AUTHOR]

This paper reports a method for electrical communication between the inner part of cells and an electrode with the help of iRGD peptide. Due to the enhancement of the cell penetration caused by iRGD peptide, DNA molecules, previously modified on a gold electrode surface, can be easily transfected into the cells. At the same time, doxorubicin, an anticancer drug, can also be transfected into cells with high penetration. Consequently, doxorubicin binds to DNA chains through electrostatic interaction, and the redox reaction is transferred out of the cell across the cell membrane. As a result, this work may provide a novel way to get information from inside of cells.