FM-FCN: A Neural Network with Filtering Modules for Accurate Vital Signs Extraction.

Neural networks excel at capturing local spatial patterns through convolutional modules, but they may struggle to identify and effectively utilize the morphological and amplitude periodic nature of physiological signals. In this work, we propose a novel network named filtering module fully convolutional network (FM-FCN), which fuses traditional filtering techniques with neural networks to amplify physiological signals and suppress noise. First, instead of using a fully connected layer, we use an FCN to preserve the time-dimensional correlation information of physiological signals, enabling multiple cycles of signals in the network and providing a basis for signal processing.

MEAs-Filter: a novel filter framework utilizing evolutionary algorithms for cardiovascular diseases diagnosis.

Cardiovascular disease management often involves adjusting medication dosage based on changes in electrocardiogram (ECG) signals' waveform and rhythm. However, the diagnostic utility of ECG signals is often hindered by various types of noise interference. In this work, we propose a novel filter based on a multi-engine evolution framework named MEAs-Filter to address this issue.

Evaluation of dressings preventing facial medical device-related pressure injury in medical staff during the COVID-19 pandemic: A systematic review and network meta-analysis.

Aim: This study systematically compared the efficacy of various dressings that may prevent facial medical device-related pressure injury (MRDPI) in medical staff during the COVID-19 pandemic.

Background: During the COVID-19 pandemic, medical staff who are required to wear masks, goggles and other personal protective equipment (PPE) are susceptible to facial MRDPI, which exacerbates working conditions. Dressings can effectively prevent or alleviate MRDPI, but it is unclear which dressings are most effective.

Influencing factors of medical device-related pressure ulcers in medical personnel during the COVID-19 pandemic: A systematic review and meta-analysis.

Objective: To determine the influencing factors of medical device related pressure injury (MDRPU) in medical staff by meta-analysis.

Methods: A comprehensive literature search was conducted by PubMed, Embase, Cochrane Library, Web of Science, CNKI, VIP, CBM, and WanFang Data (from inception to July 27, 2022). Two researchers independently performed literature screening, quality evaluation and data extraction, and meta-analysis was conducted with RevMan 5.

Incidence of facial pressure injuries in health-care professionals during the COVID-19 pandemic: A systematic review and meta-analysis.

Aim: To evaluate the incidence of facial pressure injuries in health-care professionals during the COVID-19 pandemic in a meta-analysis.

Methods: Related studies were obtained through electronic databases, including PubMed, Embase, Cochrane Library, Web of Science, China National Knowledge Infrastructure (CNKI) Chinese Scientific Journal (VIP) China Biomedical Literature service systems (CBM) and Wanfang Data (from inception to 27 November 2021). The pooled incidence and the 95% confidence interval of facial pressure injuries were calculated with Review Manager v5.

The effect of abdominal massage on enteral nutrition tolerance in patients on mechanical ventilation: A Randomized Controlled Study.

Objective: To assess whether abdominal massage impacts enteral feeding tolerance in mechanically ventilated patients.

Methods: Patients were randomized to receive standard or intervention care (standard care plus a 15-minute abdominal massage twice daily) for three days. We recorded the vomiting, reflux, gastric retention, aspiration, diarrhea, abdominal distension, gastric residual volume and abdominal circumference from days one to three.

Evaluation of evidence of prevention and management of facial pressure injuries in medical staff.

Aim: This systematic review evaluated the quality of evidence for the prevention and management of facial pressure injuries in medical staff.

Design: This review was presented in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines.

Methods: We retrieved the relevant studies from 19 databases.

Epidermal Inorganic Optoelectronics for Blood Oxygen Measurement.

Flexible and stretchable optoelectronics, built-in inorganic semiconductor materials, offer a wide range of unprecedented opportunities and will redefine the conventional rigid optoelectronics in biological application and medical measurement. However, a significant bottleneck lies in the brittleness nature of rigid semiconductor materials and the performance's extreme sensitivity to the light intensity variation due to human skin deformation while measuring physical parameters. In this study, the authors demonstrate a systematic strategy to design an epidermal inorganic optoelectronic device by using specific strain-isolation design, nanodiamond thinning, and hybrid transfer printing.

Buckling-Based Method for Measuring the Strain-Photonic Coupling Effect of GaAs Nanoribbons.

The ability to continuously and reversibly tune the band gap and the strain-photonic coupling effect in optoelectronic materials is highly desirable for fundamentally understanding the mechanism of strain engineering and its applications in semiconductors. However, optoelectronic materials (i.e.

Measurements for displacement and deformation at high temperature by using edge detection of digital image.

In this work, we propose a structural deformation measuring method based on structural feature processing (straight line/edge detection) of the recorded digital images for specimens subjected to a high-temperature environment. Both radiation light and oxidation at high temperatures challenge the optics-based measurements. The images of a rectangular piece of copper specimen are obtained by using a bandpass filtering method at high temperatures, then all the edges are detected by using an edge detection operator, and then a Hough transform is conducted to search the straight edges for the calculation of deformation.

Toll-like receptor 4 prompts human breast cancer cells invasiveness via lipopolysaccharide stimulation and is overexpressed in patients with lymph node metastasis.

Toll-like receptor (TLR)4-mediated signaling has been implicated in tumor cell invasion, survival, and metastasis in a variety of cancers. This study investigated the expression and biological role of TLR4 in human breast cancer metastasis. MCF-7 and MDA-MB-231 are human breast cancer cell lines with low and high metastatic potential, respectively.