Prediction of gestational diabetes using deep learning and Bayesian optimization and traditional machine learning techniques
AbstractThe study aimed to develop a clinical diagnosis system to identify patients in the GD risk group and reduce unnecessary oral glucose tolerance test (OGTT) applications for pregnant women who are not in the GD risk group using deep learning algorithms. With this aim, a prospective study was designed and the data was taken from 489 patients between the years 2019 and 2021, and informed consent was obtained. The clinical decision support system for the diagnosis of GD was developed using the generated dataset with deep learning algorithms and Bayesian optimization. As a result, a novel successful decision support mode...
Source: Medical and Biological Engineering and Computing - June 19, 2023 Category: Biomedical Engineering Source Type: research

AI-assisted identification of intrapapillary capillary loops in magnification endoscopy for diagnosing early-stage esophageal squamous cell carcinoma: a preliminary study
AbstractEsophageal squamous cell carcinoma (ESCC) is one of the most common histological types of esophageal cancers. It can seriously affect public health, particularly in Eastern Asia. Early diagnosis and effective therapy of ESCC can significantly help improve patient prognoses. The visualization of intrapapillary capillary loops (IPCLs) under magnification endoscopy (ME) can greatly support the identification of ESCC occurrences by endoscopists. This paper proposes an artificial-intelligence-assisted endoscopic diagnosis approach using deep learning for localizing and identifying IPCLs to diagnose early-stage ESCC. An ...
Source: Medical and Biological Engineering and Computing - June 19, 2023 Category: Biomedical Engineering Source Type: research

Automatic vertebral fracture and three-column injury diagnosis with fracture visualization by a multi-scale attention-guided network
This study proposed a novel network, a multi-scale attention-guided network (MAGNet), to diagnose vertebral fractures and three-column injuries with fracture visualization at a vertebra level. By imposing attention constraints through a disease attention map (DAM), a fusion of multi-scale spatial attention maps, the MAGNet can get task highly relevant features and localize fractures. A total of 989 vertebrae were studied here. After four-fold cross-validation, the area under the ROC curve (AUC) of our model for vertebral fracture dichotomized diagnosis and three-column injury diagnosis was 0.884  ± 0.015 and 0.920 Â...
Source: Medical and Biological Engineering and Computing - June 19, 2023 Category: Biomedical Engineering Source Type: research

Continuous estimation of multi-DOF movement from sEMG based on non-negative matrix factorization and L2 regulation
AbstractAccurate continuous estimation of multi-DOF movement is crucial for simultaneous control of advanced myoelectric prosthetic. The decoupling of multi-DOF is a challenge for continuous estimation. In this paper, we propose a model combined non-negative matrix factorization (NMF) with Hadamard product and L2 regulation to suppress the non-active DOF and achieve the multi-DOF movement continuous estimation. The L2 regulation of non-active DOF activation coefficient was added to the object function of NMF with the benefit of Hadamard product. The angles were estimated by a linear combination of the activation coefficien...
Source: Medical and Biological Engineering and Computing - June 19, 2023 Category: Biomedical Engineering Source Type: research

A fast sample entropy for pulse rate variability analysis
AbstractSample entropy is an effective nonlinear index for analyzing pulse rate variability (PRV) signal, but it has problems with a large amount of calculation and time consumption. Therefore, this study proposes a fast sample entropy calculation method to analyze the PRV signal according to the microprocessor process of data updating and the principle of sample entropy. The simulated data and PRV signal are employed as experimental data to verify the accuracy and time consumption of the proposed method. The experimental results on simulated data display that the proposed improved sample entropy can improve the operation ...
Source: Medical and Biological Engineering and Computing - June 19, 2023 Category: Biomedical Engineering Source Type: research

Collision avoidance analysis of human –robot physical interaction based on null-space impedance control of a dynamic reference arm plane
AbstractWhen the terminal upper limb rehabilitation robot is used for motion-assisted training, collisions between the manipulator links and the human upper limb may occur due to the null-space self-motion of the redundant manipulator. A null-space impedance control method based on a dynamic reference arm plane is proposed to realize collision avoidance during human –robot physical interaction motion for the collision problem between the manipulator links and the human upper limb. Firstly, a dynamic model and a Cartesian impedance controller of the manipulator are established. Then, the null-space impedance controller of...
Source: Medical and Biological Engineering and Computing - June 16, 2023 Category: Biomedical Engineering Source Type: research

Effect of ureteral stent length and implantation position on migration after implantation
ConclusionThe biomechanism of stent migration and ureteral peristalsis weakening after stent implantation was explored. Shorter stents were more likely to migrate. The implantation position had less influence on ureteral peristalsis compared with the stent length, which provided a reference for stent design aimed at reducing stent migration. Stent length was the main factor affecting ureteral peristalsis. This study provides a reference for the study of ureteral peristalsis.Graphical Abstract (Source: Medical and Biological Engineering and Computing)
Source: Medical and Biological Engineering and Computing - June 15, 2023 Category: Biomedical Engineering Source Type: research

Forecasting and what-if analysis of new positive COVID-19 cases during the first three waves in Italy
AbstractThe joint exploitation of data related to epidemiological, mobility, and restriction aspects of COVID-19 with machine learning algorithms can support the development of predictive models that can be used to forecast new positive cases and study the impact of more or less severe restrictions. In this work, we integrate heterogeneous data from several sources and solve a multivariate time series forecasting task, specifically targeting the Italian case at both national and regional levels, during the first three waves of the pandemic. The goal is to build a robust predictive model to predict the number of new cases o...
Source: Medical and Biological Engineering and Computing - June 14, 2023 Category: Biomedical Engineering Source Type: research

Recognize enhanced temporal-spatial-spectral features with a parallel multi-branch CNN and GRU
AbstractDeep learning has been applied to the recognition of motor imagery electroencephalograms (MI-EEG) in brain-computer interface, and the performance results depend on data representation as well as neural network structure. Especially, MI-EEG is so complex with the characteristics of non-stationarity, specific rhythms, and uneven distribution; however, its multidimensional feature information is difficult to be fused and enhanced simultaneously in the existing recognition methods. In this paper, a novel channel importance (NCI) based on time –frequency analysis is proposed to develop an image sequence generation me...
Source: Medical and Biological Engineering and Computing - June 9, 2023 Category: Biomedical Engineering Source Type: research

Transfer learning –driven ensemble model for detection of diabetic retinopathy disease
In this study, we propose an ensemble model for the detection of diabetic retinopathy (DR) illness that is driven by transfer learning. Due to diabetes, the DR is a problem that affects the eyes. The retinal blood vessels in a person with high blood sugar deteriorate. The blood arteries may enlarge and leak as a result, or they may close and stop the flow of blood. If DR is not treated, it can become severe, damage vision, and eventually result in blindness. Medical experts study the colored fundus photos for this reason in order to manually diagnose disease, however this is a perilous technique. As a result, the condition...
Source: Medical and Biological Engineering and Computing - June 9, 2023 Category: Biomedical Engineering Source Type: research

Volatile organic compound sensing in breath using conducting polymer coated chemi-resistive filter paper sensors
AbstractIn this work, a disposable sensor array was designed based on the chemi-resistive behavior of the conducting polymers to detect three volatile organic compounds (VOCs), i.e., acetone, ethanol, and methanol in air and breath. Four disposable resistive sensors were designed by coating polypyrrole and polyaniline (in their doped and de-doped forms) on filter paper substrates and tested against VOCs in air. Change in conductivity of the polymer resulting from exposure to various VOC concentration was measured as percentage resistance change using a standard multimeter. The lowest concentration detected for acetone, eth...
Source: Medical and Biological Engineering and Computing - June 7, 2023 Category: Biomedical Engineering Source Type: research

Transformer-based temporal sequence learners for arrhythmia classification
AbstractAn electrocardiogram (ECG) plays a crucial role in identifying and classifying cardiac arrhythmia. Traditional methods employ handcrafted features, and more recently, deep learning methods use convolution and recursive structures to classify heart signals. Considering the time sequence nature of the ECG signal, a transformer-based model with its high parallelism is proposed to classify ECG arrhythmia. The DistilBERT transformer model, pre-trained for natural language processing tasks, is used in the proposed work. The signals are denoised and then segmented around the R peak and oversampled to get a balanced datase...
Source: Medical and Biological Engineering and Computing - June 6, 2023 Category: Biomedical Engineering Source Type: research

A membership-function –based broad learning system for human–robot interaction force estimation under drawing task
AbstractEstimating interaction force is of great significance in the field of human-robot interaction (HRI) thanks to its guarantee of interaction safety. To this end, this paper proposes a novel estimation method by leveraging broad learning system (BLS) and human surface electromyography (sEMG) signals. Since the previous sEMG may also contain valuable information of human muscle force, it would cause the estimation to be incomplete and abate the estimation accuracy in the case of neglecting the previous sEMG. To remedy this thorn, a new linear membership function is first developed to calculate contributions of sEMG at ...
Source: Medical and Biological Engineering and Computing - June 3, 2023 Category: Biomedical Engineering Source Type: research

Design and evaluation of vascular interventional robot system for complex coronary artery lesions
AbstractAt present, most vascular intervention robots cannot cope with the more common coronary complex lesions in the clinic. Moreover, the lack of effective force feedback increases the risk of surgery. In this paper, a vascular interventional robot that can collaboratively deliver multiple interventional instruments has been developed to assist doctors in the operation of complex lesions. Based on the doctor ’s skills and the delivery principle of interventional instruments, the main and slave manipulators of the robot system are designed. Haptic force feedback is generated through resistance measuring mechanism and a...
Source: Medical and Biological Engineering and Computing - May 13, 2023 Category: Biomedical Engineering Source Type: research

A survey of machine learning-based methods for COVID-19 medical image analysis
AbstractThe ongoing COVID-19 pandemic caused by the SARS-CoV-2 virus has already resulted in 6.6 million deaths with more than 637 million people infected after only 30 months since the first occurrences of the disease in December 2019. Hence, rapid and accurate detection and diagnosis of the disease is the first priority all over the world. Researchers have been working on various methods for COVID-19 detection and as the disease infects lungs, lung image analysis has become a popular research area for detecting the presence of the disease. Medical images from chest X-rays (CXR), computed tomography (CT) images, and lung ...
Source: Medical and Biological Engineering and Computing - May 13, 2023 Category: Biomedical Engineering Source Type: research