Multi-joint protective effects of lumbar brace on lumbar, hip, knee, and ankle in parachute landing with backpack load
This study aimed to evaluate multi-joints protective effects of the lumbar brace on lumbar and lower limb joints in parachuting landing with the backpack load. Seven participants landed from a 120 cm height platform without and with a lumbar brace and without and with a 5-kg backpack load, respectively. Infrared makers were pasted on trunk, pelvis, and lower limb in order to build a multi-rigid-body model for calculating kinematic and kinetic parameters. The joint angular displacements of lumbar and ankle and the peak vertical ground reaction force were significantly decreased from 29.2  ± 9.2°, 45.2 ± 7.8°, an...
Source: Medical and Biological Engineering and Computing - September 2, 2023 Category: Biomedical Engineering Source Type: research

CR-Conformer: a fusion network for clinical skin lesion classification
AbstractDeep convolutional neural network (DCNN) models have been widely used to diagnose skin lesions, and some of them have achieved diagnostic results comparable to or even better than dermatologists. Most publicly available skin lesion datasets used to train DCNN were dermoscopic images. Expensive dermoscopic equipment is rarely available in rural clinics or small hospitals in remote areas. Therefore, it is of great significance to rely on clinical images for computer-aided diagnosis of skin lesions. This paper proposes an improved dual-branch fusion network called CR-Conformer. It integrates a DCNN branch that can eff...
Source: Medical and Biological Engineering and Computing - September 1, 2023 Category: Biomedical Engineering Source Type: research

Numerical study on the performance of mixed flow blood pump with superhydrophobic surface
AbstractTo meet the clinical status of the wide application of percutaneous mechanical circulatory support, this paper selects the mixed flow blood pump applied with superhydrophobic surface as the research object. The Navier slip model was used to simulate the slip characteristics of superhydrophobic surface, and the effects of the blade wrap angle and the superhydrophobic surface on the performance of the mixed flow blood pump are studied by numerical simulation. The results show that (1) considering the head, hydraulic efficiency, and hemolysis index of the blood pump, the optimal value of the blade wrap angle of the mi...
Source: Medical and Biological Engineering and Computing - September 1, 2023 Category: Biomedical Engineering Source Type: research

Classification of benign and malignant parotid tumors based on CT images combined with stack generalization model
AbstractParotid tumors are among the most prevalent tumors in otolaryngology, and malignant parotid tumors are one of the main causes of facial paralysis in patients. Currently, the main diagnostic modality for parotid tumors is computed tomography, which relies mainly on the subjective judgment of clinicians and leads to practical problems such as high workloads. Therefore, to assist physicians in solving the preoperative classification problem, a stacked generalization model is proposed for the automated classification of parotid tumor images. A ResNet50 pretrained model is used for feature extraction. The first layer of...
Source: Medical and Biological Engineering and Computing - September 1, 2023 Category: Biomedical Engineering Source Type: research

Knowledge distillation for efficient standard scanplane detection of fetal ultrasound
We report a thorough analysis of fetal ultrasound data, focusing on a benchmark dataset, to the best of our knowledge the only one available to date.Graphical abstract (Source: Medical and Biological Engineering and Computing)
Source: Medical and Biological Engineering and Computing - September 1, 2023 Category: Biomedical Engineering Source Type: research

Contrastive self-supervised learning for diabetic retinopathy early detection
AbstractDiabetic Retinopathy (DR) is the major cause of blindness, which seriously threatens the world ’s vision health. Limited medical resources make early diagnosis and a large-scale screening of DR difficult. Most of the current automatic diagnostic methods are mostly based on deep learning and large-scale labeled data. However, the insufficiency of manual annotations for medical images still i s a great challenge of training deep neural networks. Self-supervised learning methods are proposed to learn general features from dataset without manual annotations. Inspired by this, we proposed a deep learning based DR clas...
Source: Medical and Biological Engineering and Computing - August 10, 2023 Category: Biomedical Engineering Source Type: research

Design of ear-contactless stethoscope and improvement in the performance of deep learning based on CNN to classify the heart sound
AbstractCardiac-related disorders are rapidly growing throughout the world. Accurate classification of cardiovascular diseases is an important research topic in healthcare. During COVID-19, auscultating heart sounds was challenging as health workers and doctors wear protective clothing, and direct contact with patients can spread the outbreak. Thus, contactless auscultation of heart sound is necessary. In this paper, a low-cost ear contactless stethoscope is designed where auscultation is done with the help of a bluetooth-enabled micro speaker instead of an earpiece. The PCG recordings are further compared with other stand...
Source: Medical and Biological Engineering and Computing - August 10, 2023 Category: Biomedical Engineering Source Type: research

Deep convolutional neural network for hippocampus segmentation with boundary region refinement
In conclusion, our study proposes a novel method for hippocampus segmentation, which improves upon the current state-of-the-art methods. By incorporating a boundary refinement step, our approach achieves higher accuracy in hippocampus segmentation and may facilitate research on brain disorders.Graphical Abstract (Source: Medical and Biological Engineering and Computing)
Source: Medical and Biological Engineering and Computing - August 10, 2023 Category: Biomedical Engineering Source Type: research

3D vessel extraction using a scale-adaptive hybrid parametric tracker
Abstract3D vessel extraction has great significance in the diagnosis of vascular diseases. However, accurate extraction of vessels from computed tomography angiography (CTA) data is challenging. For one thing, vessels in different body parts have a wide range of scales and large curvatures; for another, the intensity distributions of vessels in different CTA data vary considerably. Besides, surrounding interfering tissue, like bones or veins with similar intensity, also seriously affects vessel extraction. Considering all the above imaging and structural features of vessels, we propose a new scale-adaptive hybrid parametri...
Source: Medical and Biological Engineering and Computing - August 10, 2023 Category: Biomedical Engineering Source Type: research

Effect of 3D paradigm synchronous motion for SSVEP-based hybrid BCI-VR system
AbstractA brain-computer interface (BCI) system and virtual reality (VR) are integrated as a more interactive hybrid system (BCI-VR) that allows the user to manipulate the car. A virtual scene in the VR system that is the same as the physical environment is built, and the object ’s movement can be observed in the VR scene. The four-class three-dimensional (3D) paradigm is designed and moves synchronously in virtual reality. The dynamic paradigm may affect their attention according to the experimenters’ feedback. Fifteen subjects in our experiment steered the car accordi ng to a specified motion trajectory. According to...
Source: Medical and Biological Engineering and Computing - August 10, 2023 Category: Biomedical Engineering Source Type: research

Portable deep-learning decoder for motor imaginary EEG signals based on a novel compact convolutional neural network incorporating spatial-attention mechanism
In this study, we proposed a high-accuracy MI EEG decoder by incorporating spatial-attention mechanism into convolution neural network (CNN), and deployed it on fully integrated single-chip microcontroller unit (MCU). After the CNN model was trained on workstation computer using GigaDB MI datasets (52 subjects), its parameters were then extracted and converted to build deep-learning architecture interpreter on MCU. For comparison, EEG-Inception model was also trained using the same dataset, and was deployed on MCU. The results indicate that our deep-learning model can independently decode imaginary left-/right-hand motions...
Source: Medical and Biological Engineering and Computing - August 10, 2023 Category: Biomedical Engineering Source Type: research

Finite element analysis of the influence of interdigitation pattern and collagen fibers on the mechanical behavior of the midpalatal suture
The objective of this research was to observe the influence of interdigitation and collagen fibers on the mechanical response of MPS. To this end, a finite element analysis in two-dimensional models of the bone-suture-bone interface was performed considering the characteristics of the MPS. The geometry of the suture was modeled with 4 different levels of interdigitation: null, moderate, scalloped and fractal. The influence of collagen fibers, aligned transversely along the suture, was considered by incorporating linked structures of the bone fronts. According to the results, the factor that has the greatest impact on the m...
Source: Medical and Biological Engineering and Computing - August 10, 2023 Category: Biomedical Engineering Source Type: research

A robust walking detection algorithm using a single foot-worn inertial sensor: validation in real-life settings
In this study, we aim to validate a robust walking detection algorithm using a single foot-worn inertial measurement unit (IMU) in real-life settings. We used a challenging dataset including 18 individuals performing free-living activities. A multi-sensor wearable system including pressure insoles, multiple IMUs, and infrared distance sensors (INDIP) was used as reference. Accurate walking detection was obtained, with sensitivity and specificity of 98 and 91% respectively. As robust walking detection is needed for ambulatory monitoring to complete the processing pipeline from raw recorded data to walking/mobility outcomes,...
Source: Medical and Biological Engineering and Computing - August 10, 2023 Category: Biomedical Engineering Source Type: research

Segmentation of rectal tumor from multi-parametric MRI images using an attention-based fusion network
This study presents an attention-based multi-modal fusion module to effectively integrate complementary information from different MRI images and suppress redundancy. In addition, a deep learning –based segmentation model (AF-UNet) is designed to achieve accurate segmentation of rectal tumors. This model takes multi-parametric MRI images as input and effectively integrates the features from different multi-parametric MRI images by embedding the attention fusion module. Finally, three types of MRI images (T2, ADC, DWI) of 250 patients with rectal cancer were collected, with the tumor regions delineated by two oncologists....
Source: Medical and Biological Engineering and Computing - August 10, 2023 Category: Biomedical Engineering Source Type: research

CervicoXNet: an automated cervicogram interpretation network
This study proposed an automated cervicogram interpretation using explainable convolutional neural networks named “CervicoXNet” to support medical workers decision. The total number of 779 cervicograms was used for the learning process: 487 w ith VIA ( +) and 292 with VIA ( −). We performed data augmentation process under a geometric transformation scenario, such process produces 7325 cervicogram with VIA ( −) and 7242 cervicogram with VIA ( +). The proposed model outperformed other deep learning models, with 99.22% accuracy, 100% sensitivity, and 98.28% specificity. Moreover, to test the robustness of the ...
Source: Medical and Biological Engineering and Computing - August 10, 2023 Category: Biomedical Engineering Source Type: research