Computer Methods in Biomechanics and Biomedical Engineering最新文献

Exploring coronavirus sequence motifs through convolutional neural network for accurate identification of COVID-19. 通过卷积神经网络探索冠状病毒序列图案，准确识别 COVID-19。

IF 1.7 4区医学

Computer Methods in Biomechanics and Biomedical Engineering Pub Date : 2024-11-07 DOI: 10.1080/10255842.2024.2404149

Praveen Gugulothu, Raju Bhukya

{"title":"Exploring coronavirus sequence motifs through convolutional neural network for accurate identification of COVID-19.","authors":"Praveen Gugulothu, Raju Bhukya","doi":"10.1080/10255842.2024.2404149","DOIUrl":"https://doi.org/10.1080/10255842.2024.2404149","url":null,"abstract":"The SARS-CoV-2 virus reportedly originated in Wuhan in 2019, causing the coronavirus outbreak (COVID-19), which was technically designated as a global epidemic. Numerous studies have been carried out to diagnose and treat COVID-19 throughout the midst of the disease's spread. However, the genetic similarity between COVID-19 and other types of coronaviruses makes it challenging to differentiate between them. Therefore it's essential to swiftly identify if an epidemic is brought on by a brand-new virus or a well-known disease. In the present article, the DeepCoV deep-learning (DL) approach utilizes layered convolutional neural networks (CNNs) to classify viral serious acute respiratory syndrome coronavirus 2 (SARS-CoV-2) besides other viral diseases. Additionally, various motifs linked with SARS-CoV-2 can be located by examining the computational filter processes. In identifying these important motifs, DeepCoV reveals the transparency of CNNs. Experiments were conducted using the 2019nCoVR datasets, and the results indicate that DeepCoV performed more accurately than several benchmark ML models. Additionally, DeepCoV scored its maximum area under the precision-recall curve (AUCPR) and receiver operating characteristic curve (AUC-ROC) at 98.62% and 98.58%, respectively. Overall, these investigations provide strong knowledge of the employment of deep learning (DL) algorithms as a crucial alternative to identifying SARS-CoV-2 and identifying patterns of disease in the SARS-CoV-2 genes.","PeriodicalId":50640,"journal":{"name":"Computer Methods in Biomechanics and Biomedical Engineering","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142592013","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Accurate detection of gait events using neural networks and IMU data mimicking real-world smartphone usage. 利用神经网络和模仿真实世界智能手机使用情况的 IMU 数据准确检测步态事件。

IF 1.7 4区医学

Computer Methods in Biomechanics and Biomedical Engineering Pub Date : 2024-11-07 DOI: 10.1080/10255842.2024.2423252

Aske G Larsen, Line Ø Sadolin, Trine R Thomsen, Anderson S Oliveira

{"title":"Accurate detection of gait events using neural networks and IMU data mimicking real-world smartphone usage.","authors":"Aske G Larsen, Line Ø Sadolin, Trine R Thomsen, Anderson S Oliveira","doi":"10.1080/10255842.2024.2423252","DOIUrl":"https://doi.org/10.1080/10255842.2024.2423252","url":null,"abstract":"Wearable technologies such as inertial measurement units (IMUs) can be used to evaluate human gait and improve mobility, but sensor fixation is still a limitation that needs to be addressed. Therefore, aim of this study was to create a machine learning algorithm to predict gait events using a single IMU mimicking the carrying of a smartphone. Fifty-two healthy adults (35 males/17 females) walked on a treadmill at various speeds while carrying a surrogate smartphone in the right hand, front right trouser pocket, and right jacket pocket. Ground-truth gait events (e.g. heel strikes and toe-offs) were determined bilaterally using a gold standard optical motion capture system. The tri-dimensional accelerometer and gyroscope data were segmented in 20-ms windows, which were labelled as containing or not the gait events. A long-short term memory neural network (LSTM-NN) was used to classify the 20-ms windows as containing the heel strike or toe-off for the right or left legs, using 80% of the data for training and 20% of the data for testing. The results demonstrated an overall accuracy of 92% across all phone positions and walking speeds, with a slightly higher accuracy for the right-side predictions (∼94%) when compared to the left side (∼91%). Moreover, we found a median time error <3% of the gait cycle duration across all speeds and positions (∼77 ms). Our results represent a promising first step towards using smartphones for remote gait analysis without requiring IMU fixation, but further research is needed to enhance generalizability and explore real-world deployment.","PeriodicalId":50640,"journal":{"name":"Computer Methods in Biomechanics and Biomedical Engineering","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142592011","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Coexistence of horizontal bone loss and dehiscence with the bundle and conventional fiber post: a finite element analysis. 束状纤维桩和传统纤维桩同时存在水平骨丢失和开裂：有限元分析。

IF 1.7 4区医学

Computer Methods in Biomechanics and Biomedical Engineering Pub Date : 2024-11-05 DOI: 10.1080/10255842.2024.2423266

Deniz Yanık, Nurullah Türker, Ahmet Mert Nalbantoğlu

{"title":"Coexistence of horizontal bone loss and dehiscence with the bundle and conventional fiber post: a finite element analysis.","authors":"Deniz Yanık, Nurullah Türker, Ahmet Mert Nalbantoğlu","doi":"10.1080/10255842.2024.2423266","DOIUrl":"https://doi.org/10.1080/10255842.2024.2423266","url":null,"abstract":"Horizontal bone loss (HBL) and dehiscence are common supportive tissue defects. This study evaluated the stress distribution in the presence of HBL or dehiscence and two types of fiber posts. Twelve premolars that were endodontically treated (Model-E), restored with conventional (Model-C), and bundle (Model-B) post were modeled. Bone defects were created as control (Model-1), with 4 mm (Model-4) and 8 mm (Model-8) HBL, and dehiscence involving two-thirds of the root (Model-D). HBL was included in all aspects of the models, while dehiscence was confined to the buccal aspect. The models were subjected to a 200 N force, and von Mises stress was analyzed. Model-B1 showed higher stress than Model-C1 but was more homogeneous. In Model-D, the stress was limited to the area without bone and only occurred at the buccal aspect. The highest stress was observed in Model-B8. The presence of a post caused a 2-5.8 times increase in stress. When the crown-root ratio was 1:0.8, stress was in the coronal two-thirds of the root, while at a ratio of 1:0.3, stress was distributed throughout the entire root. Bundle post with 8 mm HBL increased the stress 5.8 times. HBL resulted in stress extending beyond the marginal bone, while dehiscence did not.","PeriodicalId":50640,"journal":{"name":"Computer Methods in Biomechanics and Biomedical Engineering","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142584826","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Effects of a soft back exoskeleton on lower lumbar spine loads during manual materials handling: a musculoskeletal modelling study. 软背外骨骼对人工搬运物料过程中腰椎下部负荷的影响：肌肉骨骼模型研究。

IF 1.7 4区医学

Computer Methods in Biomechanics and Biomedical Engineering Pub Date : 2024-11-04 DOI: 10.1080/10255842.2024.2422925

Arthur Favennec, Florent Moissenet, Julien Frère, Guillaume Mornieux

引用次数: 0

The role of m5C RNA methylation regulators in the diagnosis and immune microenvironment of osteoarthritis. m5C RNA 甲基化调节因子在骨关节炎的诊断和免疫微环境中的作用。

IF 1.7 4区医学

Computer Methods in Biomechanics and Biomedical Engineering Pub Date : 2024-11-04 DOI: 10.1080/10255842.2024.2422911

Kehan Li, Shengjie Wang, Chenyue Xu, Zhengyi Ni, Xiurong Wang, Fei Wang

{"title":"The role of m5C RNA methylation regulators in the diagnosis and immune microenvironment of osteoarthritis.","authors":"Kehan Li, Shengjie Wang, Chenyue Xu, Zhengyi Ni, Xiurong Wang, Fei Wang","doi":"10.1080/10255842.2024.2422911","DOIUrl":"https://doi.org/10.1080/10255842.2024.2422911","url":null,"abstract":"The 5-methylcytosine (m5C) is a common post-transcriptional RNA methylation modification and is involved in the pathological process of many diseases. However, little is known about the role of m5C in osteoarthritis (OA). OA gene data and the corresponding information were downloaded from the Gene Expression Omnibus database. Based on 36 m5C regulators, we constructed the landscape and diagnostic model for OA. Later, two m5C modification patterns were identified, and functional analyses were performed to evaluate whether these patterns were related to endoplasmic reticulum (ER) stress and mitochondrial autophagy. We further comprehensively analyzed the immune cell infiltration characteristics in different modification patterns in OA. We also established the post-transcriptional regulatory networks and drug-gene networks. Our findings suggested that m5C regulators were differentially expressed between OA and normal samples and could serve as novel biomarkers for the diagnosis of OA. Besides, m5C regulators may be involved in regulating ER stress, mitochondrial autophagy, and immune infiltration in OA. The m5C modification can influence the sensitivity to drugs and the potential post-transcriptional regulatory mechanisms might provide promising targets.","PeriodicalId":50640,"journal":{"name":"Computer Methods in Biomechanics and Biomedical Engineering","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142570346","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Real-time EEG-based detection of driving fatigue using a novel semi-dry electrode with self-replenishment of conductive fluid. 基于脑电图的驾驶疲劳实时检测，采用新型半干电极，可自我补充导电液。

IF 1.7 4区医学

Computer Methods in Biomechanics and Biomedical Engineering Pub Date : 2024-11-04 DOI: 10.1080/10255842.2024.2423268

Fuwang Wang, Anni Luo, Daping Chen

引用次数: 0

Mechanical effect of taper position in abutment hole and screw taper angles on implant system and peri-implant tissue: a finite element analysis. 基台孔锥位和螺钉锥角对种植体系统和种植体周围组织的力学影响：有限元分析。

IF 1.7 4区医学

Computer Methods in Biomechanics and Biomedical Engineering Pub Date : 2024-11-04 DOI: 10.1080/10255842.2024.2423253

Hu Hou, Jianguo Zhang, Song Huang, Fengling Hu, Youcheng Yu, Liang Song

引用次数: 0

OmicPredict: a framework for omics data prediction using ANOVA-Firefly algorithm for feature selection. OmicPredict：使用ANOVA萤火虫算法进行特征选择的组学数据预测框架。

IF 1.7 4区医学

Computer Methods in Biomechanics and Biomedical Engineering Pub Date : 2024-11-01 Epub Date: 2023-10-16 DOI: 10.1080/10255842.2023.2268236

Parampreet Kaur, Ashima Singh, Inderveer Chana

{"title":"OmicPredict: a framework for omics data prediction using ANOVA-Firefly algorithm for feature selection.","authors":"Parampreet Kaur, Ashima Singh, Inderveer Chana","doi":"10.1080/10255842.2023.2268236","DOIUrl":"10.1080/10255842.2023.2268236","url":null,"abstract":"High-throughput technologies and machine learning (ML), when applied to a huge pool of medical data such as omics data, result in efficient analysis. Recent research aims to apply and develop ML models to predict a disease well in time using available omics datasets. The present work proposed a framework, 'OmicPredict', deploying a hybrid feature selection method and deep neural network (DNN) model to predict multiple diseases using omics data. The hybrid feature selection method is developed using the Analysis of Variance (ANOVA) technique and firefly algorithm. The OmicPredict framework is applied to three case studies, Alzheimer's disease, Breast cancer, and Coronavirus disease 2019 (COVID-19). In the case study of Alzheimer's disease, the framework predicts patients using GSE33000 and GSE44770 dataset. In the case study of Breast cancer, the framework predicts human epidermal growth factor receptor 2 (HER2) subtype status using Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) dataset. In the case study of COVID-19, the framework performs patients' classification using GSE157103 dataset. The experimental results show that DNN model achieved an Area Under Curve (AUC) score of 0.949 for the Alzheimer's (GSE33000 and GSE44770) dataset. Furthermore, it achieved an AUC score of 0.987 and 0.989 for breast cancer (METABRIC) and COVID-19 (GSE157103) datasets, respectively, outperforming Random Forest, Naïve Bayes models, and the existing research.","PeriodicalId":50640,"journal":{"name":"Computer Methods in Biomechanics and Biomedical Engineering","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41240601","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Analysis of material parameter uncertainty propagation in preoperative flap suture simulation. 术前皮瓣缝合模拟中材料参数不确定性传播的分析。

IF 1.7 4区医学

Computer Methods in Biomechanics and Biomedical Engineering Pub Date : 2024-11-01 Epub Date: 2023-10-22 DOI: 10.1080/10255842.2023.2272009

Xiaogang Ji, Huabin Li, Hao Gong, Guangquan Wen, Rong Sun

{"title":"Analysis of material parameter uncertainty propagation in preoperative flap suture simulation.","authors":"Xiaogang Ji, Huabin Li, Hao Gong, Guangquan Wen, Rong Sun","doi":"10.1080/10255842.2023.2272009","DOIUrl":"10.1080/10255842.2023.2272009","url":null,"abstract":"Skin flap transplantation is the most commonly used method to repair tissue defect and cover the wound. In clinic, finite element method is often used to design the pre-operation scheme of flap suture. However, the material parameters of skin flap are uncertain due to experimental errors and differences in body parts. How to consider the influence of material parameter uncertainty on the mechanical response of flap suture in the finite element modeling is an urgent problem to be solved at present. Therefore, the influence of material parameter uncertainty propagation in skin flap suture simulation was studied, Firstly, the geometric model of clinical patient's hand wound was constructed by using reverse modeling technology, the patient's three-dimensional wound was unfolded into a flat surface by using curved surface expansion method, yielding a preliminary design contour for the patient's transplant flap. Based on the acquired patient wound geometry model, the finite element model of flap suture with different fiber orientations and different sizes was constructed in Abaqus, and the uncertainty propagation analysis method based on Monte Carlo simulation combined with surrogate model technology was further used to analyze the stress response of flap suture considering the uncertainty of material parameters. Results showed that the overall stress value was relatively lower when the average fiber orientation was 45°. which could be used as the optimal direction for the flap excision. when the preliminary design contour of the flap was scaled down within 90%, the stress value after flap suturing remained within a safe range.","PeriodicalId":50640,"journal":{"name":"Computer Methods in Biomechanics and Biomedical Engineering","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49693567","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Multiscale simulation of the effect of low-intensity pulsed ultrasound on the mechanical properties distribution of osteocytes. 低强度脉冲超声对骨细胞力学性能分布影响的多尺度模拟。

IF 1.7 4区医学

Computer Methods in Biomechanics and Biomedical Engineering Pub Date : 2024-11-01 Epub Date: 2023-10-16 DOI: 10.1080/10255842.2023.2270103

Shenggang Li, Haiying Liu, Mingzhi Li, Chunqiu Zhang

引用次数: 0