Computer Methods in Biomechanics and Biomedical Engineering This is an RSS file. You can use it to subscribe to this data in your favourite RSS reader or to display this data on your own website or blog.

The organization committee: ABSTRACTS 47th congress of the society of biomechanics
Comput Methods Biomech Biomed Engin. 2023 Jun 28:1-2. doi: 10.1080/10255842.2023.2169494. Online ahead of print.NO ABSTRACTPMID:38410941 | DOI:10.1080/10255842.2023.2169494 (Source: Computer Methods in Biomechanics and Biomedical Engineering)
Source: Computer Methods in Biomechanics and Biomedical Engineering - February 27, 2024 Category: Biomedical Engineering Authors: Imane Ait Oumghara Source Type: research

Optimized FFNN with multichannel CSP-ICA framework of EEG signal for BCI
Comput Methods Biomech Biomed Engin. 2024 Feb 26:1-18. doi: 10.1080/10255842.2024.2319701. Online ahead of print.ABSTRACTThe electroencephalogram (EEG) of the patient is used to identify their motor intention, which is then converted into a control signal through a brain-computer interface (BCI) based on motor imagery. Whenever gathering features from EEG signals, making a BCI is difficult in part because of the enormous dimensionality of the data. Three stages make up the suggested methodology: pre-processing, extraction of features, selection, and categorization. To remove unwanted artifacts, the EEG signals are filtered...
Source: Computer Methods in Biomechanics and Biomedical Engineering - February 26, 2024 Category: Biomedical Engineering Authors: E Ramkumar M Paulraj Source Type: research

Advancing COVID-19 stochastic modeling: a comprehensive examination integrating vaccination classes through higher-order spectral scheme analysis
In this study, we introduce a novel approach that integrates various vaccination classes into a stochastic model to provide a more nuanced understanding of disease transmission dynamics. We employ a higher-order spectral scheme to capture complex interactions between different population groups, vaccination statuses, and disease parameters. Our analysis not only enhances the predictive accuracy of COVID-19 modeling but also facilitates the exploration of various vaccination strategies and their impact on disease control. The findings of this study hold significant implications for optimizing vaccination campaigns and guidi...
Source: Computer Methods in Biomechanics and Biomedical Engineering - February 24, 2024 Category: Biomedical Engineering Authors: Laiquan Wang Sami Ullah Khan Farman U Khan Salman A AlQahtani Atif M Alamri Source Type: research

Scalable musculoskeletal model for dynamic simulations of lower body movement
Comput Methods Biomech Biomed Engin. 2024 Feb 23:1-27. doi: 10.1080/10255842.2024.2316240. Online ahead of print.ABSTRACTA musculoskeletal (MSK) model is an important tool for analysing human motions, calculating joint torques during movement, enhancing sports activity, and developing exoskeletons and prostheses. To enable biomechanical investigation of human motion, this work presents an open-source lower body MSK model. The MSK model of the lower body consists of 7 body segments (pelvis, left/right thigh, left/right leg, and left/right foot). The model has 20 degrees of freedom (DoFs) and 28 muscle torque generators (MTG...
Source: Computer Methods in Biomechanics and Biomedical Engineering - February 24, 2024 Category: Biomedical Engineering Authors: Ali Nasr John McPhee Source Type: research

A stroke prediction framework using explainable ensemble learning
Comput Methods Biomech Biomed Engin. 2024 Feb 21:1-20. doi: 10.1080/10255842.2024.2316877. Online ahead of print.ABSTRACTThe death of brain cells occurs when blood flow to a particular area of the brain is abruptly cut off, resulting in a stroke. Early recognition of stroke symptoms is essential to prevent strokes and promote a healthy lifestyle. FAST tests (looking for abnormalities in the face, arms, and speech) have limitations in reliability and accuracy for diagnosing strokes. This research employs machine learning (ML) techniques to develop and assess multiple ML models to establish a robust stroke risk prediction fr...
Source: Computer Methods in Biomechanics and Biomedical Engineering - February 22, 2024 Category: Biomedical Engineering Authors: Mostarina Mitu S M Mahedy Hasan Md Palash Uddin Md Al Mamun Venkatesan Rajinikanth Seifedine Kadry Source Type: research

Enhancing drug discovery in schizophrenia: a deep learning approach for accurate drug-target interaction prediction - DrugSchizoNet
Comput Methods Biomech Biomed Engin. 2024 Feb 20:1-18. doi: 10.1080/10255842.2023.2282951. Online ahead of print.ABSTRACTDrug discovery relies on the precise prognosis of drug-target interactions (DTI). Due to their ability to learn from raw data, deep learning (DL) methods have displayed outstanding performance over traditional approaches. However, challenges such as imbalanced data, noise, poor generalization, high cost, and time-consuming processes hinder progress in this field. To overcome the above challenges, we propose a DL-based model termed DrugSchizoNet for drug interaction (DI) prediction of Schizophrenia. Our m...
Source: Computer Methods in Biomechanics and Biomedical Engineering - February 20, 2024 Category: Biomedical Engineering Authors: Sherine Glory J Durgadevi P Ezhumalai P Source Type: research

A multi-branch convolutional neural network for snoring detection based on audio
This study utilized Mel-frequency cepstral coefficients (MFCCs) as a method for extracting features during the preprocessing of raw data. In order to extract multi-scale features from the frequency domain of sound sources, this study proposes the utilization of a multi-branch convolutional neural network (MBCNN) for the purpose of classification. The network utilized asymmetric convolutional kernels to acquire additional information, while the adoption of one-hot encoding labels aimed to mitigate the impact of labels. The experiment tested the network's performance by utilizing a publicly available dataset consisting of 1,...
Source: Computer Methods in Biomechanics and Biomedical Engineering - February 19, 2024 Category: Biomedical Engineering Authors: Hao Dong Haitao Wu Guan Yang Junming Zhang Keqin Wan Source Type: research

Computer model of non-Newtonian canalicular fluid flow in lacunar-canalicular system of bone tissue
Comput Methods Biomech Biomed Engin. 2024 Feb 19:1-15. doi: 10.1080/10255842.2024.2317442. Online ahead of print.ABSTRACTBrittle bone diseases are a global healthcare problem for orthopaedic clinicians, that reduces bone strength and promotes bone fracture risk. In vivo studies reported that loading-induced fluid flow through the lacunar-canalicular channel (LCS) of bone tissue inhibit such bone loss and encourages osteogenesis i.e. new bone formation. Canalicular fluid flow converts mechanical signals into biological signals and regulates bone reconstruction by releasing signalling molecules responsible for mechanotransdu...
Source: Computer Methods in Biomechanics and Biomedical Engineering - February 19, 2024 Category: Biomedical Engineering Authors: Rakesh Kumar Source Type: research

Effects of various cross-linked collagen scaffolds on wound healing in rats model by deep-learning CNN
This study investigates the efficacy of four types of collagen scaffolds in promoting wound healing and regeneration in a Sprague-Dawley murine model-the histomorphology analysis of collagen scaffolds and developing a deep learning model for accurate tissue classification. Four female rats (n = 24) groups received collagen scaffolds prepared through physical and chemical crosslinking. Wound healing progress was evaluated by monitoring granulation tissue formation, collagen matrix organization, and collagen fiber deposition, with histological scoring for quantification-the EDC and HA groups demonstrated enhanced tissue rege...
Source: Computer Methods in Biomechanics and Biomedical Engineering - February 15, 2024 Category: Biomedical Engineering Authors: Chih-Tsung Chang Chun-Hui Huang Source Type: research