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.

A transcutaneous acupoint electrical simulation glove for relieving the mental fatigue of crane drivers in real building environment
In this study, non-periodic transcutaneous acupoint electrical stimulation (NPTAES) was used to stimulate human acupuncture points. This is different from the traditional periodic transcutaneous acupoint electrical stimulation (PTAES) method for relieving mental fatigue. In addition, this study used hilbert marginal spectral entropy (HMSE) to calculate the heart rate variability (HRV) characteristics of the subjects, so as to detect and analyze the driving fatigue of the drivers. At the same time, the drivers' blinking frequency and electroencephalogram (EEG) characteristics were analyzed comprehensively. The results show ...
Source: Computer Methods in Biomechanics and Biomedical Engineering - January 5, 2024 Category: Biomedical Engineering Authors: Fuwang Wang Daping Chen Xiaolei Zhang Source Type: research

Mechanical property of Ti6Al4V cylindrical porous structure for dental implants fabricated by selective laser melting
Comput Methods Biomech Biomed Engin. 2024 Jan 4:1-19. doi: 10.1080/10255842.2023.2300686. Online ahead of print.ABSTRACTThe commonly used titanium alloy dental implants currently apply solid structures. However, issues such as stress shielding and stress concentration may arise due to the significant difference in elastic modulus between the implant and host. In order to address these problems, this paper proposes five porous structures based on the Gibson-Ashby theoretical model. We utilized selective laser melting technology to shape a porous structure using Ti-6Al-4V material precisely. The mechanical properties of the ...
Source: Computer Methods in Biomechanics and Biomedical Engineering - January 5, 2024 Category: Biomedical Engineering Authors: Yun Zhai Hao Zhang Tong Liu Cong Zou Changchun Zhou Source Type: research

Revolutionizing Breast Cancer Care: AI-Enhanced Diagnosis and Patient History
This study presents a holistic approach that harnesses the power of artificial intelligence (AI) and machine learning (ML) to address these pressing needs. This study presents a comprehensive methodology for breast cancer diagnosis and medical history generation, integrating data collection, feature extraction, machine learning, and AI-driven history-taking. The research employs a systematic approach to ensure accurate diagnosis and efficient history collection. Data preprocessing merges similar attributes to streamline analysis. Three key algorithms, Support Vector Machine (SVM), K-Nearest Neighbours (KNN), and Fuzzy Logi...
Source: Computer Methods in Biomechanics and Biomedical Engineering - January 5, 2024 Category: Biomedical Engineering Authors: Maleeha Fathima Mohammed Moulana Source Type: research

Stochastic intelligent computing solvers for the SIR dynamical prototype epidemic model using the impacts of the hospital bed
Comput Methods Biomech Biomed Engin. 2024 Jan 2:1-13. doi: 10.1080/10255842.2023.2300684. Online ahead of print.ABSTRACTThe present investigations are related to design a stochastic intelligent solver using the infrastructure of artificial neural networks (ANNs) and scaled conjugate gradient (SCG), i.e. ANNs-SCG for the numerical simulations of SIR dynamical prototype system based impacts of hospital bed. The SIR dynamical model is defined into three classes, susceptible patients in the hospital, infected population and recovered people. The proposed results are obtained through the sample statics of verification, testing ...
Source: Computer Methods in Biomechanics and Biomedical Engineering - January 3, 2024 Category: Biomedical Engineering Authors: Manoj Gupta Achyuth Sarkar Source Type: research

Cognizance detection during mental arithmetic task using statistical approach
Comput Methods Biomech Biomed Engin. 2024 Jan 2:1-14. doi: 10.1080/10255842.2023.2298362. Online ahead of print.ABSTRACTThe handheld diagnosis and analysis are highly dependent on the physiological data in the clinical sector. Detection of the defect in the neuronal-assisted activity raises the challenge to the prevailing treatment that benefits from machine learning approaches. The congregated EEG data is then utilized in design of learning applications to develop a model that classifies intricate EEG patterns into active and inactive segments. During arithmetic problem-solving EEG signal acquired from frontal lobe contri...
Source: Computer Methods in Biomechanics and Biomedical Engineering - January 2, 2024 Category: Biomedical Engineering Authors: Hemalatha Karnan D Uma Maheswari D Priyadharshini S Laushya T K Thivyaprakas Source Type: research

Nonlinear optimal control for the multi-variable tumor-growth dynamics
Comput Methods Biomech Biomed Engin. 2024 Jan 2:1-29. doi: 10.1080/10255842.2023.2297660. Online ahead of print.ABSTRACTThe multivariable tumor-growth dynamic model has been widely used to describe the inhibition of tumor-cells proliferation under the simultaneous infusion of multiple chemotherapeutic drugs. In this article, a nonlinear optimal (H-infinity) control method is developed for the multi-variable tumor-growth model. First, differential flatness properties are proven for the associated state-space description. Next, the state-space description undergoes approximate linearization with the use of first-order Taylor...
Source: Computer Methods in Biomechanics and Biomedical Engineering - January 2, 2024 Category: Biomedical Engineering Authors: G Rigatos Source Type: research

EEG-BCI-based motor imagery classification using double attention convolutional network
This article aims to improve and diversify signal processing techniques to execute a brain-computer interface (BCI) based on neurological phenomena observed when performing motor tasks using motor imagery (MI). The noise present in the original data, such as intermodulation noise, crosstalk, and other unwanted noise, is removed by Modify Least Mean Square (M-LMS) in the pre-processing stage. Traditional LMSs were unable to extract all the noise from the images. After pre-processing, the required features, such as statistical features, entropy features, etc., were extracted using Common Spatial Pattern (CSP) and Pearson's C...
Source: Computer Methods in Biomechanics and Biomedical Engineering - January 2, 2024 Category: Biomedical Engineering Authors: V Sireesha V V Satyanarayana Tallapragada M Naresh G V Pradeep Kumar Source Type: research