A numerical investigation of e-scooter-to-vehicle traffic accidents
Comput Methods Biomech Biomed Engin. 2024 May 2:1-5. doi: 10.1080/10255842.2024.2347477. Online ahead of print.ABSTRACTWithin the past decade, injuries caused by electric scooter (e-scooter) crashes have significantly increased. A common cause of fatalities for e-scooter riders is a collision between a car and an e-scooter. To develop a better understanding of the complex injury mechanisms in these collisions, four crashes between an e-scooter and a family car/sedan and a sports utility vehicle were simulated using finite element models. The vehicles impacted the e-scooter at a speed of 30 km/hr in a perpendicular collisio...
Source: Computer Methods in Biomechanics and Biomedical Engineering - May 2, 2024 Category: Biomedical Engineering Authors: Rafael Chontos Daniel Grindle Alexandrina Untaroiu Zachary Doerzaph Costin Untaroiu Source Type: research

A biomechanical analysis of novel endovascular implants for aortic valve replacement and ascending aortic repair
This study proposes a novel linked diamond-shaped implant (LD). To evaluate the safety and effectiveness of this new implant, finite element simulation models were created to assess the risks of endoleak, migration, and vascular wall rupture under annulus displacement load. After the SZ, SD, and LD implants were grafted in virtual release method, all the implants can cover tear-entry located in the ascending aorta, but space distance (δ) which exposed to blood was 14.5, 13.1, and 7.4 mm, respectively; the maximum areas of contact gap was 76.5, 51.5 and 6.3 mm2; the maximum migration distance (ΔL1) were 1.27, 1.06, and 0....
Source: Computer Methods in Biomechanics and Biomedical Engineering - May 2, 2024 Category: Biomedical Engineering Authors: Hui Zuo Wentao Feng Jingbo Wu Tong Gao Yubo Fan Source Type: research

A numerical investigation of e-scooter-to-vehicle traffic accidents
Comput Methods Biomech Biomed Engin. 2024 May 2:1-5. doi: 10.1080/10255842.2024.2347477. Online ahead of print.ABSTRACTWithin the past decade, injuries caused by electric scooter (e-scooter) crashes have significantly increased. A common cause of fatalities for e-scooter riders is a collision between a car and an e-scooter. To develop a better understanding of the complex injury mechanisms in these collisions, four crashes between an e-scooter and a family car/sedan and a sports utility vehicle were simulated using finite element models. The vehicles impacted the e-scooter at a speed of 30 km/hr in a perpendicular collisio...
Source: Computer Methods in Biomechanics and Biomedical Engineering - May 2, 2024 Category: Biomedical Engineering Authors: Rafael Chontos Daniel Grindle Alexandrina Untaroiu Zachary Doerzaph Costin Untaroiu Source Type: research

A biomechanical analysis of novel endovascular implants for aortic valve replacement and ascending aortic repair
This study proposes a novel linked diamond-shaped implant (LD). To evaluate the safety and effectiveness of this new implant, finite element simulation models were created to assess the risks of endoleak, migration, and vascular wall rupture under annulus displacement load. After the SZ, SD, and LD implants were grafted in virtual release method, all the implants can cover tear-entry located in the ascending aorta, but space distance (δ) which exposed to blood was 14.5, 13.1, and 7.4 mm, respectively; the maximum areas of contact gap was 76.5, 51.5 and 6.3 mm2; the maximum migration distance (ΔL1) were 1.27, 1.06, and 0....
Source: Computer Methods in Biomechanics and Biomedical Engineering - May 2, 2024 Category: Biomedical Engineering Authors: Hui Zuo Wentao Feng Jingbo Wu Tong Gao Yubo Fan Source Type: research

Compression of EEG signals with the LSTM-autoencoder via domain adaptation approach
Comput Methods Biomech Biomed Engin. 2024 Apr 30:1-14. doi: 10.1080/10255842.2024.2346356. Online ahead of print.ABSTRACTThe successful implementation of neural network-based EEG signal compression has led to significant cost reductions in data transmission. However, a major obstacle in this process arises from the decline in performance when compressing EEG signals from multiple subjects. This challenge arises due to the notable feature shift of EEG signals between subjects, which poses an impediment to the neural network's efficient concurrent acquisition of information from multiple subjects. To address this limitation ...
Source: Computer Methods in Biomechanics and Biomedical Engineering - April 30, 2024 Category: Biomedical Engineering Authors: Yongfei Liu Fan Yang Binbin Wu Source Type: research

TriKSV-LG: a robust approach to disease prediction in healthcare systems using AI and Levy Gazelle optimization
Comput Methods Biomech Biomed Engin. 2024 Apr 30:1-17. doi: 10.1080/10255842.2024.2339479. Online ahead of print.ABSTRACTA seamless connection between the Internet and people is provided by the Internet of Things (IoT). Furthermore, lives are enhanced using the integration of the cloud layer. In the healthcare domain, a reactive healthcare strategy is turned into a proactive one using predictive analysis. The challenges faced by existing techniques are inaccurate prediction and a time-consuming process. This paper introduces an Artificial Intelligence (AI) and IoT-based disease prediction method, the TriKernel Support Vect...
Source: Computer Methods in Biomechanics and Biomedical Engineering - April 30, 2024 Category: Biomedical Engineering Authors: Kavitha Dhanushkodi Prema Vinayagasundaram Vidhya Anbalagan Surendran Subbaraj Ravikumar Sethuraman Source Type: research

Compression of EEG signals with the LSTM-autoencoder via domain adaptation approach
Comput Methods Biomech Biomed Engin. 2024 Apr 30:1-14. doi: 10.1080/10255842.2024.2346356. Online ahead of print.ABSTRACTThe successful implementation of neural network-based EEG signal compression has led to significant cost reductions in data transmission. However, a major obstacle in this process arises from the decline in performance when compressing EEG signals from multiple subjects. This challenge arises due to the notable feature shift of EEG signals between subjects, which poses an impediment to the neural network's efficient concurrent acquisition of information from multiple subjects. To address this limitation ...
Source: Computer Methods in Biomechanics and Biomedical Engineering - April 30, 2024 Category: Biomedical Engineering Authors: Yongfei Liu Fan Yang Binbin Wu Source Type: research

TriKSV-LG: a robust approach to disease prediction in healthcare systems using AI and Levy Gazelle optimization
Comput Methods Biomech Biomed Engin. 2024 Apr 30:1-17. doi: 10.1080/10255842.2024.2339479. Online ahead of print.ABSTRACTA seamless connection between the Internet and people is provided by the Internet of Things (IoT). Furthermore, lives are enhanced using the integration of the cloud layer. In the healthcare domain, a reactive healthcare strategy is turned into a proactive one using predictive analysis. The challenges faced by existing techniques are inaccurate prediction and a time-consuming process. This paper introduces an Artificial Intelligence (AI) and IoT-based disease prediction method, the TriKernel Support Vect...
Source: Computer Methods in Biomechanics and Biomedical Engineering - April 30, 2024 Category: Biomedical Engineering Authors: Kavitha Dhanushkodi Prema Vinayagasundaram Vidhya Anbalagan Surendran Subbaraj Ravikumar Sethuraman Source Type: research

Compression of EEG signals with the LSTM-autoencoder via domain adaptation approach
Comput Methods Biomech Biomed Engin. 2024 Apr 30:1-14. doi: 10.1080/10255842.2024.2346356. Online ahead of print.ABSTRACTThe successful implementation of neural network-based EEG signal compression has led to significant cost reductions in data transmission. However, a major obstacle in this process arises from the decline in performance when compressing EEG signals from multiple subjects. This challenge arises due to the notable feature shift of EEG signals between subjects, which poses an impediment to the neural network's efficient concurrent acquisition of information from multiple subjects. To address this limitation ...
Source: Computer Methods in Biomechanics and Biomedical Engineering - April 30, 2024 Category: Biomedical Engineering Authors: Yongfei Liu Fan Yang Binbin Wu Source Type: research

Neural harmony: revolutionizing thyroid nodule diagnosis with hybrid networks and genetic algorithms
Comput Methods Biomech Biomed Engin. 2024 Apr 22:1-18. doi: 10.1080/10255842.2024.2341969. Online ahead of print.ABSTRACTIn the contemporary world, thyroid disease poses a prevalent health issue, particularly affecting women's well-being. Recognizing the significance of maternal thyroid (MT) hormones in fetal neurodevelopment during the first half of pregnancy, this study introduces the HNN-GSO model. This groundbreaking hybrid approach, utilizing the MT dataset, integrates ResNet-50 and Artificial Neural Network (ANN) within a Glow-worm Swarm Optimization (GSO) framework for optimal parameter tuning. With a comprehensive ...
Source: Computer Methods in Biomechanics and Biomedical Engineering - April 22, 2024 Category: Biomedical Engineering Authors: H Summia Parveen S Karthik Kavitha M S Source Type: research

Neural harmony: revolutionizing thyroid nodule diagnosis with hybrid networks and genetic algorithms
Comput Methods Biomech Biomed Engin. 2024 Apr 22:1-18. doi: 10.1080/10255842.2024.2341969. Online ahead of print.ABSTRACTIn the contemporary world, thyroid disease poses a prevalent health issue, particularly affecting women's well-being. Recognizing the significance of maternal thyroid (MT) hormones in fetal neurodevelopment during the first half of pregnancy, this study introduces the HNN-GSO model. This groundbreaking hybrid approach, utilizing the MT dataset, integrates ResNet-50 and Artificial Neural Network (ANN) within a Glow-worm Swarm Optimization (GSO) framework for optimal parameter tuning. With a comprehensive ...
Source: Computer Methods in Biomechanics and Biomedical Engineering - April 22, 2024 Category: Biomedical Engineering Authors: H Summia Parveen S Karthik Kavitha M S Source Type: research

Neural harmony: revolutionizing thyroid nodule diagnosis with hybrid networks and genetic algorithms
Comput Methods Biomech Biomed Engin. 2024 Apr 22:1-18. doi: 10.1080/10255842.2024.2341969. Online ahead of print.ABSTRACTIn the contemporary world, thyroid disease poses a prevalent health issue, particularly affecting women's well-being. Recognizing the significance of maternal thyroid (MT) hormones in fetal neurodevelopment during the first half of pregnancy, this study introduces the HNN-GSO model. This groundbreaking hybrid approach, utilizing the MT dataset, integrates ResNet-50 and Artificial Neural Network (ANN) within a Glow-worm Swarm Optimization (GSO) framework for optimal parameter tuning. With a comprehensive ...
Source: Computer Methods in Biomechanics and Biomedical Engineering - April 22, 2024 Category: Biomedical Engineering Authors: H Summia Parveen S Karthik Kavitha M S Source Type: research

Neural harmony: revolutionizing thyroid nodule diagnosis with hybrid networks and genetic algorithms
Comput Methods Biomech Biomed Engin. 2024 Apr 22:1-18. doi: 10.1080/10255842.2024.2341969. Online ahead of print.ABSTRACTIn the contemporary world, thyroid disease poses a prevalent health issue, particularly affecting women's well-being. Recognizing the significance of maternal thyroid (MT) hormones in fetal neurodevelopment during the first half of pregnancy, this study introduces the HNN-GSO model. This groundbreaking hybrid approach, utilizing the MT dataset, integrates ResNet-50 and Artificial Neural Network (ANN) within a Glow-worm Swarm Optimization (GSO) framework for optimal parameter tuning. With a comprehensive ...
Source: Computer Methods in Biomechanics and Biomedical Engineering - April 22, 2024 Category: Biomedical Engineering Authors: H Summia Parveen S Karthik Kavitha M S Source Type: research

Neural harmony: revolutionizing thyroid nodule diagnosis with hybrid networks and genetic algorithms
Comput Methods Biomech Biomed Engin. 2024 Apr 22:1-18. doi: 10.1080/10255842.2024.2341969. Online ahead of print.ABSTRACTIn the contemporary world, thyroid disease poses a prevalent health issue, particularly affecting women's well-being. Recognizing the significance of maternal thyroid (MT) hormones in fetal neurodevelopment during the first half of pregnancy, this study introduces the HNN-GSO model. This groundbreaking hybrid approach, utilizing the MT dataset, integrates ResNet-50 and Artificial Neural Network (ANN) within a Glow-worm Swarm Optimization (GSO) framework for optimal parameter tuning. With a comprehensive ...
Source: Computer Methods in Biomechanics and Biomedical Engineering - April 22, 2024 Category: Biomedical Engineering Authors: H Summia Parveen S Karthik Kavitha M S Source Type: research

Tunable < em > Q < /em > -factor wavelet transform based identification of diabetic patients using ECG signals
Comput Methods Biomech Biomed Engin. 2024 Apr 18:1-10. doi: 10.1080/10255842.2024.2342512. Online ahead of print.ABSTRACTDiabetes is a chronic health condition that is characterized by increased levels of glucose (sugar) in the blood. It can have harmful effects on different parts of the body, such as the retina of the eyes, skin, nervous system, kidneys, and heart. Diabetes affects the structure of electrocardiogram (ECG) impulses by causing cardiovascular autonomic dysfunction. Multi-resolution analysis of the input ECG signal is utilized in this paper to develop a machine learning-based system for the automated detectio...
Source: Computer Methods in Biomechanics and Biomedical Engineering - April 18, 2024 Category: Biomedical Engineering Authors: Anuja Jain Anurag Verma Amit Kumar Verma Varun Bajaj Source Type: research