Journal of Biomimetics, Biomaterials and Biomedical Engineering最新文献_第2页

Volumetric Alterations in Brain Structures Caused by Autism during Different Age Stages 不同年龄阶段自闭症患者大脑结构的体积变化

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Journal of Biomimetics, Biomaterials and Biomedical Engineering Pub Date : 2024-04-10 DOI: 10.4028/p-yjqi3j

I. Masad, Lamis R. Banyissa, A. M. Alqudah

{"title":"Volumetric Alterations in Brain Structures Caused by Autism during Different Age Stages","authors":"I. Masad, Lamis R. Banyissa, A. M. Alqudah","doi":"10.4028/p-yjqi3j","DOIUrl":"https://doi.org/10.4028/p-yjqi3j","url":null,"abstract":"Conclusions in literature regarding the effect of Autism on the size of different brain structures are contradictory. The aim of this study is to determine the effect of Autism on the volumes of different brain subcortical structures, and the age stage at which those changes occur. 7 main brain structures were segmented and their volumes were obtained. Volumes and the ratio of the volume to total brain volume (SBR) were compared in Autism group to their corresponding values in Control group. Then, each group was divided into 4 subgroups based on age; the comparison was repeated for each subgroup. Independent t-test was used to determine if significant differences existed between compared groups. Significant reductions were observed in the SBR of Autistic Pallidum and Accumbens compared to Control group when considering the full range of ages (5–25 years). However, Amygdala’s volume was significantly smaller in Autism in the 5–8 year subgroup. In addition, the SBR of Putaman, Pallidum, Hippocampus, and Accumbens were reduced in the 18–25 year Autism subgroup. In conclusion, the alteration in the ratio of structure’s volume to total brain volume is a better indicator of Autism diagnosis than change in the absolute volume alone.","PeriodicalId":15161,"journal":{"name":"Journal of Biomimetics, Biomaterials and Biomedical Engineering","volume":null,"pages":null},"PeriodicalIF":0.7,"publicationDate":"2024-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140717886","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Adaptive Random Forest for Gait Prediction in Lower Limb Exoskeleton 用于下肢外骨骼步态预测的自适应随机森林

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Journal of Biomimetics, Biomaterials and Biomedical Engineering Pub Date : 2024-04-10 DOI: 10.4028/p-q2hybx

Xu Dong Guo, Feng Qi Zhong, Jian Ru Xiao, Zhen Hua Zhou, Wei Xu

{"title":"Adaptive Random Forest for Gait Prediction in Lower Limb Exoskeleton","authors":"Xu Dong Guo, Feng Qi Zhong, Jian Ru Xiao, Zhen Hua Zhou, Wei Xu","doi":"10.4028/p-q2hybx","DOIUrl":"https://doi.org/10.4028/p-q2hybx","url":null,"abstract":"To improve the human-machine cooperativity of a wearable lower limb exoskeleton, a gait recognition method based on surface electromyography (sEMG) was proposed. sEMG of rectus femoris, vastus medialis, vastus lateralis, semitendinosus and biceps femoris were acquired. Then, time domain, frequency domain, time-frequency domain and nonlinear features were extracted. The integrated value of electromyography, variance, root mean square and wavelength were selected as the time domain features and the frequency domain feature includes mean power frequency. Wavelet packet energy was selected as the time-frequency domain feature. Nonlinear features including approximate entropy, sample entropy and fuzzy entropy of sEMG were extracted. Classification accuracy of different feature matrices and different muscle groups were constructed and verified. The optimal multi-dimensional fusion feature matrix was determined. Introducing the Bayesian optimization algorithm, the Bayesian optimized Random Forest classification model was constructed to identify different gait phases. Comparing with Random Forest, the accuracy of the optimized Random Forest was improved by 5.89%. Applying Random Forest algorithm with Bayesian optimization to gait prediction based on sEMG, the followership and consistency of gait control in lower limb exoskeleton can be improved. This template explains and demonstrates how to prepare your camera-ready paper for Trans Tech Publications. The best is to read these instructions and follow the outline of this text.","PeriodicalId":15161,"journal":{"name":"Journal of Biomimetics, Biomaterials and Biomedical Engineering","volume":null,"pages":null},"PeriodicalIF":0.7,"publicationDate":"2024-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140718589","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Numerical Simulation Study on the Effect of Resistance Microstructure on Blood Flow Resistance 阻力微结构对血流阻力影响的数值模拟研究

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Journal of Biomimetics, Biomaterials and Biomedical Engineering Pub Date : 2024-04-10 DOI: 10.4028/p-ymq40w

Wen Ting Wang, Yun Qing Gu, Ling Zhi Yu, Zhuofan Yin, Zhou Li, Deng Hao Wu, Jie Gang Mou, Shui Hua Zheng, Hui Jie Zhou

引用次数: 0

The Influence of Black Tea on Secretory IgA from Saliva in Caries and Caries-Free Subjects 红茶对龋齿和无龋受试者唾液分泌型 IgA 的影响

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Journal of Biomimetics, Biomaterials and Biomedical Engineering Pub Date : 2024-04-10 DOI: 10.4028/p-b3v5u6

A. R. Fitri, Yendriwati Yendriwati, Pocut Astari, Diniaturahmi Diniaturahmi, A. Primasari

{"title":"The Influence of Black Tea on Secretory IgA from Saliva in Caries and Caries-Free Subjects","authors":"A. R. Fitri, Yendriwati Yendriwati, Pocut Astari, Diniaturahmi Diniaturahmi, A. Primasari","doi":"10.4028/p-b3v5u6","DOIUrl":"https://doi.org/10.4028/p-b3v5u6","url":null,"abstract":"The crucial role of saliva in the prevention of dental caries is associated with the regulation of its flow rate as well as salivary protein. Black tea, derived from the plant Camellia sinensis, contains catechins and has been shown to have a beneficial effect on saliva in preventing tooth decay. Nevertheless, research on the oral health benefits of black tea is still limited. This study aimed to investigate the effects of black tea (Camellia sinensis) on salivary pH (potential hydrogen), salivary flow rate, lysozyme, and sIgA levels in caries and caries-free patients. The study used a quasi-experimental design with a pre-test and a post-test. Twenty six subjects (male or female) were selected and divided into two groups (caries and caries free), thirteen subjects for each. Saliva samples were obtained before and thirty minutes after tea consumption. The flow rate of saliva was measured by dividing the weight of saliva collected by the time. At the same time, secretory immunoglobulin A (sIgA) levels were analyzed by enzyme-linked immunosorbent assay (ELISA). The t-dependent and t-independent tests and Mann-Whitney tests were selected to evaluate the effect of drinking black tea on salivary flow rate and sIgA value. The results showed that black tea significantly increased salivary flow rate but did not significantly affect the concentration of sIgA. No statistically significant differences in salivary flow rate and sIgA were observed between patients with and without caries after tea consumption. Although the concentration of sIgA did not demonstrate a significant change, however, the salivary flow rate was significantly enhanced. Therefore, drinking black tea did not negatively affect the saliva in the oral cavity, suggesting it can be a good option for daily consumption due to its protective role against dental caries.","PeriodicalId":15161,"journal":{"name":"Journal of Biomimetics, Biomaterials and Biomedical Engineering","volume":null,"pages":null},"PeriodicalIF":0.7,"publicationDate":"2024-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140718426","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Sleep Apnea Detection Methodology Based on SE-ResNeXt Model Using Single-Lead ECG 基于 SE-ResNeXt 模型、使用单导联心电图的睡眠呼吸暂停检测方法

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Journal of Biomimetics, Biomaterials and Biomedical Engineering Pub Date : 2024-04-10 DOI: 10.4028/p-cbr55f

Tran Anh Vu, Do Thi Thu Phuong, H. Q. Huy, N. Kien, Pham Thi Viet Huong

{"title":"A Sleep Apnea Detection Methodology Based on SE-ResNeXt Model Using Single-Lead ECG","authors":"Tran Anh Vu, Do Thi Thu Phuong, H. Q. Huy, N. Kien, Pham Thi Viet Huong","doi":"10.4028/p-cbr55f","DOIUrl":"https://doi.org/10.4028/p-cbr55f","url":null,"abstract":"Sleep apnea (SA) is considered one of the most dangerous sleep disorders. That happens when a person is sleeping, his or her breathing repeatedly stops and starts. In order to develop therapies and management strategies that will be effective in treating SA, it is critical to precisely diagnose sleep apnea episodes. In this study, the single-lead electrocardiogram (ECG), one of the most physiologically pertinent markers for SA, is analyzed to identify the SA issue. In this paper, a novel signal processing method is proposed, in which noise filtering is added and the detection of R peaks is utilized. Particularly, the Teager Energy Operator (TEO) algorithm is applied to detect R peaks and then obtain the RR intervals and amplitudes. Afterward, the SE-ResNeXt 50 deep learning model, which has never been used in SA detection before, is used as a classifier to perform the objective. The proposed model, which is a variation of ResNet 50, has the ability to use global information to highlight helpful information while allowing for feature recalibration. In order to confirm the proposed method, the benchmark dataset PhysioNet ECG Sleep Apnea v1.0.0 is used. Results are better than current research, with 89.21% accuracy, 90.29% sensitivity, and 87.36% specificity. This is also clear evidence that the ECG signals can be taken advantage of to efficiently detect SA.","PeriodicalId":15161,"journal":{"name":"Journal of Biomimetics, Biomaterials and Biomedical Engineering","volume":null,"pages":null},"PeriodicalIF":0.7,"publicationDate":"2024-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140717285","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Journal of Biomimetics, Biomaterials and Biomedical Engineering Vol. 64 生物仿生学、生物材料和生物医学工程学杂志》第 64 卷

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Journal of Biomimetics, Biomaterials and Biomedical Engineering Pub Date : 2024-04-10 DOI: 10.4028/b-es7wrk

引用次数: 0

Influence of Mechanical Properties of Dental Implants on Biomechanical Behavior: A Three-Dimensional Finite Element Analysis 牙科植入物的机械特性对生物力学行为的影响：三维有限元分析

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Journal of Biomimetics, Biomaterials and Biomedical Engineering Pub Date : 2024-04-10 DOI: 10.4028/p-g22co2

Youcef Goradia, Sadek Gouasmi, Sid Ahmed Reffas

引用次数: 0

Analytical Study of Interstitial Fluid Extractive Microneedle Arrays Using Differential Transform Method 基于微分变换的间隙流体萃取微针阵列分析研究

Journal of Biomimetics, Biomaterials and Biomedical Engineering Pub Date : 2023-11-03 DOI: 10.4028/p-2spruh

Ihuoma V. Diwe, Olurotimi A. Adeleye, Henry E. Mgbemere

{"title":"Analytical Study of Interstitial Fluid Extractive Microneedle Arrays Using Differential Transform Method","authors":"Ihuoma V. Diwe, Olurotimi A. Adeleye, Henry E. Mgbemere","doi":"10.4028/p-2spruh","DOIUrl":"https://doi.org/10.4028/p-2spruh","url":null,"abstract":"The computational studies of a predictive mathematical model for the extraction of interstitial (ISF) for transdermal and non-invasive diagnosis using biodegradable and hollow microneedle patch is presented in this paper. Rapid Diagnostic Tests diagnosis, which is non-invasive, affordable, straightforward, and provides results promptly and reliably, has increased access to parasite-based analysis on a global scale. Microneedle arrays are a rapidly evolving and promising technology for transdermal interstitial fluid extraction, which is used for many clinical diagnostic procedures. Hence, a developed mathematical predictive model used to optimize the design of microneedle patch for transdermal ISF extraction and subsequent diagnosis using dissolvable microneedle arrays was applied in this study. The model's solutions were obtained using the Differential Transform Method. The numerical Runge-Kutta method of fourth order was used to validate it. An experimental test result was also used to further validate the analytical results in the absence of the extracted velocity parameter. And there was a good agreement among them. Influence of dissolution rate constant, microneedle height, diffusion coefficient, velocity of ISF, microneedle ISF drug load, and density of the microneedle; were investigated. Increase in diffusion coefficient and density led to an increase in concentration of ISF extracted over time, an increase in dissolution rate led to a decrease in concentration extracted, while decrease in drug load and height, led to increase in ISF concentration extracted. A negligible effect was observed by varying the velocity of ISF extracted. The approximate analytical approach utilized in the current work has given us a more precise strategy for creating a mathematical model that predicts how ISF will be extracted from skin for use in transdermal and non-invasive rapid diagnostic tests.","PeriodicalId":15161,"journal":{"name":"Journal of Biomimetics, Biomaterials and Biomedical Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135819885","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Journal of Biomimetics, Biomaterials and Biomedical Engineering Vol. 63 生物仿生学、生物材料和生物医学工程学杂志》第 63 卷

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Journal of Biomimetics, Biomaterials and Biomedical Engineering Pub Date : 2023-11-03 DOI: 10.4028/b-q6rjge

David Duday, S. Nandyala, A. Shidiq, Thangaprakash Sengodan

引用次数: 0

Active Rehabilitation Gloves Based on Brain-Computer Interfaces and Deep Learning 基于脑机接口和深度学习的主动康复手套

Journal of Biomimetics, Biomaterials and Biomedical Engineering Pub Date : 2023-11-03 DOI: 10.4028/p-2jc2qf

Jia Hua Zhu, Xing Zhao Shi, Xing Yue Cheng, Qi Rui Yang, Ruo Xiu Xiao

引用次数: 0