2022 14th Biomedical Engineering International Conference (BMEiCON)最新文献_第5页

Automatic Ray-Sum Panoramic Synthesis from Cone-Beam CT Data 从锥束CT数据自动射线和全景合成

2022 14th Biomedical Engineering International Conference (BMEiCON) Pub Date : 2022-11-10 DOI: 10.1109/BMEiCON56653.2022.10011585

Duangkamol Banarsarn, W. Narkbuakaew, Kongyot Wangkaoom, Saowanee Iamsiri, S. Thongvigitmanee

引用次数: 0

A Low-Cost Digital Stethoscope For Normal and Abnormal Heart Sound Classification 一种低成本数字听诊器用于心音正常与异常分类

2022 14th Biomedical Engineering International Conference (BMEiCON) Pub Date : 2022-11-10 DOI: 10.1109/BMEiCON56653.2022.10012113

Sorawit Khoruamkid, S. Visitsattapongse

{"title":"A Low-Cost Digital Stethoscope For Normal and Abnormal Heart Sound Classification","authors":"Sorawit Khoruamkid, S. Visitsattapongse","doi":"10.1109/BMEiCON56653.2022.10012113","DOIUrl":"https://doi.org/10.1109/BMEiCON56653.2022.10012113","url":null,"abstract":"Heart disease is a major problem in most deaths. To conquer this situation, heartbeat sound analysis is a convenient method for diagnosing heart disease. Heartbeat sound classification remains a challenging problem in heart sound division and feature extraction. A stethoscope is a medical device widely used by physicians to listen to the heartbeat. An acoustic stethoscope operates on the chest piece to the ears of the listener. The main problem is in listening to heart sounds that the low signal level and are difficult to be analyzed. Adding electronic circuitry and software to acoustic stethoscopes will strengthen the heart rate signal and can minimize error analysis of the state of the patient's heart. Machine learning is used to efficiently analyze and classify heart sounds. Convolutional Neural Network (CNN) models and Support Vector Machine (SVM) with feature extractors were effective methods and were used in this research. First, the Phonocardiogram (PCG) files are fragmented into pieces of equivalent length. Then, we convert the PCG files to a spectrogram. The spectrogram images are fed into a convolutional neural network and support vector machine. The best result is using an Inception V3 model with the CNN classifier which has an accuracy of 0.909, with 0.948 sensitivity and 0.869 specificity.","PeriodicalId":177401,"journal":{"name":"2022 14th Biomedical Engineering International Conference (BMEiCON)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131505975","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

Development of Variable-Elasticity Cell Scaffolds Using Magnetic Gels 磁性凝胶制备变弹性细胞支架

2022 14th Biomedical Engineering International Conference (BMEiCON) Pub Date : 2022-11-10 DOI: 10.1109/BMEiCON56653.2022.10012083

Yuya Shimomura, Zugui Peng, K. Shimba, Y. Miyamoto, T. Yagi

{"title":"Development of Variable-Elasticity Cell Scaffolds Using Magnetic Gels","authors":"Yuya Shimomura, Zugui Peng, K. Shimba, Y. Miyamoto, T. Yagi","doi":"10.1109/BMEiCON56653.2022.10012083","DOIUrl":"https://doi.org/10.1109/BMEiCON56653.2022.10012083","url":null,"abstract":"It is well known that cells are influenced by the properties of their extracellular matrix, which is primarily composed of sugars and proteins. In particular, there exists a strong relationship between the elasticity of the extracellular substrate and cell motility. Clarification of the relationship between cells and substrate elasticity is expected to prove useful in both the design of scaffold materials for tissue engineering and the elucidation of the mechanisms of diseases that cause fibrosis. The elasticity of the extracellular matrix is characterized by two features: a partial elastic gradient and day-to-day variation. Most previous studies reproduced either one or the other, and this likely does not reflect the in vivo situation. Thus, a greater understanding of the changes in cells and substrates is needed. In this study, we propose a scaffold based on a magnetic gel with variable elasticity. We describe the preparation of a magnetic gel and cell seeding on its surface. The cells were cultured under the application of magnetic force after seeding, revealing an increase in the cell area due to the hardening of the magnetic gel in the presence of magnetic force.","PeriodicalId":177401,"journal":{"name":"2022 14th Biomedical Engineering International Conference (BMEiCON)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116810874","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

Preliminary Study of the Relationship Between Age and Gender using Sounds Generated from the Nostrils and Pharynx During Swallowing in Healthy Subjects 利用健康受试者吞咽时鼻腔和咽部发出的声音初步研究年龄和性别的关系

2022 14th Biomedical Engineering International Conference (BMEiCON) Pub Date : 2022-11-10 DOI: 10.1109/BMEiCON56653.2022.10012075

Naru Sato, T. Igasaki, Chiharu Matsumoto, Tadashi Sakata, Hitomi Maeda

{"title":"Preliminary Study of the Relationship Between Age and Gender using Sounds Generated from the Nostrils and Pharynx During Swallowing in Healthy Subjects","authors":"Naru Sato, T. Igasaki, Chiharu Matsumoto, Tadashi Sakata, Hitomi Maeda","doi":"10.1109/BMEiCON56653.2022.10012075","DOIUrl":"https://doi.org/10.1109/BMEiCON56653.2022.10012075","url":null,"abstract":"Although many studies have evaluated swallowing using sounds from the pharynx, few studies have evaluated it using sounds from the nostrils. Therefore, in this study, we placed two microphones near the nostrils and pharynx and recorded sounds produced while swallowing five grams of solid jelly. The participants included 16 healthy volunteers (eight in their early twenties (22-24 years old; younger group) and eight early elderly (66-74 years old; elder group), four males and four females in each group) over eight trials. We then examined the peak sound pressure levels of the nostrils and pharynx waveforms and investigated the time lags between the sounds generated by the nostrils and pharynx in each subject. As a result, although the time lags varied across the subjects, the minimum time lags observed in the elder group (0.32 – 0.78 s) were significantly longer than those of the younger group (0.04 – 0.44 s. $F_{1:15}$ = 30.10, $p lt 0.05$, repeated two-way ANOVA), and the maximum time lags observed in the female subjects were significantly longer (1.04 – 2.30 s) than those of males (0.20 – 1.43 s. $F_{1:15}$ = 5.57, $p lt 0.05$, repeated two-way ANOVA). It was suggested that measuring the sounds from both the pharynx and nostrils during swallowing helps in evaluating the swallowing function with aging, and considering gender differences.","PeriodicalId":177401,"journal":{"name":"2022 14th Biomedical Engineering International Conference (BMEiCON)","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115452797","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

The Importance of Gender Specification for Detection of Driver Fatigue using a Single EEG Channel 性别特征对单脑电通道驾驶员疲劳检测的重要性

2022 14th Biomedical Engineering International Conference (BMEiCON) Pub Date : 2022-11-10 DOI: 10.1109/BMEiCON56653.2022.10012118

M. Shahbakhti, Matin Beiramvand, Erfan Nasiri, W. Chen, Jordi Solé-Casals, M. Wierzchoń, Anna Broniec-Wójcik, P. Augustyniak, V. Marozas

{"title":"The Importance of Gender Specification for Detection of Driver Fatigue using a Single EEG Channel","authors":"M. Shahbakhti, Matin Beiramvand, Erfan Nasiri, W. Chen, Jordi Solé-Casals, M. Wierzchoń, Anna Broniec-Wójcik, P. Augustyniak, V. Marozas","doi":"10.1109/BMEiCON56653.2022.10012118","DOIUrl":"https://doi.org/10.1109/BMEiCON56653.2022.10012118","url":null,"abstract":"Although detection of the driver fatigue using a single electroencephalography (EEG) channel has been addressed in literature, the gender differentiation for applicability of the model has not been investigated heretofore. Motivated accordingly, we address the detection of driver fatigue based the gender-segregated datasets, where each of them contains 8 subjects. After splitting the EEG signal into its sub-bands (delta, theta, alpha, beta, and gamma) using discrete wavelet transform, the log energy entropy of each band is computed to form the feature vector. Afterwards, the feature vector is randomly split into 50% for training and 50% for the unseen testing, and fed to a support vector machine model. When comparing the classification results of fatigue driving detection between the gender segregated and non-gender segregated datasets, the former achieved the accuracy 78% and 77% for male and female subjects, respectively, than the latter (71%). The obtained results show the importance of gender-specification for the driver fatigue detection.","PeriodicalId":177401,"journal":{"name":"2022 14th Biomedical Engineering International Conference (BMEiCON)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124076130","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: 2

Computerized Medical Device Management System In Luangprabang Provincial Hospital 琅勃拉邦省医院计算机化医疗设备管理系统

2022 14th Biomedical Engineering International Conference (BMEiCON) Pub Date : 2022-11-10 DOI: 10.1109/BMEiCON56653.2022.10012115

Sengaloun Xayalath, N. Thongpance, Anantasak Wongkamhang, Anuchit Nirapai

引用次数: 0

The effect of visual cognition on the fear caused by pain recall 视觉认知对疼痛回忆引起的恐惧的影响

2022 14th Biomedical Engineering International Conference (BMEiCON) Pub Date : 2022-11-10 DOI: 10.1109/BMEiCON56653.2022.10012108

Nina Itagaki, K. Iramina, Yutarou Nakada

引用次数: 0

Evaluating Improvement on Feature Selection for Classification of Implicit Learning on EEG’s Multiscale Entropy Data using BMNABC 基于BMNABC的脑电多尺度熵数据内隐学习分类特征选择改进评价

2022 14th Biomedical Engineering International Conference (BMEiCON) Pub Date : 2022-11-10 DOI: 10.1109/BMEiCON56653.2022.10012069

Chayapol Chaiyanan, B. Kaewkamnerdpong

{"title":"Evaluating Improvement on Feature Selection for Classification of Implicit Learning on EEG’s Multiscale Entropy Data using BMNABC","authors":"Chayapol Chaiyanan, B. Kaewkamnerdpong","doi":"10.1109/BMEiCON56653.2022.10012069","DOIUrl":"https://doi.org/10.1109/BMEiCON56653.2022.10012069","url":null,"abstract":"Those who are good at implicit learning can learn things faster and are more adaptable in the fast pace age of information. Implicit learning is a type of learning without being explicitly taught. It’s commonly seen in younger children when they develop their ability to speak their native language without learning grammar. The human brain can be trained to be good at learning by training the brain to be in the state of learning more often. By using neurofeedback to regulate the human brain state, educators and learners can help each other in training the brain to be better implicit learners. Our research aims to classify implicit learning events from EEG signals to help identify and moderate such states. This paper analyzed the feature selection process section to improve classification performance. We used previously measured participants' EEG signals while performing cognitive task experiments. Those signals were then getting feature extracted into Multiscale Entropy. Previously, Artificial Bee Colony (ABC) was used on the Multiscale Entropy to help classify the implicit learning events with reasonable success. However, an improvement was required to make the entire system more optimized due to how features being selected were in a binary search space. Binary Multi-Neighborhood Artificial Bee Colony (BMNABC) was chosen as an alternative. The comparison indicated that BMNABC increased the accuracy to as high as 90.57% and can be regarded as a promising method for identifying implicit learning events.","PeriodicalId":177401,"journal":{"name":"2022 14th Biomedical Engineering International Conference (BMEiCON)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132660325","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

Reconstruction of 3D Abdominal Aorta Aneurysm from Computed Tomographic Angiography Using 3D U-Net Deep Learning Network 利用三维U-Net深度学习网络重建三维腹主动脉瘤

2022 14th Biomedical Engineering International Conference (BMEiCON) Pub Date : 2022-11-10 DOI: 10.1109/BMEiCON56653.2022.10012097

Siriporn Kongrat, C. Pintavirooj, S. Tungjitkusolmun

引用次数: 0

A radiopathomics model for prognosis prediction in patients with gastric cancer 胃癌患者预后预测的放射病理学模型

2022 14th Biomedical Engineering International Conference (BMEiCON) Pub Date : 2022-11-10 DOI: 10.1109/BMEiCON56653.2022.10012107

Yuanshen Zhao, Jingxian Duan, Zhicheng Li, N. Chai, Longsong Li

{"title":"A radiopathomics model for prognosis prediction in patients with gastric cancer","authors":"Yuanshen Zhao, Jingxian Duan, Zhicheng Li, N. Chai, Longsong Li","doi":"10.1109/BMEiCON56653.2022.10012107","DOIUrl":"https://doi.org/10.1109/BMEiCON56653.2022.10012107","url":null,"abstract":"Predicting gastric cancer prognosis is imperative for more appropriate clinical treatment plans. Compared with traditional radiomics model adopting CT images alone, the radiopathomics is a novel medical image analysis strategy which employed the radiomcs features extracted from CT image and pathomics features extracted from pathological image to build a prediction model. In this paper, we developed a radiopathomics model to predict whether patients with gastric cancer survive more than 2 years. By using LASSO algorithm, two pathomics features, a radiomics feature and the clinical variables of TNM were selected from totally 1565 features to build the prediction model. For reflecting the advantage of the radiopathomics model, we implemented the comparison tests between the radiopathomics model with radiomics model and pathomics model. The results showed that the radiopathomics model achieved an AUC of 0.904 and an accuracy of 84.2%, which was significantly better than the other two models. It demonstrated that integrated of the microscopic level and macroscopic level phenotype information for tumor could be useful in prediction of prognosis.","PeriodicalId":177401,"journal":{"name":"2022 14th Biomedical Engineering International Conference (BMEiCON)","volume":"16 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132286834","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