2018 11th Biomedical Engineering International Conference (BMEiCON)最新文献_第7页

Inverse Kinematics Analysis, Size Optimization and Error Analysis of Urology Surgical Manipulator 泌尿外科手术机械臂逆运动学分析、尺寸优化及误差分析

2018 11th Biomedical Engineering International Conference (BMEiCON) Pub Date : 2018-11-01 DOI: 10.1109/BMEICON.2018.8609995

Li Jiajie, S. Hu, Yang Lin

引用次数: 3

Exoskeleton Suit Supports the Movement 外骨骼套装支持运动

2018 11th Biomedical Engineering International Conference (BMEiCON) Pub Date : 2018-11-01 DOI: 10.1109/BMEICON.2018.8609990

Parkbhum Reanaree, C. Pintavirooj

{"title":"Exoskeleton Suit Supports the Movement","authors":"Parkbhum Reanaree, C. Pintavirooj","doi":"10.1109/BMEICON.2018.8609990","DOIUrl":"https://doi.org/10.1109/BMEICON.2018.8609990","url":null,"abstract":"Thailand is entering into aging society. Paralysis occurs commonly in this group of people. This is a disease that affects the nervous system, including muscular weakness or Amyo-trophic Lateral Sclerosis (ALS). Patients may not be able to walk or use their lower part of the body. Hence, physical activity is fundamental to human life, if the elders are not able to walk or use some of their body part, their quality of life will be reduce. For this reason, research and development of an equipment to assist physiotherapy rehabilitation or supports the movement of patients has been made. The focus has been drawn to standing and walking, which will result in a better functioning of the patient’s body. This lead to the creation of the prototype exoskeleton suit supporting the body movement. The wearable device consists of a movement mechanism, and a microcontroller-driven system. The development of the device is based on a normal human’s gait. In addition, the prototype has a mechanism for limiting the degree of movement of the joints in the waist and knee, with both mechanical and electrical security. Finally, this device can help the patient’s body stood up and assist the walk, which allowing them to take care of themselves and not rely on the family and society.","PeriodicalId":232271,"journal":{"name":"2018 11th Biomedical Engineering International Conference (BMEiCON)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123892205","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: 1

Measurement System for Detecting Action Potential to Electrical Vagus Nerve Stimulation 迷走神经电刺激动作电位检测系统

2018 11th Biomedical Engineering International Conference (BMEiCON) Pub Date : 2018-11-01 DOI: 10.1109/BMEICON.2018.8609938

Hajime Nakamura, A. Ueno, Masayuki Yagi, Koji Morishita, Y. Otomo

引用次数: 2

Alzheimer’s disease Classification from Brain MRI based on transfer learning from CNN 基于CNN迁移学习的脑MRI阿尔茨海默病分类

2018 11th Biomedical Engineering International Conference (BMEiCON) Pub Date : 2018-11-01 DOI: 10.1109/BMEICON.2018.8609974

Bijen Khagi, Chung-Ghiu Lee, G. Kwon

{"title":"Alzheimer’s disease Classification from Brain MRI based on transfer learning from CNN","authors":"Bijen Khagi, Chung-Ghiu Lee, G. Kwon","doi":"10.1109/BMEICON.2018.8609974","DOIUrl":"https://doi.org/10.1109/BMEICON.2018.8609974","url":null,"abstract":"Various Convolutional Neural Network (CNN) architecture has been proposed for image classification and Object recognition. For the image based classification, it is a complex task for CNN to deal with hundreds of MRI Image slices, each of almost identical nature in a single patient. So, classifying a number of patients as an AD, MCI or NC based on 3D MRI becomes vague technique using 2D CNN architecture. Hence, to address this issue, we have simplified the idea of classifying patients on basis of 3D MRI but acknowledging the 2D features generated from the CNN framework. We present our idea regarding how to obtain 2D features from MRI and transform it to be applicable to classify using machine learning algorithm. Our experiment shows the result of classifying 3 class subjects patients. We employed scratched trained CNN or pretrained Alexnet CNN as generic feature extractor of 2D image which dimensions were reduced using PCA+TSNE, and finally classifying using simple Machine learning algorithm like KNN, Navies Bayes Classifier. Although the result is not so impressive but it definitely shows that this can be better than scratch trained CNN softmax classification based on probability score. The generated feature can be well manipulated and refined for better accuracy, sensitivity, and specificity.","PeriodicalId":232271,"journal":{"name":"2018 11th Biomedical Engineering International Conference (BMEiCON)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131302303","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: 41

Characterizing EMG Signals using Aggregated CENSUS Transform 利用聚合普查变换表征肌电信号

2018 11th Biomedical Engineering International Conference (BMEiCON) Pub Date : 2018-11-01 DOI: 10.1109/BMEICON.2018.8609929

K. Subhash, P. Pournami, P. Joseph

引用次数: 1

Imputation of Missing Diagnosis of Diabetes in an Administrative EMR System 行政电子病历系统中糖尿病漏诊的归算

2018 11th Biomedical Engineering International Conference (BMEiCON) Pub Date : 2018-11-01 DOI: 10.1109/BMEICON.2018.8609956

Debby D. Wang, S. Ng, Siti Nabilah Binte Abdul, Sravan Ramachandran, Srinath Sridharan, Xin Quan Tan

引用次数: 0

Implementation of Asymmetric Kernel Median Filtering for Real-Time Ultrasound Imaging 非对称核中值滤波在实时超声成像中的实现

2018 11th Biomedical Engineering International Conference (BMEiCON) Pub Date : 2018-11-01 DOI: 10.1109/BMEICON.2018.8609959

U. Techavipoo, R. Keinprasit, Warakorn Khamkaew, Prachumpong Dangsakul, P. Thajchayapong, Sarun Angamnuaysiri, D. Worasawate

引用次数: 0

BMEiCON 2018 Index

2018 11th Biomedical Engineering International Conference (BMEiCON) Pub Date : 2018-11-01 DOI: 10.1109/bmeicon.2018.8609968

引用次数: 0

Nanopore-spanning lipid bilayer formed by self-spreading method 采用自扩散法形成纳米跨孔脂质双分子层

2018 11th Biomedical Engineering International Conference (BMEiCON) Pub Date : 2018-11-01 DOI: 10.1109/BMEICON.2018.8609982

Zugui Peng, K. Shimba, Yositaka Miyamoto, T. Yagi

引用次数: 0

Determination of the Mechanical Properties of Aortic Tissue for 3D Printed Surgical Models 3D打印手术模型主动脉组织力学性能的测定

2018 11th Biomedical Engineering International Conference (BMEiCON) Pub Date : 2018-11-01 DOI: 10.1109/BMEICON.2018.8609983

Hannah Riedle, Barbara Mukai, Pirmin Molz, J. Franke

引用次数: 6