2018 IEEE Life Sciences Conference (LSC)最新文献

Muscle Activity Distribution Features Extracted from HD sEMG to Perform Forearm Pattern Recognition 从高清表面肌电信号中提取肌肉活动分布特征进行前臂模式识别

2018 IEEE Life Sciences Conference (LSC) Pub Date : 2018-10-01 DOI: 10.1109/EMBC.2016.7590722

F. Nougarou, Alexandre Campeau-Lecours, R. Islam, Daniel Massicotte, Benoit Gosselin

引用次数: 11

Computer-Aided Diagnosis System for Alzheimer's Disease Using Fuzzy-Possibilistic Tissue Segmentation and SVM Classification 基于模糊可能性组织分割和SVM分类的阿尔茨海默病计算机辅助诊断系统

2018 IEEE Life Sciences Conference (LSC) Pub Date : 2018-10-01 DOI: 10.1109/LSC.2018.8572122

L. Lazli, M. Boukadoum, O. Ait Mohamed

{"title":"Computer-Aided Diagnosis System for Alzheimer's Disease Using Fuzzy-Possibilistic Tissue Segmentation and SVM Classification","authors":"L. Lazli, M. Boukadoum, O. Ait Mohamed","doi":"10.1109/LSC.2018.8572122","DOIUrl":"https://doi.org/10.1109/LSC.2018.8572122","url":null,"abstract":"We describe a computer-aided diagnosis (CAD) system for discriminating patients suffering from Alzheimer's disease (AD) dementia and healthy patients. It is based on: 1) a clustering process to assess white matter, gray matter and cerebrospinal fluid volumes from noisy anatomical magnetic resonance (MR) and functional positron emission tomography (PET) brain images11The MR and PET data used in this work were obtained from the Alzheimer's disease Neuroimaging Initiative (ADNI) database (http://adni.loni.usc.edu/).; 2) a classification process that distinguishes the brain images of normal and AD patients. The clustering stage consists of three steps: First, the fuzzy c-means (FCM) algorithm is used for a fuzzy partition of the initial class centroids. Second, fuzzy tissue maps are computed using a possibilistic C-means (PCM) algorithm that uses the FCM partition to obtain the final image clusters. The final segmentation is then made to delimit the brain tissue volumes. For the classification stage, a support vector machine (SVM) is used with different kernel functions. Validating the proposed CAD system on the MRI and PET images of 45 AD and 50 healthy brains, of subjects aged between 55 and 90 years, shows better sensitivity, specificity and accuracy in comparison to three alternative approaches, namely FCM, PCM and VAF (Voxels-As-Features). The accuracy rates for the noisiest images (20% of noise) were 75% for MRI and 73% for PET scan, compared to 71 % and 70,2%, 68.5% and 67%, and 65 % and 64.7 % with the three other approaches, respectively.","PeriodicalId":254835,"journal":{"name":"2018 IEEE Life Sciences Conference (LSC)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128523803","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: 8

Development and Verification of a Low-Cost Prosthetic Knee Motion Sensor 低成本假体膝关节运动传感器的研制与验证

2018 IEEE Life Sciences Conference (LSC) Pub Date : 2018-10-01 DOI: 10.1109/LSC.2018.8572092

McNiel-Inyani Keri, A. W. Shehata, Quinn A. Boser, A. Vette, Jacqueline S. Hebert

{"title":"Development and Verification of a Low-Cost Prosthetic Knee Motion Sensor","authors":"McNiel-Inyani Keri, A. W. Shehata, Quinn A. Boser, A. Vette, Jacqueline S. Hebert","doi":"10.1109/LSC.2018.8572092","DOIUrl":"https://doi.org/10.1109/LSC.2018.8572092","url":null,"abstract":"Limb amputation affects many individuals across the world, with the majority of amputations occurring in the lower limb. Healthy individuals with intact limbs have biological sensors embedded in their anatomy to interact with the environment and to facilitate stable walking. Lower limb prosthetic users lose these embedded sensors, leading to decreased balance and an increased risk of falling, abnormal gait, and decreased quality of life. Tactile and kinesthetic sensory feedback techniques are being investigated for upper limb prosthetic users and may soon translate to lower limb users. A barrier to implementing these techniques is the lack of adequate instrumentation of lower limb prostheses. The objective of this research was to design and develop a low-cost wireless system, using inertial measurement units, which can detect when a single axis prosthetic knee is in motion. This sensor could be used to communicate the movement of a prosthetic device to actuators responsible for providing feedback to the user. Our results indicate that the device is capable of tracking the onset and termination of movement at normal walking speeds.","PeriodicalId":254835,"journal":{"name":"2018 IEEE Life Sciences Conference (LSC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124333215","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

A Practical Guide to Circuit Selection for Portable Microprocessor-Based, Low Component Count, Near-DC Ammeter for Custom Instruments 实用指南电路选择便携式微处理器为基础，低组件计数，近直流电流表定制仪器

2018 IEEE Life Sciences Conference (LSC) Pub Date : 2018-10-01 DOI: 10.1109/LSC.2018.8572257

Paul E. Stevenson, J. Christen

引用次数: 0

Design of a Smart IoT-Enabled Walker for Deployable Activity and Gait Monitoring 用于可部署活动和步态监测的智能物联网助行器设计

2018 IEEE Life Sciences Conference (LSC) Pub Date : 2018-10-01 DOI: 10.1109/LSC.2018.8572227

S. Gill, Suraj Nssk, N. Seth, E. Scheme

引用次数: 4

EMG Asymmetry Index in Cyclic Movements 循环运动中的肌电不对称指数

2018 IEEE Life Sciences Conference (LSC) Pub Date : 2018-10-01 DOI: 10.1109/LSC.2018.8572041

C. Castagneri, V. Agostini, G. Balestra, M. Knaflitz, M. Carlone, Giuseppe Massazza

引用次数: 4

A Nanosurface Microfluidic Device for Capture and Detection of Bacteria 一种用于细菌捕获和检测的纳米表面微流控装置

2018 IEEE Life Sciences Conference (LSC) Pub Date : 2018-10-01 DOI: 10.1109/LSC.2018.8572083

Tamer AbdEIFatah, M. Jalali, S. Mahshid

引用次数: 2

Deep Learning for Grading Cardiomegaly Severity in Chest X-Rays: An Investigation 深度学习用于胸部x光片中心脏肿大严重程度分级的研究

2018 IEEE Life Sciences Conference (LSC) Pub Date : 2018-10-01 DOI: 10.1109/LSC.2018.8572113

S. Candemir, S. Rajaraman, G. Thoma, Sameer Kiran Antani

引用次数: 25

A Compact Deep Learning Network for Temporal Sleep Stage Classification 一种用于睡眠阶段分类的紧凑深度学习网络

2018 IEEE Life Sciences Conference (LSC) Pub Date : 2018-10-01 DOI: 10.1109/LSC.2018.8572286

A. Vetek, Kiti Müller, H. Lindholm

引用次数: 3

Radiomics to Predict Response to Neoadjuvant Chemotherapy in Rectal Cancer: Influence of Simultaneous Feature Selection and Classifier Optimization 放射组学预测直肠癌新辅助化疗反应:同时特征选择和分类器优化的影响

2018 IEEE Life Sciences Conference (LSC) Pub Date : 2018-10-01 DOI: 10.1109/LSC.2018.8572194

S. Rosati, C. M. Gianfreda, G. Balestra, V. Giannini, S. Mazzetti, D. Regge

引用次数: 12