International Congress on Neurotechnology, Electronics and Informatics最新文献_第5页

Web-enabled Neuron Model Hardware Implementation and Testing 网络神经元模型硬件实现与测试

International Congress on Neurotechnology, Electronics and Informatics Pub Date : 1900-01-01 DOI: 10.5220/0005713001380145

F. Morgan, F. Krewer, F. Callaly, Aedan Coffey, B. M. Ginley

引用次数: 3

CyberBrain - A Preliminary Experience on Non Human Primate 网络大脑——非人类灵长类动物的初步经验

International Congress on Neurotechnology, Electronics and Informatics Pub Date : 1900-01-01 DOI: 10.5220/0005089700940098

Marco Piangerelli, A. Paris, P. Romanelli

引用次数: 0

A Simple and Practical Sensorimotor EEG Device for Recording in Patients with Special Needs 一种简单实用的特殊需要患者感觉运动脑电图记录装置

International Congress on Neurotechnology, Electronics and Informatics Pub Date : 1900-01-01 DOI: 10.5220/0006559100730079

S. Ehrlich, Ana Alves-Pinto, R. Lampe, G. Cheng

{"title":"A Simple and Practical Sensorimotor EEG Device for Recording in Patients with Special Needs","authors":"S. Ehrlich, Ana Alves-Pinto, R. Lampe, G. Cheng","doi":"10.5220/0006559100730079","DOIUrl":"https://doi.org/10.5220/0006559100730079","url":null,"abstract":"In studies involving patients with special needs, the use of electroencephalography (EEG) recordings is among the most delicate measurement modalities. The quietness needed and the long preparation time can be challenging especially in young ages. Furthermore, the invasive appearance of the instrumentation involved is not appealing and can raise distrust in patients. We developed a customized EEG device which adresses these issues by merging commercially available EEG hardware with an unobtrusive headphones design. The resulting device has very short preparation times, non-clinical appearance, and delivers adequate data quality with respect to recording of sensorimotor rhythms. Our device was employed in a study investigating sensorimotorrelated brain activity in adolescents and adults with cerebral palsy (CP) conducted at a day-care center. Experimenters reported convenient data collection and overall acceptance of the system among patients. The changes in sensorimotor rhythms over time during a hand motor task meet the observations described in the literature, supporting the functionality of our EEG device for the assessment of sensorimotor-related measures of brain activity in patients with sensorimotor disorders of neuronal origin.","PeriodicalId":167011,"journal":{"name":"International Congress on Neurotechnology, Electronics and Informatics","volume":"1995 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128098707","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

Semi-Supervised Spiking Neural Network for One-Shot Object Appearance Learning 单次目标外观学习的半监督脉冲神经网络

International Congress on Neurotechnology, Electronics and Informatics Pub Date : 1900-01-01 DOI: 10.5220/0006503300470053

Igor Peric, Robert Hangu, Jacques Kaiser, Stefan Ulbrich, A. Rönnau, Johann Marius Zöllner, R. Dillmann

引用次数: 2

raxDAWN: Circumventing Overfitting of the Adaptive xDAWN 规避自适应xDAWN的过拟合

International Congress on Neurotechnology, Electronics and Informatics Pub Date : 1900-01-01 DOI: 10.5220/0005657500680075

M. M. Krell, Hendrik Wöhrle, A. Seeland

引用次数: 3

An Electro-optical Connectome Prototype for Eight Neuron Representations in FPGA Technology FPGA技术中八个神经元表示的电光连接体原型

International Congress on Neurotechnology, Electronics and Informatics Pub Date : 1900-01-01 DOI: 10.5220/0005712501270132

L. Ferrara, A. Petrushin, A. Blau

引用次数: 2

Preliminary Study to Detect Gait Initiation Intention Through a BCI System 基于脑机接口系统的步态起始意图检测的初步研究

International Congress on Neurotechnology, Electronics and Informatics Pub Date : 1900-01-01 DOI: 10.5220/0005167800610066

Daniel Planelles, E. Hortal, E. Iáñez, Á. Costa, A. Úbeda, J. Azorín

引用次数: 0

Commonalities of Motor Performance Metrics are Revealed by Predictive Oscillatory EEG Components 预测振荡脑电分量揭示了运动性能指标的共性

International Congress on Neurotechnology, Electronics and Informatics Pub Date : 1900-01-01 DOI: 10.5220/0005663100320038

M. Tangermann, J. Reis, A. Meinel

{"title":"Commonalities of Motor Performance Metrics are Revealed by Predictive Oscillatory EEG Components","authors":"M. Tangermann, J. Reis, A. Meinel","doi":"10.5220/0005663100320038","DOIUrl":"https://doi.org/10.5220/0005663100320038","url":null,"abstract":"The power of oscillatory components of the electroencephalogram (EEG) can be predictive for the single-trial performance score of an upcoming task. State-of-the-art machine learning methods allow to extract such predictive subspace components even from noisy multichannel EEG recordings. In the context of an isometric hand motor rehabilitation task, we analyse EEG data of n=20 normally aged subjects. Predictive oscillatory EEG subspaces were derived with a spatial filtering method (source power comodulation, SPoC), and the transfer of these subspaces between five performance metrics but within data of single subjects was investigated. Findings suggest, that on the grand average of 20 subjects, informative SPoC subspace components were extracted, which could be shared between a set of three metrics describing the duration of subtasks and jerk characteristics of the force trajectories. Transfer to any other of the remaining four metrics was not possible above chance level for a metric describing the reaction time and a metric assessing the length of the force trajectory. Furthermore we show, that these transfer results are in line with the structure of cross-correlations between the performance metrics.","PeriodicalId":167011,"journal":{"name":"International Congress on Neurotechnology, Electronics and Informatics","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116703167","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: 4

Comparison of Data Selection Strategies for Online Support Vector Machine Classification 支持向量机在线分类的数据选择策略比较

International Congress on Neurotechnology, Electronics and Informatics Pub Date : 1900-01-01 DOI: 10.5220/0005650700590067

M. M. Krell, Nils Wilshusen, A. Ignat, S. K. Kim

{"title":"Comparison of Data Selection Strategies for Online Support Vector Machine Classification","authors":"M. M. Krell, Nils Wilshusen, A. Ignat, S. K. Kim","doi":"10.5220/0005650700590067","DOIUrl":"https://doi.org/10.5220/0005650700590067","url":null,"abstract":"It is often the case that practical applications of support vector machines (SVMs) require the capability to perform online learning under limited availability of computational resources. Enabling SVMs for online learning can be done through several strategies. One group thereof manipulates the training data and limits its size. We aim to summarize these existing approaches and compare them, firstly, on several synthetic datasets with different shifts and, secondly, on electroencephalographic (EEG) data. During the manipulation, class imbalance can occur across the training data and it might even happen that all samples of one class are removed. In order to deal with this potential issue, we suggest and compare three balancing criteria. Results show, that there is a complex interaction between the different groups of selection criteria, which can be combined arbitrarily. For different data shifts, different criteria are appropriate. Adding all samples to the pool of considered samples performs usually significantly worse than other criteria. Balancing the data is helpful for EEG data. For the synthetic data, balancing criteria were mostly relevant when the other criteria were not","PeriodicalId":167011,"journal":{"name":"International Congress on Neurotechnology, Electronics and Informatics","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123655130","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

Application of the Discriminant Analysis for Diagnostics of the Arterial Hypertension - Analysis of Short-Term Heart Rate Variability Signals 判别分析在高血压诊断中的应用——短期心率变异性信号分析

International Congress on Neurotechnology, Electronics and Informatics Pub Date : 1900-01-01 DOI: 10.5220/0006044000450052

V. Kublanov, A. Dolganov, V. Borisov

引用次数: 5