2017 5th International Winter Conference on Brain-Computer Interface (BCI)最新文献

Bimanual Arm Movements Decoding using Hybrid Method 用混合方法解码双手手臂动作

2017 5th International Winter Conference on Brain-Computer Interface (BCI) Pub Date : 2017-02-16 DOI: 10.1109/IWW-BCI.2017.7858159

Hoseok Choi, D. Jang, K. Lee

引用次数: 1

Towards a whole body brain-machine interface system for decoding expressive movement intent Challenges and Opportunities 面向表达性动作意图解码的全身脑机接口系统的挑战与机遇

2017 5th International Winter Conference on Brain-Computer Interface (BCI) Pub Date : 2017-02-16 DOI: 10.1109/IWW-BCI.2017.7858142

J. Contreras-Vidal, Jesus G. Cruz-Garza, Anastasiya E. Kopteva

{"title":"Towards a whole body brain-machine interface system for decoding expressive movement intent Challenges and Opportunities","authors":"J. Contreras-Vidal, Jesus G. Cruz-Garza, Anastasiya E. Kopteva","doi":"10.1109/IWW-BCI.2017.7858142","DOIUrl":"https://doi.org/10.1109/IWW-BCI.2017.7858142","url":null,"abstract":"The restoration and rehabilitation of human bipedal locomotion represent major goals for brain machine interfaces (BMIs), i.e., devices that translate neural activity into motor commands to control wearable robots to enable locomotive and non-locomotive tasks by individuals with gait disabilities. Prior BMI efforts based on scalp electroencephalography (EEG) have revealed that fluctuations in the amplitude of slow cortical potentials in the delta band contain information that can be used to infer motor intent, and more specifically, the kinematics of walking and non-locomotive tasks such as sitting and standing. However, little is known about the extent to which EEG can be used to discern the expressive qualities that influence such functional movements. Here, we discuss how novel experimental approaches integrated with machine learning techniques can deployed to decode expressive qualities of movement. Applications to artistic brain-computer interfaces (BCIs), movement aesthetics, and gait neuroprostheses endowed with expressive qualities are discussed.","PeriodicalId":443427,"journal":{"name":"2017 5th International Winter Conference on Brain-Computer Interface (BCI)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124053911","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

Single-trial analysis of readiness potentials for lower limb exoskeleton control 下肢外骨骼控制准备电位的单次试验分析

2017 5th International Winter Conference on Brain-Computer Interface (BCI) Pub Date : 2017-02-16 DOI: 10.1109/IWW-BCI.2017.7858156

Ji-Hoon Jeong, Min-Ho Lee, No-Sang Kwak, Seong-Whan Lee

{"title":"Single-trial analysis of readiness potentials for lower limb exoskeleton control","authors":"Ji-Hoon Jeong, Min-Ho Lee, No-Sang Kwak, Seong-Whan Lee","doi":"10.1109/IWW-BCI.2017.7858156","DOIUrl":"https://doi.org/10.1109/IWW-BCI.2017.7858156","url":null,"abstract":"Bran-machine interface (BMI) can be used for controlling of external devices such as the exoskeleton, robot arm, etc. For efficient communication between a user and machine, fast and accurate detection of user intention is important elements in the BMI application. For this reason, readiness potential (RP) is a useful feature that is possible to detect movement intention before the movement onset. To our knowledge, however, the analysis of single-trial RP component has not been sufficiently investigated in the real-world application (e.g. powered exoskeleton or robot arm). In our study, we first validate a single-trial RP performance in the lower limb exoskeleton environment where the user allows for voluntary walking. The experiments are executed in the two different walking conditions which are normal and exoskeleton walking. The Laplacian and common average reference (CAR) filters are applied to reduce spatial noise and regularized linear discriminant analysis (RLDA) is used as a classifier. Our results show the averaged classification accuracy of 80.7% for 5 subjects. This study demonstrates a feasibility of RP-based BMI system for controlling of a lower limb exoskeleton.","PeriodicalId":443427,"journal":{"name":"2017 5th International Winter Conference on Brain-Computer Interface (BCI)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115548052","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: 13

A brain-computer interface speller using peripheral stimulus-based SSVEP and P300 使用基于外围刺激的SSVEP和P300的脑机接口拼写器

2017 5th International Winter Conference on Brain-Computer Interface (BCI) Pub Date : 2017-02-16 DOI: 10.1109/IWW-BCI.2017.7858164

J. Hwang, Min-Ho Lee, Seong-Whan Lee

引用次数: 13

Design and evaluation of a P300-ERP based BCI system for real-time control of a mobile robot 基于P300-ERP的移动机器人BCI实时控制系统的设计与评价

2017 5th International Winter Conference on Brain-Computer Interface (BCI) Pub Date : 2017-02-16 DOI: 10.1109/IWW-BCI.2017.7858177

Damir Nurseitov, Abzal Serekov, A. Shintemirov, B. Abibullaev

引用次数: 21

Pop or not? EEG correlates of risk-taking behavior in the balloon analogue risk task 流行与否?脑电与气球模拟风险任务中冒险行为的相关性

2017 5th International Winter Conference on Brain-Computer Interface (BCI) Pub Date : 2017-01-01 DOI: 10.1109/IWW-BCI.2017.7858146

Yiyu Chen, C. Wallraven

引用次数: 4

Learning suite of kernel feature spaces enhances SMR-based EEG-BCI classification 核特征空间学习套件增强了基于smr的EEG-BCI分类

2017 5th International Winter Conference on Brain-Computer Interface (BCI) Pub Date : 1900-01-01 DOI: 10.1109/IWW-BCI.2017.7858158

B. Abibullaev

{"title":"Learning suite of kernel feature spaces enhances SMR-based EEG-BCI classification","authors":"B. Abibullaev","doi":"10.1109/IWW-BCI.2017.7858158","DOIUrl":"https://doi.org/10.1109/IWW-BCI.2017.7858158","url":null,"abstract":"Brain-Computer Interface (BCI) research hopes to improve the quality of life for people with severe motor disabilities by providing a capability to control external devices using their thoughts. To control a device through BCI, neural signals of a user must be translated to meaningful control commands using various machine learning components, e.g. feature extraction, dimensionality reduction and classification, that should also be carefully designed for practical use. However, the noise and variability in the neural data pose one of the greatest challenges that in practice previously functioning BCI fails in the subsequent operation requiring re-tuning/optimization. This paper presents an idea of defining multiple feature spaces and optimal decision boundaries therein to account for noise and variability in data and improve a generalization of a learning machine. The spaces are defined in the Reproducing Kernel Hilbert Spaces induced by a Radial Basis Gaussian function. Then the learning is done via L1-regularized Support Vector Machines. The central idea behind our approach is that a classifier predicts an unseen test examples by learning more rich feature spaces with a suite of optimal hyperparameters. Empirical evaluation have shown an improved generalization performance (range 79–90%) on two class motor imagery Electroencephalography (EEG) data, when compared with other conventional machine learning methods.","PeriodicalId":443427,"journal":{"name":"2017 5th International Winter Conference on Brain-Computer Interface (BCI)","volume":"131 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":"114663090","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: 5

English ability score prediction algorithm based on prefrontal cortex blood volume utilizing a regulated linear regression model 基于调节线性回归模型的前额皮质血容量英语能力评分预测算法

2017 5th International Winter Conference on Brain-Computer Interface (BCI) Pub Date : 1900-01-01 DOI: 10.1109/IWW-BCI.2017.7858147

Kosho Oki, Y. Kurihara, T. Kaburagi, K. Shiba

引用次数: 0

Multimodal integration, attention and sensory augmentation? 多模态整合、注意力和感官增强?

2017 5th International Winter Conference on Brain-Computer Interface (BCI) Pub Date : 1900-01-01 DOI: 10.1109/IWW-BCI.2017.7858148

Basil Wahn, P. König

{"title":"Multimodal integration, attention and sensory augmentation?","authors":"Basil Wahn, P. König","doi":"10.1109/IWW-BCI.2017.7858148","DOIUrl":"https://doi.org/10.1109/IWW-BCI.2017.7858148","url":null,"abstract":"Human information processing is limited in capacity. Here, we investigated under which circumstances humans can better process information if they receive task-relevant sensory input via several sensory modalities compared to only one sensory modality (i.e., vision). We found that the benefits of distributing information processing across sensory modalities critically depend on task demands. That is, when information processing requires only spatial processing, distributing information processing across several sensory modalities does not lead to any performance benefits in comparison to receiving the same information only via the visual sensory modality. When information processing additionally involves the discrimination of stimulus attributes, then distributing information processing across several sensory modalities effectively circumvents processing limitations within the visual modality. Crucially, these performance benefits generalize to settings using sensory augmentation as well as a collaborative setting. Findings are potentially applicable to visually taxing real-world tasks that are either performed alone or in a group.","PeriodicalId":443427,"journal":{"name":"2017 5th International Winter Conference on Brain-Computer Interface (BCI)","volume":"34 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":"128204970","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

Detecting and tracking multiple directional movements in EEG based BCI 基于脑机接口的多方向运动检测与跟踪

2017 5th International Winter Conference on Brain-Computer Interface (BCI) Pub Date : 1900-01-01 DOI: 10.1109/IWW-BCI.2017.7858154

Cuntai Guan, Neethu Robinson, Vikram Shenoy Handiru, V. Prasad

引用次数: 3