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Causal neurofeedback based BCI-FES rehabilitation for post-stroke patients

Causal neurofeedback based BCI-FES rehabilitation for post-s...

引用

20th International Conference on Neural Information Processing, ICONIP 2013

作者： Wang, Hang Liu, Ye Zhang, Hao Li, Junhua Zhang, Liqing MOE-Microsoft Key Laboratory for Intelligent Computing and Intelligent Systems Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai 200240 China

ISBN: (纸本)9783642420535

BCI-FES therapy has been proved to be an effective way to help post-stroke patients restore motor function of paralyzed limbs. In the existing BCI-FES system, patients can only asynchronously receive feedback in the form of FES or robot-assisted arm movements, and such a system does not provide a positive feedback corresponding to patient's motor imagery. In this work, we propose a causal related BCI-FES rehabilitation training platform, consisting top-down and bottom-up causal chains to achieve a better rehabilitation performance. We compare our system with a popular BCI-FES system on EEG data recorded from ten patients divided in two groups. The results show that almost all patients have achieved improvements in the motor function recovery after our training. © Springer-Verlag 2013.

关键词： Patient treatment

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A frequency boosting method for motor imagery EEG classification in BCI-FES rehabilitation training system

A frequency boosting method for motor imagery EEG classifica...

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10th International Symposium on Neural Networks, ISNN 2013

作者： Liang, Jianyi Zhang, Hao Liu, Ye Wang, Hang Li, Junhua Zhang, Liqing MOE-Microsoft Key Laboratory for Intelligent Computing and Intelligent Systems Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai 200240 China

ISBN: (纸本)9783642390678

Common Spatial Pattern (CSP) and Support Vector Machine (SVM) are usually adopted for feature extraction and classification of two-class motor imagery. However, in a motor imagery based BCI-FES rehabilitation system, stroke patients usually are not able to conduct correct motor imagery like healthy people due to the injury of motor cortex. Therefore, motor imagery EEG of stroke patients lacks of specific discriminant features as appearances of healthy people, which significantly blocks CSP to seek the optimal projection subspace. In this paper, a method, which filters EEG into a variety of bands and improves performance through boosting principle based on a set of weak CSP-SVM classifiers, was proposed to solve the problem mentioned above and was evaluated on the EEG datasets of three stroke subjects. The proposed method outperformed the traditional CSP-SVM method in terms of classification accuracy. From data analysis, we observed that optimal spectral band for classification had been changing along with rehabilitation training, which may reveal mechanisms that dominant frequency band may be changed along with rehabilitation training and spectral power distribution may be changed in different stages of rehabilitation. In addition, this work also demonstrated the feasibility of our SJTU-BCMI BCI-FES rehabilitation training system. © 2013 Springer-Verlag Berlin Heidelberg.

关键词： Support vector machines

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Optimal calculation of tensor learning approaches

Optimal calculation of tensor learning approaches

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10th International Symposium on Neural Networks, ISNN 2013

作者： Huang, Kai Zhang, Liqing MOE-Microsoft Key Laboratory for Intelligent Computing and Intelligent Systems Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai 200240 China

ISBN: (纸本)9783642390647

Most algorithms have been extended to the tensor space to create algorithm versions with direct tensor inputs. However, very unfortunately basically all objective functions of algorithms in the tensor space are non-convex. However, sub-problems constructed by fixing all the modes but one are often convex and very easy to solve. However, this method may lead to difficulty converging;iterative algorithms sometimes get stuck in a local minimum and have difficulty converging to the global solution. Here, we propose a computational framework for constrained and unconstrained tensor methods. Using our methods, the algorithm convergence situation can be improved to some extent and better solutions obtained. We applied our technique to Uncorrelated Multilinear Principal Component Analysis (UMPCA), Tensor Rank one Discriminant Analysis (TR1DA) and Support Tensor Machines (STM);Experiment results show the effectiveness of our method. © 2013 Springer-Verlag Berlin Heidelberg.

关键词： Tensors

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Hidden Markov model for action recognition using joint angle acceleration

Hidden Markov model for action recognition using joint angle...

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20th International Conference on Neural Information Processing, ICONIP 2013

作者： Huang, Sha Zhang, Liqing MOE-Microsoft Key Laboratory for Intelligent Computing and Intelligent Systems Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai 200240 China

ISBN: (纸本)9783642420504

This paper proposes a recognition method of human actions in video by adding new features, the joint angle acceleration to the feature space. In this method, human body is described as three-dimensional skeletons. The features consist of vectors of several important joint angles on the human body and the joint angle accelerations are also considered as a part of features. Hidden Markov Model (HMM) is used as classification scheme. The HMM models are trained by sequences extracted from the CMU graphics lab motion capture database 1. This method is invariant to scale, coordinate system and transition. A system is implemented to recognize 4 different types of actions (walk, run, jump and jumping jack) both on the dataset of CMU and Weizmann[7]. Each video clip contains a single action type. The experimental results show excellent performance of the proposed approach. A maximum 10.3% accuracy gain can be achieved by our method compared with the method without considering acceleration. © Springer-Verlag 2013.

关键词： Hidden Markov models

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UMPCA based feature extraction for ECG

UMPCA based feature extraction for ECG

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10th International Symposium on Neural Networks, ISNN 2013

作者： Li, Dong Huang, Kai Zhang, Hanlin Zhang, Liqing MOE-Microsoft Key Laboratory for Intelligent Computing and Intelligent Systems Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai 200240 China

ISBN: (纸本)9783642390647

In this paper, we propose an algorithm for 12-leads ECG signals feature extraction by Uncorrelated Multilinear Principal Component Analysis(UMPCA). However, traditional algorithms usually base on 2-leads ECG signals and do not efficiently work out for 12-leads signals. Our algorithm aims at the natural 12-leads ECG signals. We firstly do the Short Time Fourier Transformation(STFT) on the raw ECG data and obtain 3rd-order tensors in the spatial-spectral- temporal domain, then take UMPCA to find a Tensor-to-Vector Projection(TVP) for feature extraction. Finally the Support Vector Machine(SVM) classifier is applied to achieve a high accuracy with these features. © 2013 Springer-Verlag Berlin Heidelberg.

关键词： Tensors

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The value-passing calculus

The value-passing calculus

引用

Theories of Programming and Formal Methods: Essays Dedicated to Jifeng He on the Occasion of His 70th Birthday

作者： Fu, Yuxi BASICS Department of Computer Science Shanghai Jiaotong University China MOE-MS Key Laboratory for Intelligent Computing and Intelligent Systems China

ISBN: (纸本)9783642396977

A value-passing calculus is a process calculus in which the contents of communications are values chosen from some data domain, and the propositions appearing in the conditionals are formulas constructed from a logic. Previous studies treat the domain models, as well as the logic theories, as unspecified oracles. The open-ended approach leaves open some fundamental issues unanswered. The paper provides a more formal account of the value-passing calculi. The new treatment is self-contained in that the logic theory a value-passing calculus refers to is formally defined. A value-passing calculus consists of a complete first order theory with an operational model that makes use of the terms and the boolean expressions of the theory. A systematic investigation into the theory of the value-passing calculi is carried out. A particular value-passing calculus, double-struck Vℂ, is shown to be the least expressive among all Turing complete value-passing calculi. © 2013 Springer-Verlag.

关键词： Computer circuits

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Image denoising based on overcomplete topographic sparse coding

Image denoising based on overcomplete topographic sparse cod...

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20th International Conference on Neural Information Processing, ICONIP 2013

作者： Zhao, Haohua Luo, Jun Huang, Zhiheng Nagumo, Takefumi Murayama, Jun Zhang, Liqing MOE-Microsoft Key Laboratory for Intelligent Computing and Intelligent Systems Dep. of Computer Science and Engineering Shanghai Jiao Tong Univ. Shanghai China SONY Corporation Tokyo Japan

ISBN: (纸本)9783642420504

This paper presents a novel image denoising framework using overcomplete topographic model. To adapt to the statistics of natural images, we impose sparseness constraints on the denoising model. Based on the overcomplete topographic model, our denoising system improves over previous work on the following aspects: multi-category based sparse coding, adaptive learning, local normalization, and shrinkage function. A large number of simulations have been performed to show the performance of the modified model, demonstrating that the proposed model achieves better denoising performance. © Springer-Verlag 2013.

关键词： Shrinkage

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Labeled Alignment for Recognizing Textual Entailment 6

Labeled Alignment for Recognizing Textual Entailment

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6th International Joint Conference on Natural Language Processing, IJCNLP 2013

作者： Wang, Xiao-Lin Zhao, Hai Lu, Bao-Liang Center for Brain-Like Computing and Machine Intelligence MOE-Microsoft Key Laboratory for Intelligent Computing and Intelligent Systems Department of Computer Science and Engineering Shanghai Jiao Tong University 800 Dongchuan Road Shanghai 200240 China

ISBN: (纸本)9784990734800

Recognizing Textual Entailment (RTE) is to predict whether one text fragment can semantically infer another, which is required across multiple applications of natural language processing. The conventional alignment scheme, which is developed for machine translation, only marks the paraphrases and hyponyms to justify the entailment pairs, while provides less support for the non-entailment ones. This paper proposes a novel alignment scheme, named labeled alignment, to address this problem, which introduces negative links to explicitly mark the contradictory expressions to justify the non-entailment pairs. Thus the alignment-based RTE method employing the proposed scheme, compared with those employing the conventional one, can gain accuracy improvement through actively detecting the signals of non-entailment. The experimental results on the data sets of two shared RTE tasks indicate the implemented system significantly outperforms both the baseline system and all the other submitted systems. © IJCNLP *** right reserved.

关键词： Alignment

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Grammatical error correction as multiclass classification with single model 17

Grammatical error correction as multiclass classification wi...

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17th Conference on Computational Natural Language Learning: Shared Task, CoNLL 2013

作者： Jia, Zhongye Wang, Peilu Zhao, Hai MOE-Microsoft Key Laboratory for Intelligent Computing and Intelligent Systems Center for Brain-Like Computing and Machine Intelligence Department of Computer Science and Engineering Shanghai Jiao Tong University 800 Dongchuan Road Shanghai200240 China

ISBN: (纸本)9781937284718

This paper describes our system in the shared task of CoNLL-2013. We illustrate that grammatical error detection and correction can be transformed into a multiclass classification task and implemented as a single-model system regardless of various error types with the aid of maximum entropy modeling. Our system achieves the F1 score of 17.13% on the standard test set. © 2013 Association for Computational Linguistics.

关键词： Error correction

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KySS 1.0: a Framework for Automatic Evaluation of Chinese Input Method Engines 6

KySS 1.0: a Framework for Automatic Evaluation of Chinese In...

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6th International Joint Conference on Natural Language Processing, IJCNLP 2013

作者： Jia, Zhongye Zhao, Hai MOE-Microsoft Key Laboratory for Intelligent Computing and Intelligent Systems Center for Brain-Like Computing and Machine Intelligence Department of Computer Science and Engineering Shanghai Jiao Tong University 800 Dongchuan Road Shanghai200240 China

ISBN: (纸本)9784990734800

Chinese Input Method Engine (IME) plays an important role in Chinese language processing. However, it has been subjected to lacking a proper evaluation metric for a long time. The natural metric for IME is user experience, which is a rather vague goal for research purpose. We propose a novel approach of quantifying user experience by using keystroke count and then correspondingly develop a framework of IME evaluation, which is fast and accurate. With the underlying linguistic background, the proposed evaluation framework can properly model the user behavior as Chinese is input through English keyboard. It is helpful to point out a way to improve the current Chinese IME performance. © IJCNLP *** right reserved.

关键词： Engines

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