• Complex
  • Title
  • Author
  • Keyword
  • Abstract
  • Scholars
High Impact Results & Cited Count Trend for Year Keyword Cloud and Partner Relationship

Query:

学者姓名:徐光华

Refining:

Source

Submit Unfold

Co-Author

Submit Unfold

Language

Submit

Clean All

Export Sort by:
Default
  • Default
  • Title
  • Year
  • WOS Cited Count
  • Impact factor
  • Ascending
  • Descending
< Page ,Total 20 >
Detection of weak transient signals based on unsupervised learning for bearing fault diagnosis EI SCIE Scopus
期刊论文 | 2018 , 314 , 445-457 | NEUROCOMPUTING
Abstract&Keyword Cite

Abstract :

Transient impulse contains abundant information of bearings status. When fault occurs, it is activated and would recur periodically or quasi-periodically. Its period can indicate where defects lie in. However, transient impulse is easily swallowed by background noise or interferences in part or in whole, especially at early stage of fault. This problem brings hard obstacles into faults detection. Considering that transient impulses are periodical or quasi-periodical and vibration signal has local similarity, the single transient impulse can be seen as one of shift-invariant features. In view of this, this paper derives adaptive and non-linear signal decomposition formulas and further proposes adaptive and unsupervised feature learning method by using convolutional restricted Boltzmann machine model. With respecting local waveform structures, this method can automatically capture shift-invariant patterns hidden in original signal and decompose the original signal into several sub-components at the cost of minimizing reconstruction error. Among these sub-components, the fault-related information, i.e., transient impulses signal, could be extracted likely. It provides a promising idea for intelligent signal processing by using unsupervised learning. Afterwards, Maximizing kurtosis is applied to select optimally latent fault component. Two real bearing experiments validate this method is effective and reliable in extraction of weak transient impulses. (C) 2018 Elsevier B.V. All rights reserved.

Keyword :

Signal decomposition Bearing fault detection Unsupervised deep learning Convolutional restricted Boltzmann machine Shift-invariant feature learning

Cite:

Copy from the list or Export to your reference management。

GB/T 7714 Chen, Longting , Xu, Guanghua , Wang, Yi et al. Detection of weak transient signals based on unsupervised learning for bearing fault diagnosis [J]. | NEUROCOMPUTING , 2018 , 314 : 445-457 .
MLA Chen, Longting et al. "Detection of weak transient signals based on unsupervised learning for bearing fault diagnosis" . | NEUROCOMPUTING 314 (2018) : 445-457 .
APA Chen, Longting , Xu, Guanghua , Wang, Yi , Wang, Jianhua . Detection of weak transient signals based on unsupervised learning for bearing fault diagnosis . | NEUROCOMPUTING , 2018 , 314 , 445-457 .
Export to NoteExpress RIS BibTex
Pre-Impact Fall Detection Based on a Modified Zero Moment Point Criterion Using Data From Kinect Sensors EI SCIE Scopus
期刊论文 | 2018 , 18 (13) , 5522-5531 | IEEE SENSORS JOURNAL
Abstract&Keyword Cite

Abstract :

Accidental falls have always been a serious problem for the elderly. There is considerable demand for pre-impact fall detection systems with long lead times. According to the zero moment point criterion, the zero moment point should be kept beneath the supporting foot for stability during humanoid robot standing or walking. However, the zero moment point in the human walk does not stay fixed under the supporting foot. In this paper, we define a dynamic supporting area containing both feet and the area between the two feet, and propose a method of fall prediction based on a modified zero moment point criterion using motion-monitoring data from a Kinect sensor. A fall event is predicted if the projection of the zero moment point locates outside of the dynamic supporting area. The proposed method is compared with a method identifying the imbalance state based on a support vector machine classifier. Experimental results show that fall events could be detected with an average lead time of 867.9 ms (SD = 199.2), a sensitivity of 100%, a specificity of 81.3%, a positive predictive value of 87.0%, a negative predictive value of 100%, and an accuracy of 91.7% using the modified zero moment point criterion. The lead time was 571.9 ms (SD = 153.5) and accuracy was 100% for the support vector machine classifier. The modified zero moment point criterion-based method achieved the longest lead time in the pre-impact fall detection.

Keyword :

Kinect Fall prediction home care zero moment point criterion

Cite:

Copy from the list or Export to your reference management。

GB/T 7714 Li, Min , Xu, Guanghua , He, Bo et al. Pre-Impact Fall Detection Based on a Modified Zero Moment Point Criterion Using Data From Kinect Sensors [J]. | IEEE SENSORS JOURNAL , 2018 , 18 (13) : 5522-5531 .
MLA Li, Min et al. "Pre-Impact Fall Detection Based on a Modified Zero Moment Point Criterion Using Data From Kinect Sensors" . | IEEE SENSORS JOURNAL 18 . 13 (2018) : 5522-5531 .
APA Li, Min , Xu, Guanghua , He, Bo , Ma, Xiaolong , Xie, Jun . Pre-Impact Fall Detection Based on a Modified Zero Moment Point Criterion Using Data From Kinect Sensors . | IEEE SENSORS JOURNAL , 2018 , 18 (13) , 5522-5531 .
Export to NoteExpress RIS BibTex
A review: Motor rehabilitation after stroke with control based on human intent EI SSCI SCIE PubMed Scopus
期刊论文 | 2018 , 232 (4) , 344-360 | PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART H-JOURNAL OF ENGINEERING IN MEDICINE
Abstract&Keyword Cite

Abstract :

Strokes are a leading cause of acquired disability worldwide, and there is a significant need for novel interventions and further research to facilitate functional motor recovery in stroke patients. This article reviews motor rehabilitation methods for stroke survivors with a focus on rehabilitation controlled by human motor intent. The review begins with the neurodevelopmental principles of motor rehabilitation that provide the neuroscientific basis for intuitively controlled rehabilitation, followed by a review of methods allowing human motor intent detection, biofeedback approaches, and quantitative motor rehabilitation assessment. Challenges for future advances in motor rehabilitation after stroke using intuitively controlled approaches are addressed.

Keyword :

human motor intent Stroke rehabilitation neuroplasticity motor rehabilitation brain-computer interface

Cite:

Copy from the list or Export to your reference management。

GB/T 7714 Li, Min , Xu, Guanghua , Xie, Jun et al. A review: Motor rehabilitation after stroke with control based on human intent [J]. | PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART H-JOURNAL OF ENGINEERING IN MEDICINE , 2018 , 232 (4) : 344-360 .
MLA Li, Min et al. "A review: Motor rehabilitation after stroke with control based on human intent" . | PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART H-JOURNAL OF ENGINEERING IN MEDICINE 232 . 4 (2018) : 344-360 .
APA Li, Min , Xu, Guanghua , Xie, Jun , Chen, Chaoyang . A review: Motor rehabilitation after stroke with control based on human intent . | PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART H-JOURNAL OF ENGINEERING IN MEDICINE , 2018 , 232 (4) , 344-360 .
Export to NoteExpress RIS BibTex
Enhanced Plasticity of Human Evoked Potentials by Visual Noise During the Intervention of Steady-State Stimulation Based Brain-Computer Interface EI SCIE
期刊论文 | 2018 , 12 | FRONTIERS IN NEUROROBOTICS
Abstract&Keyword Cite

Abstract :

Neuroplasticity, also known as brain plasticity, is an inclusive term that covers the permanent changes in the brain during the course of an individual's life, and neuroplasticity can be broadly defined as the changes in function or structure of the brain in response to the external and/or internal influences. Long-term potentiation (LTP), a well-characterized form of functional synaptic plasticity, could be influenced by rapid-frequency stimulation (or "tetanus") within in vivo human sensory pathways. Also, stochastic resonance (SR) has brought new insight into the field of visual processing for the study of neuroplasticity. In the present study, a brain-computer interface (BCI) intervention based on rapid and repetitive motion-reversal visual stimulation (i.e., a "tetanizing" stimulation) associated with spatiotemporal visual noise was implemented. The goal was to explore the possibility that the induction of LTP-like plasticity in the visual cortex may be enhanced by the SR formalism via changes in the amplitude of visual evoked potentials (VEPs) measured non-invasively from the scalp of healthy subjects. Changes in the absolute amplitude of P1 and N1 components of the transient VEPs during the initial presentation of the steady-state stimulation were used to evaluate the LIP-like plasticity between the non-noise and noise-tagged BCI interventions. We have shown that after adding a moderate visual noise to the rapid-frequency visual stimulation, the degree of the N1 negativity was potentiated following an similar to 40-min noise-tagged visual tetani. This finding demonstrated that the SR mechanism could enhance the plasticity-like changes in the human visual cortex.

Keyword :

motion-reversal stimulation visual noise plasticity brain-computer interface (BCI) visual evoked potential (VEP)

Cite:

Copy from the list or Export to your reference management。

GB/T 7714 Xie, Jun , Xu, Guanghua , Zhao, Xingang et al. Enhanced Plasticity of Human Evoked Potentials by Visual Noise During the Intervention of Steady-State Stimulation Based Brain-Computer Interface [J]. | FRONTIERS IN NEUROROBOTICS , 2018 , 12 .
MLA Xie, Jun et al. "Enhanced Plasticity of Human Evoked Potentials by Visual Noise During the Intervention of Steady-State Stimulation Based Brain-Computer Interface" . | FRONTIERS IN NEUROROBOTICS 12 (2018) .
APA Xie, Jun , Xu, Guanghua , Zhao, Xingang , Li, Min , Wang, Jing , Han, Chengcheng et al. Enhanced Plasticity of Human Evoked Potentials by Visual Noise During the Intervention of Steady-State Stimulation Based Brain-Computer Interface . | FRONTIERS IN NEUROROBOTICS , 2018 , 12 .
Export to NoteExpress RIS BibTex
Second harmonic reflection and transmission from primary S0 mode Lamb wave interacting with a localized microscale damage in a plate: A numerical perspective EI SCIE PubMed Scopus
期刊论文 | 2018 , 82 , 57-71 | ULTRASONICS
WoS CC Cited Count: 4
Abstract&Keyword Cite

Abstract :

Second harmonic generation has been widely used in characterizing microstructural changes which are evenly distributed in a whole structure. However, few attention has been paid to evaluating localized micro-scale damages. In this paper, second harmonic reflection and transmission from the primary S0 mode Lamb wave interacting with a localized microstructural damage is numerically discussed. Schematic diagram for deriving fundamental temporal waveform and reconstructing the second harmonic temporal waveform based on Morlet wavelet transform is presented. Second harmonic reflection and transmission from an interface between the zones of linear elastic and nonlinear materials is firstly studied to verify the existence of interfacial nonlinearity. Compositions contributing to second harmonic components in the reflected and transmitted waves are analyzed. Amplitudes of the reflected and transmitted second harmonic components generated at an interface due to the interfacial nonlinearity are quantitatively evaluated. Then, second harmonic reflection and transmission from a localized microscale damage is investigated. The effects of the length and width of a microscale damage on WCPA (wavelet coefficient profile area) of the reflected and transmitted second harmonic components are studied respectively. It is found that the second harmonic component in the reflected waves mainly reflects the interfacial nonlinearity while second harmonic in the transmitted waves reflects the material nonlinearity. These findings provide some basis on using second harmonic generation for characterization and detection of localized microstructural changes. (C) 2017 Elsevier B.V. All rights reserved.

Keyword :

Transmission S0 mode Lamb waves Reflection Second harmonic Localized microscale damage

Cite:

Copy from the list or Export to your reference management。

GB/T 7714 Wan, Xiang , Tse, Peter W. , Chen, Jingming et al. Second harmonic reflection and transmission from primary S0 mode Lamb wave interacting with a localized microscale damage in a plate: A numerical perspective [J]. | ULTRASONICS , 2018 , 82 : 57-71 .
MLA Wan, Xiang et al. "Second harmonic reflection and transmission from primary S0 mode Lamb wave interacting with a localized microscale damage in a plate: A numerical perspective" . | ULTRASONICS 82 (2018) : 57-71 .
APA Wan, Xiang , Tse, Peter W. , Chen, Jingming , Xu, Guanghua , Zhang, Qing . Second harmonic reflection and transmission from primary S0 mode Lamb wave interacting with a localized microscale damage in a plate: A numerical perspective . | ULTRASONICS , 2018 , 82 , 57-71 .
Export to NoteExpress RIS BibTex
Comparison of Visual Cortex Functional Connectivity Patterns Based on Steady-state Monochromatic Flicker and Oscillating Checkerboard Visual Stimulus CPCI-S
会议论文 | 2018 , 732-736 | 15th International Conference on Ubiquitous Robots (UR)
Abstract&Keyword Cite

Abstract :

Steady-state visual evoked potential (SSVEP) and steady-state motion visual evoked potential (SSMVEP) are commonly implemented in brain computer interfaces (BCIs). The primary visual system is believed to consist of two pathways: a ventral pathway involved with conscious perception and a dorsal pathway for moving visual information processing. In this paper, as monochromatic flicker and oscillating checkerboard served as distinct stimuli for the elicit of SSVEP and SSMVEP respectively, we investigated functional connectivity patterns of SSVEP and SSMVEP by applying directed transfer function (DTF) to electroencephalography (EEG) signals. The value of flow gain, which is defined as the ratio of outflow to inflow of information flows in one channel, was used to measure the activating level of specific brain region in the information transmission process. We found that the occipital region was strongly activated by flicker stimulation whereas the strongest response of oscillating checkerboard was in the middle temporal visual region. Owing to the difference of activating area, fourteen-channel canonical correlation analysis (CCA) was also applied to compare the recognition accuracy. Results indicated that, due to the wider area activated by oscillating checkerboard, it achieved a higher recognition performance with short response time when compared to monochromatic flicker.

Cite:

Copy from the list or Export to your reference management。

GB/T 7714 Han, XingLiang , Xie, Jun , Luo, AiLing et al. Comparison of Visual Cortex Functional Connectivity Patterns Based on Steady-state Monochromatic Flicker and Oscillating Checkerboard Visual Stimulus [C] . 2018 : 732-736 .
MLA Han, XingLiang et al. "Comparison of Visual Cortex Functional Connectivity Patterns Based on Steady-state Monochromatic Flicker and Oscillating Checkerboard Visual Stimulus" . (2018) : 732-736 .
APA Han, XingLiang , Xie, Jun , Luo, AiLing , Xu, GuangHua , Zhang, XiaoDong , Wang, Jing et al. Comparison of Visual Cortex Functional Connectivity Patterns Based on Steady-state Monochromatic Flicker and Oscillating Checkerboard Visual Stimulus . (2018) : 732-736 .
Export to NoteExpress RIS BibTex
The Role of Visual Noise in Influencing Mental Load and Fatigue in a Steady-State Motion Visual Evoked Potential-Based Brain-Computer Interface EI SSCI SCIE PubMed Scopus
期刊论文 | 2017 , 17 (8) | SENSORS | IF: 2.475
WoS CC Cited Count: 1
Abstract&Keyword Cite

Abstract :

As a spatial selective attention-based brain-computer interface (BCI) paradigm, steady-state visual evoked potential (SSVEP) BCI has the advantages of high information transfer rate, high tolerance to artifacts, and robust performance across users. However, its benefits come at the cost of mental load and fatigue occurring in the concentration on the visual stimuli. Noise, as a ubiquitous random perturbation with the power of randomness, may be exploited by the human visual system to enhance higher-level brain functions. In this study, a novel steady-state motion visual evoked potential (SSMVEP, i.e., one kind of SSVEP)-based BCI paradigm with spatiotemporal visual noise was used to investigate the influence of noise on the compensation of mental load and fatigue deterioration during prolonged attention tasks. Changes in alpha, theta, theta + alpha powers, theta/alpha ratio, and electroencephalography (EEG) properties of amplitude, signal-to-noise ratio (SNR), and online accuracy, were used to evaluate mental load and fatigue. We showed that presenting a moderate visual noise to participants could reliably alleviate the mental load and fatigue during online operation of visual BCI that places demands on the attentional processes. This demonstrated that noise could provide a superior solution to the implementation of visual attention controlling-based BCI applications.

Keyword :

steady-state motion visual evoked potential (SSMVEP) steady-state visual evoked potential (SSVEP) visual noise mental load fatigue brain-computer interface

Cite:

Copy from the list or Export to your reference management。

GB/T 7714 Xie, Jun , Xu, Guanghua , Luo, Ailing et al. The Role of Visual Noise in Influencing Mental Load and Fatigue in a Steady-State Motion Visual Evoked Potential-Based Brain-Computer Interface [J]. | SENSORS , 2017 , 17 (8) .
MLA Xie, Jun et al. "The Role of Visual Noise in Influencing Mental Load and Fatigue in a Steady-State Motion Visual Evoked Potential-Based Brain-Computer Interface" . | SENSORS 17 . 8 (2017) .
APA Xie, Jun , Xu, Guanghua , Luo, Ailing , Li, Min , Zhang, Sicong , Han, Chengcheng et al. The Role of Visual Noise in Influencing Mental Load and Fatigue in a Steady-State Motion Visual Evoked Potential-Based Brain-Computer Interface . | SENSORS , 2017 , 17 (8) .
Export to NoteExpress RIS BibTex
EEG signal co-channel interference suppression based on image dimensionality reduction and permutation entropy EI SCIE Scopus
期刊论文 | 2017 , 134 , 113-122 | SIGNAL PROCESSING | IF: 3.47
WoS CC Cited Count: 2
Abstract&Keyword Cite

Abstract :

It is well known that electroencephalogram (EEG) signals collected from scalps are highly contaminated by various types of artifacts and background noise. The perturbations induced by artifacts and random noise are particularly difficult to correct because of their high amplitude, wide spectral distribution, and variable topographical distribution. Therefore, de-noising of EEG is a very challenging pre-processing step prior to qualitative or quantitative EEG signal analysis. To address this issue, some de-noising approaches have been proposed for noise suppression. However, most of these methods are only available for multi-electrode EEG signal processing, besides, the co-channel interference are always left unprocessed. Aiming at the obstacles encountered by the conventional approaches in single electrode EEG signal co-channel interference suppression, a method based on time-frequency image dimensionality reduction is proposed in this paper. The innovative idea of the proposed method is that it is applicable for single electrode EEG signal enhancement and the background noise can be suppressed in entire time-frequency space. The proposed method is experimentally validated by a group of real EEG data. The experimental results indicate that the proposed method is effective in EEG single electrode co-channel interference suppression.

Keyword :

Permutation entropy Co-channel interference suppression Electroencephalogram (EEG) Image dimensionality reduction Brain-computer interface (BCI)

Cite:

Copy from the list or Export to your reference management。

GB/T 7714 Wang, Yi , Xu, Guanghua , Zhang, Sicong et al. EEG signal co-channel interference suppression based on image dimensionality reduction and permutation entropy [J]. | SIGNAL PROCESSING , 2017 , 134 : 113-122 .
MLA Wang, Yi et al. "EEG signal co-channel interference suppression based on image dimensionality reduction and permutation entropy" . | SIGNAL PROCESSING 134 (2017) : 113-122 .
APA Wang, Yi , Xu, Guanghua , Zhang, Sicong , Luo, Ailing , Li, Min , Han, Chengcheng . EEG signal co-channel interference suppression based on image dimensionality reduction and permutation entropy . | SIGNAL PROCESSING , 2017 , 134 , 113-122 .
Export to NoteExpress RIS BibTex
Running state detection and performance evaluation method for feed mechanism of numerical control machine EI Scopus
会议论文 | 2017 , 222-226 | 2017 IEEE International Conference on Prognostics and Health Management, ICPHM 2017
Abstract&Keyword Cite

Abstract :

Due to the enclosed construction and real-time servo control, it is difficult to detect and evaluate the running state of numerical control (NC) machine feed mechanism. In this paper, the motor torque, which is provided by open NCs, is used to analyze the operating performance of feed mechanism. The torque data is divided into segments in different feed condition and piecewise resolved into long-term trend and short-term fluctuation by the least square method. Features of trend and fluctuation are used to indicate the operating condition and mechanical performance. The proposed method is evaluated by three typical feed mechanisms, i.e. rack & pinion, ball-screw and ball-screw with balance hydraulic cylinder, in a large scale milling and boring machine. Results show that the running state of feed mechanisms can be effectively evaluated and some installed and structural defects are well identified. © 2017 IEEE.

Keyword :

Feed mechanisms Hydraulic cylinders Least square methods Mechanical performance Numerical control machines Operating performance Performance evaluations State Detection

Cite:

Copy from the list or Export to your reference management。

GB/T 7714 Zhang, Xun , Zhang, Qing , Tan, Luyao et al. Running state detection and performance evaluation method for feed mechanism of numerical control machine [C] . 2017 : 222-226 .
MLA Zhang, Xun et al. "Running state detection and performance evaluation method for feed mechanism of numerical control machine" . (2017) : 222-226 .
APA Zhang, Xun , Zhang, Qing , Tan, Luyao , Xu, Guanghua . Running state detection and performance evaluation method for feed mechanism of numerical control machine . (2017) : 222-226 .
Export to NoteExpress RIS BibTex
Classification of single-trial motor imagery EEG by complexity regularization EI Scopus
期刊论文 | 2017 , 1-7 | Neural Computing and Applications | IF: 4.213
Abstract&Keyword Cite

Abstract :

Brain computer interface based on electroencephalogram is a popular way to enable communication between brain and output devices helping elderly and disabled people and in rehabilitation. In practice, the effectiveness of brain computer interface has a strong relationship with the classification accuracy of single trials. Common spatial pattern is believed to be an effective algorithm for classifying the single-trial brain signal. Since it is based on the characteristics of a broad frequency band which is manually selected and not individual variability, it is sensitive to noise and individual variability. In this paper, the common spatial pattern was extended in order to improve classification accuracies and to mitigate these influences. The channel-specific complexity weights of characteristic on montage were derived and added to improve the effects of the relevant function area and the separability between classes. The proposed method was evaluated using two public datasets, and achieved an average accuracy of 18.4% higher than conventional common spatial pattern, and the performance of the proposed method over conventional common spatial pattern was significant (p < 0.05). It indicates that the proposed method extracts subject-specific characteristics and outperforms the conventional common spatial pattern in single-trial EEG classification. © 2017 The Natural Computing Applications Forum

Keyword :

Classification accuracy Common spatial patterns Complexity Complexity regularizations Individual variability Motor imagery Separability between class Single-trial EEG

Cite:

Copy from the list or Export to your reference management。

GB/T 7714 Li, Lili , Xu, Guanghua , Xie, Jun et al. Classification of single-trial motor imagery EEG by complexity regularization [J]. | Neural Computing and Applications , 2017 : 1-7 .
MLA Li, Lili et al. "Classification of single-trial motor imagery EEG by complexity regularization" . | Neural Computing and Applications (2017) : 1-7 .
APA Li, Lili , Xu, Guanghua , Xie, Jun , Li, Min . Classification of single-trial motor imagery EEG by complexity regularization . | Neural Computing and Applications , 2017 , 1-7 .
Export to NoteExpress RIS BibTex
10| 20| 50 per page
< Page ,Total 20 >

Export

Results:

Selected

to

Format:
FAQ| About| Online/Total:3505/50772684
Address:XI'AN JIAOTONG UNIVERSITY LIBRARY(No.28, Xianning West Road, Xi'an, Shaanxi Post Code:710049) Contact Us:029-82667865
Copyright:XI'AN JIAOTONG UNIVERSITY LIBRARY Technical Support:Beijing Aegean Software Co., Ltd.