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学者姓名:徐光华

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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
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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

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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 .
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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
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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

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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 .
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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
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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

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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 .
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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
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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

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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 .
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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
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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

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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) .
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Evaluation of stiffness feedback for hard nodule identification on a phantom silicone model SCIE PubMed Scopus
期刊论文 | 2017 , 12 (3) | PLOS ONE | IF: 2.766
WoS CC Cited Count: 2
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Abstract :

Haptic information in robotic surgery can significantly improve clinical outcomes and help detect hard soft-tissue inclusions that indicate potential abnormalities. Visual representation of tissue stiffness information is a cost-effective technique. Meanwhile, direct force feedback, although considerably more expensive than visual representation, is an intuitive method of conveying information regarding tissue stiffness to surgeons. In this study, real-time visual stiffness feedback by sliding indentation palpation is proposed, validated, and compared with force feedback involving human subjects. In an experimental tele-manipulation environment, a dynamically updated color map depicting the stiffness of probed soft tissue is presented via a graphical interface. The force feedback is provided, aided by a master haptic device. The haptic device uses data acquired from an F/T sensor attached to the end-effector of a tele-manipulated robot. Hard nodule detection performance is evaluated for 2 modes (force feedback and visual stiffness feedback) of stiffness feedback on an artificial organ containing buried stiff nodules. From this artificial organ, a virtual-environment tissue model is generated based on sliding indentation measurements. Employing this virtual-environment tissue model, we compare the performance of human participants in distinguishing differently sized hard nodules by force feedback and visual stiffness feedback. Results indicate that the proposed distributed visual representation of tissue stiffness can be used effectively for hard nodule identification. The representation can also be used as a sufficient substitute for force feedback in tissue palpation.

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GB/T 7714 Li, Min , Konstantinova, Jelizaveta , Xu, Guanghua et al. Evaluation of stiffness feedback for hard nodule identification on a phantom silicone model [J]. | PLOS ONE , 2017 , 12 (3) .
MLA Li, Min et al. "Evaluation of stiffness feedback for hard nodule identification on a phantom silicone model" . | PLOS ONE 12 . 3 (2017) .
APA Li, Min , Konstantinova, Jelizaveta , Xu, Guanghua , He, Bo , Aminzadeh, Vahid , Xie, Jun et al. Evaluation of stiffness feedback for hard nodule identification on a phantom silicone model . | PLOS ONE , 2017 , 12 (3) .
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Steady-State Motion Visual Evoked Potential (SSMVEP) Based on Equal Luminance Colored Enhancement SCIE PubMed Scopus
期刊论文 | 2017 , 12 (1) | PLOS ONE | IF: 2.766
WoS CC Cited Count: 1
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Steady-state visual evoked potential (SSVEP) is one of the typical stimulation paradigms of brain-computer interface (BCI). It has become a research approach to improve the performance of human-computer interaction, because of its advantages including multiple objectives, less recording electrodes for electroencephalogram (EEG) signals, and strong anti-interference capacity. Traditional SSVEP using light flicker stimulation may cause visual fatigue with a consequent reduction of recognition accuracy. To avoid the negative impacts on the brain response caused by prolonged strong visual stimulation for SSVEP, steadystate motion visual evoked potential (SSMVEP) stimulation method was used in this study by an equal-luminance colored ring-shaped checkerboard paradigm. The movement patterns of the checkerboard included contraction and expansion, which produced less discomfort to subjects. Feature recognition algorithms based on power spectrum density (PSD) peak was used to identify the peak frequency on PSD in response to visual stimuli. Results demonstrated that the equal-luminance red-green stimulating paradigm within the low frequency spectrum (lower than 15 Hz) produced higher power of SSMVEP and recognition accuracy than black-white stimulating paradigm. PSD-based SSMVEP recognition accuracy was 88.15 +/- 6.56%. There was no statistical difference between canonical correlation analysis (CCA) (86.57 +/- 5.37%) and PSD on recognition accuracy. This study demonstrated that equal-luminance colored ring-shaped checkerboard visual stimulation evoked SSMVEP with better SNR on low frequency spectrum of power density and improved the interactive performance of BCI.

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GB/T 7714 Yan, Wenqiang , Xu, Guanghua , Li, Min et al. Steady-State Motion Visual Evoked Potential (SSMVEP) Based on Equal Luminance Colored Enhancement [J]. | PLOS ONE , 2017 , 12 (1) .
MLA Yan, Wenqiang et al. "Steady-State Motion Visual Evoked Potential (SSMVEP) Based on Equal Luminance Colored Enhancement" . | PLOS ONE 12 . 1 (2017) .
APA Yan, Wenqiang , Xu, Guanghua , Li, Min , Xie, Jun , Han, Chengcheng , Zhang, Sicong et al. Steady-State Motion Visual Evoked Potential (SSMVEP) Based on Equal Luminance Colored Enhancement . | PLOS ONE , 2017 , 12 (1) .
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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
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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)

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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 .
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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
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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

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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 .
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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
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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

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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 .
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