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< Page ,Total 31 >
A novel detection method for diagnosis of rotor eccentricity in three-phase induction motor EI SCIE
期刊论文 | 2021 , 32 (11) | MEASUREMENT SCIENCE AND TECHNOLOGY
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Abstract :

In this paper, a novel method to diagnose eccentricity fault in rotor of three-phase induction motor based on the current signal, is proposed along with experimental validation. It utilizes three-phase current in time series into Clarks two phase alpha-beta 90 degrees apart vectors assimilating into 0 degrees measuring reference frame starting point with the aid of key-phasor averaging method. alpha-beta sinusoidal waves are applied to an interpolation method which gives an improved Fast Fourier transform of amplitude and phase angle of alpha-beta components. These transformed two-phase current signals are again measured to get amplitude and phase. Finally, the amplitude and phase of alpha-beta are used to generate holo-spectrum with an ellipse of the first order. Since unbalance fault occur at peak fundamental 1X harmonic frequency component, so its amplitude and phase angle are utilized for orbit construction. A comparison is made on rotor orbit and its eccentricity values, constructed from vibration signals and three-phase current signals, both measured simultaneously. This leads to a direct relationship in terms of orbit eccentricity and its longitudinal major axis inclination. The results show that at low frequency the eccentricity values of vibration and current signals orbits coincide hence the unbalance fault is detectable in induction motor by only utilizing the current signals. This method represents rotor non-linear dynamic behavior and is immune to unsymmetrical and anisotropic surface properties of the rotor and can measure rotor condition representing an accurate severity level of air gap eccentricity or, in mechanical terms, rotor unbalance fault. The new technique is a progressive development in induction motor air gap eccentricity fault detection and is applicable to harsh running conditions due to its simplified and non-invasive approach.

Keyword :

severity level measurement three-phase induction motor air gap eccentricity holo spectrum

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GB/T 7714 Khalique, Umair , Xu, Guanghua , Zhang Xining et al. A novel detection method for diagnosis of rotor eccentricity in three-phase induction motor [J]. | MEASUREMENT SCIENCE AND TECHNOLOGY , 2021 , 32 (11) .
MLA Khalique, Umair et al. "A novel detection method for diagnosis of rotor eccentricity in three-phase induction motor" . | MEASUREMENT SCIENCE AND TECHNOLOGY 32 . 11 (2021) .
APA Khalique, Umair , Xu, Guanghua , Zhang Xining , Fei, Liu , Ahmad, Shahzad , Xun, Zhang et al. A novel detection method for diagnosis of rotor eccentricity in three-phase induction motor . | MEASUREMENT SCIENCE AND TECHNOLOGY , 2021 , 32 (11) .
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Measurement and evaluation of cylindricity deviation in Cartesian coordinates EI SCIE Scopus
期刊论文 | 2021 , 32 (3) | MEASUREMENT SCIENCE AND TECHNOLOGY
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Abstract :

In the earlier studies of the Liu et al (2015 Intersecting chord method for minimum zone evaluation of roundness deviation using Cartesian coordinate data Precis. Eng. 42 242-52, 2016 Minimum circumscribed circle and maximum inscribed circle of roundness deviation evaluation with intersecting chord method IEEE Trans. Instrum. Meas. 65 2787-96), the intersecting chords method was proposed for modeling roundness and sphericity deviations. Because cylindricity deviation is partially associated with both deviations, this study focuses on the measurement and evaluation of cylindricity deviations using the intersecting chords method in the Cartesian coordinate system. Combined with the geometric structure of a cylinder, the measurement method of the cylindricity deviation in Cartesian coordinates is introduced, and the cylindricity measurement is conducted by multi-section sampling, axis fitting, and spatial projection. Based on this, the intersecting chords method is employed to construct models for the cylindricity deviation evaluation using the point coordinates obtained from the cylindricity measurements, including minimum circumscribed cylindricity, maximum inscribed cylindricity, and minimum zone cylindricity. The core of the intersecting chords method is using a chord instead of a curve as the characteristic element of the evaluation model. Moreover, the cross structure produced by the intersecting chords can control the position of the reference form and obtain the center of the evaluation model accurately. For the cylindricity deviation, the intersecting chords method not only reduces the modeling difficulty but also improves the evaluation accuracy. Moreover, the availability and validity of the modeling method are further verified by the experimental data obtained from coordinate measuring machines, and the results show that the research study is useful for developing measurement instruments and manufacturing equipment having large cylindrical parts.

Keyword :

intersecting chords form deviation evaluation Cartesian coordinates cylindricity deviation

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GB/T 7714 Liu, Fei , Liang, Lin , Xu, Guanghua et al. Measurement and evaluation of cylindricity deviation in Cartesian coordinates [J]. | MEASUREMENT SCIENCE AND TECHNOLOGY , 2021 , 32 (3) .
MLA Liu, Fei et al. "Measurement and evaluation of cylindricity deviation in Cartesian coordinates" . | MEASUREMENT SCIENCE AND TECHNOLOGY 32 . 3 (2021) .
APA Liu, Fei , Liang, Lin , Xu, Guanghua , Hou, Chenggang , Liu, Dan . Measurement and evaluation of cylindricity deviation in Cartesian coordinates . | MEASUREMENT SCIENCE AND TECHNOLOGY , 2021 , 32 (3) .
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Learning a superficial correlated representation using a local mapping strategy for bearing performance degradation assessment EI SCIE
期刊论文 | 2021 , 32 (6) | Measurement Science and Technology
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Abstract :

As a prime technique for proactive maintenance, bearing performance degradation assessment (PDA), which aims to build a health index (HI) to assess the performance degradation process, has drawn more and more attention in recent years. To construct an HI of high quality, we propose a novel and robust fuzzy c-means (FCM) model, based on locally linear embedding (LLE), that aims to learn a superficial correlated representation using a local mapping strategy. First, a great mass of commonly used features from the time-domain, the frequency-domain, and the time-frequency domain are extracted from the original vibration signature. Features are then implemented to obtain the initial dimensions by maximum likelihood estimation (MLE). Subsequently, local mapping produced by LLE with the initial dimensions extracts the underlying manifold structure from all the remaining features, and a superficial correlated representation is obtained, generated from the space expanded by the features. Finally, an HI based on the subjection of the FCM model is used to assess the bearing degradation process. To validate the superiority of the proposed method, it is compared with three advanced PDA models through experiments on three public datasets. A comparison of the proposed method with those of the other studies confirms the potential of MLE-LLE as an effective feature-fusion tool for the PDA of bearings. © 2021 IOP Publishing Ltd.

Keyword :

Mapping Maximum likelihood estimation Time domain analysis Frequency domain analysis

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GB/T 7714 Kuang, Jiachen , Xu, Guanghua , Zhang, Sicong et al. Learning a superficial correlated representation using a local mapping strategy for bearing performance degradation assessment [J]. | Measurement Science and Technology , 2021 , 32 (6) .
MLA Kuang, Jiachen et al. "Learning a superficial correlated representation using a local mapping strategy for bearing performance degradation assessment" . | Measurement Science and Technology 32 . 6 (2021) .
APA Kuang, Jiachen , Xu, Guanghua , Zhang, Sicong , Wang, Bo . Learning a superficial correlated representation using a local mapping strategy for bearing performance degradation assessment . | Measurement Science and Technology , 2021 , 32 (6) .
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A Convolution Neural Network with Mixed-Size Kernels for Time-Frequency Characteristics of Motor Imagery EI
会议论文 | 2021 , 69-75 | 7th International Conference on Computing and Artificial Intelligence, ICCAI 2021
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As a paradigm of spontaneous Brain-Computer Interface (BCI), motor imagery electroencephalogram (EEG) has always been a hot topic in BCI and clinical rehabilitation. Many algorithms have been proposed for decoding the motor imagery signals. The algorithm based on the convolutional neural network has shown excellent potential in the task of motor imagery signal classification. However, the existing models are not specific to the characteristics of motor imagery signals, and so, they cannot fully extract the signal features of different rhythms. Moreover, limited by difficulties in the acquisition, the classification effect of the model is network based on mixed-size convolution kernel is designed. The time-frequency graph obtained by Short-time Fourier transform (STFT) is used as input, and Deep Convolutional Generative Adversarial Networks (DCGANs) is used for data enhancement. The results show that the average classification accuracy is 85.7%. Compared with current mainstream classification algorithms, the model presented in this paper has shown high classification accuracy and good robustness. © 2021 ACM.

Keyword :

Generative adversarial networks Convolution Biomedical signal processing Convolutional neural networks Brain computer interface Electroencephalography

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GB/T 7714 Tao, Tangfei , Han, Zezhen , Xu, Guanghua et al. A Convolution Neural Network with Mixed-Size Kernels for Time-Frequency Characteristics of Motor Imagery [C] . 2021 : 69-75 .
MLA Tao, Tangfei et al. "A Convolution Neural Network with Mixed-Size Kernels for Time-Frequency Characteristics of Motor Imagery" . (2021) : 69-75 .
APA Tao, Tangfei , Han, Zezhen , Xu, Guanghua , Zhang, Kai . A Convolution Neural Network with Mixed-Size Kernels for Time-Frequency Characteristics of Motor Imagery . (2021) : 69-75 .
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Asynchronous steady-state visual evoked potential brain-computer interface application: True and false positive rate comparison between with and without eye-tracking switch paradigms EI
会议论文 | 2021 , 438-443 | 2021 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2021
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Abstract :

Due to the bypass of muscle activity or peripheral nerve control, brain-computer interface (BCI) technique has advantages in different fields such as medical field for the rehabilitation of paralyzed patients. Steady-state visual evoked potential (SSVEP) has been widely adopted in BCI applications. SSVEP based BCIs have the advantages of high information transfer rate, less or no need of training, and strong anti-interference, which could be used in the more natural asynchronous BCI application with control of the users rather than the operant system of the synchronous mode. In order to solve the problem of high false positive rate (FPR) in common asynchronous SSVEP BCI applications, this paper proposed an eye-tracking switch based BCI paradigm to reduce the FPR and to improve the performance of the asynchronous BCI system. In the proposed paradigm, the fixation point position instead of EEG signal is used to determine whether the system is in idle state. Experimental results showed that when eye-tracking switch was applied in the asynchronous SSVEP BCI, the FPR was reduced to less than 10% and the recognition accuracy (i.e., the true positive rate, TPR) can also be improved to a certain extent, which proved the applicability of the eye-tracking switch in asynchronous BCI applications. © 2021 IEEE.

Keyword :

Patient rehabilitation Interface states Interfaces (computer) Brain computer interface Brain Eye tracking Medical computing

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GB/T 7714 Xie, Jun , Zhang, Huanqing , Liu, Yi et al. Asynchronous steady-state visual evoked potential brain-computer interface application: True and false positive rate comparison between with and without eye-tracking switch paradigms [C] . 2021 : 438-443 .
MLA Xie, Jun et al. "Asynchronous steady-state visual evoked potential brain-computer interface application: True and false positive rate comparison between with and without eye-tracking switch paradigms" . (2021) : 438-443 .
APA Xie, Jun , Zhang, Huanqing , Liu, Yi , Fang, Peng , Yu, Hongwei , He, Liushi et al. Asynchronous steady-state visual evoked potential brain-computer interface application: True and false positive rate comparison between with and without eye-tracking switch paradigms . (2021) : 438-443 .
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A Three-Phase Current Tacholess Envelope Order Analysis Method for Feature Extraction of Planetary Gearbox under Variable Speed Conditions SCIE PubMed
期刊论文 | 2021 , 21 (17) | SENSORS
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Planetary gearboxes are the key components of large equipment, such as wind turbines, shield machines, etc. The operating state of the planetary gearbox is related to the safety of the equipment as a whole, and its feature extraction technology is essential. In assessing the problem of the non-stationarity of the current signal under variable speed conditions and the difficulty of evaluating the operating state of the planetary gearbox under a tacholess condition, a three-phase current, variable-speed tacholess envelope order analysis method is proposed. Firstly, a tacholess rotation speed estimation is completed by extracting the trend term of the instantaneous frequency of the asynchronous motor's three-phase currents. The motor slip rate is assumed to be constant. Then, the envelope order analysis signal is obtained by re-sampling in the angular domain. Finally, the features of the envelope order signal are extracted, and a linear discriminant analysis (LDA) algorithm is used to fuse multiple indexes to generate a comprehensive feature reflecting the operating status of the planetary gearbox. The results of the simulation analysis and experimental verification show that the proposed method is effective in evaluating the operating state of the planetary gearbox under variable speed conditions. Compared with the traditional time-frequency ridge extraction method, the tacholess speed estimation method can improve the instantaneous speed estimation accuracy. The comprehensive index of envelope order completes the planetary gearbox state identification process, and a 95% classification accuracy rate is achieved.

Keyword :

variable speed planetary gearbox tacholess envelope order analysis feature extraction

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GB/T 7714 Zhang, Xun , Xu, Guanghua , Kuang, Jiachen et al. A Three-Phase Current Tacholess Envelope Order Analysis Method for Feature Extraction of Planetary Gearbox under Variable Speed Conditions [J]. | SENSORS , 2021 , 21 (17) .
MLA Zhang, Xun et al. "A Three-Phase Current Tacholess Envelope Order Analysis Method for Feature Extraction of Planetary Gearbox under Variable Speed Conditions" . | SENSORS 21 . 17 (2021) .
APA Zhang, Xun , Xu, Guanghua , Kuang, Jiachen , Suo, Lin , Zhang, Sicong , Khalique, Umair . A Three-Phase Current Tacholess Envelope Order Analysis Method for Feature Extraction of Planetary Gearbox under Variable Speed Conditions . | SENSORS , 2021 , 21 (17) .
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Enhancing Performance of SSVEP-Based Visual Acuity via Spatial Filtering SCIE PubMed
期刊论文 | 2021 , 15 | FRONTIERS IN NEUROSCIENCE
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The purpose of this study was to enhance the performance of steady-state visual evoked potential (SSVEP)-based visual acuity assessment with spatial filtering methods. Using the vertical sinusoidal gratings at six spatial frequency steps as the visual stimuli for 11 subjects, SSVEPs were recorded from six occipital electrodes (O1, Oz, O2, PO3, POz, and PO4). Ten commonly used training-free spatial filtering methods, i.e., native combination (single-electrode), bipolar combination, Laplacian combination, average combination, common average reference (CAR), minimum energy combination (MEC), maximum contrast combination (MCC), canonical correlation analysis (CCA), multivariate synchronization index (MSI), and partial least squares (PLS), were compared for multielectrode signals combination in SSVEP visual acuity assessment by statistical analyses, e.g., Bland-Altman analysis and repeated-measures ANOVA. The SSVEP signal characteristics corresponding to each spatial filtering method were compared, determining the chosen spatial filtering methods of CCA and MSI with a higher performance than the native combination for further signal processing. After the visual acuity threshold estimation criterion, the agreement between the subjective Freiburg Visual Acuity and Contrast Test (FrACT) and SSVEP visual acuity for the native combination (0.253 logMAR), CCA (0.202 logMAR), and MSI (0.208 logMAR) was all good, and the difference between FrACT and SSVEP visual acuity was also all acceptable for the native combination (-0.095 logMAR), CCA (0.039 logMAR), and MSI (-0.080 logMAR), where CCA-based SSVEP visual acuity had the best performance and the native combination had the worst. The study proved that the performance of SSVEP-based visual acuity can be enhanced by spatial filtering methods of CCA and MSI and also recommended CCA as the spatial filtering method for multielectrode signals combination in SSVEP visual acuity assessment.

Keyword :

spatial filtering canonical correlation analysis visual acuity steady-state visual evoked potential multielectrode signals combination

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GB/T 7714 Zheng, Xiaowei , Xu, Guanghua , Han, Chengcheng et al. Enhancing Performance of SSVEP-Based Visual Acuity via Spatial Filtering [J]. | FRONTIERS IN NEUROSCIENCE , 2021 , 15 .
MLA Zheng, Xiaowei et al. "Enhancing Performance of SSVEP-Based Visual Acuity via Spatial Filtering" . | FRONTIERS IN NEUROSCIENCE 15 (2021) .
APA Zheng, Xiaowei , Xu, Guanghua , Han, Chengcheng , Tian, Peiyuan , Zhang, Kai , Liang, Renghao et al. Enhancing Performance of SSVEP-Based Visual Acuity via Spatial Filtering . | FRONTIERS IN NEUROSCIENCE , 2021 , 15 .
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Enhancement of capability for motor imagery using vestibular imbalance stimulation during brain computer interface EI SCIE PubMed
期刊论文 | 2021 , 18 (5) | JOURNAL OF NEURAL ENGINEERING
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Objective. Motor imagery (MI), based on the theory of mirror neurons and neuroplasticity, can promote motor cortical activation in neurorehabilitation. The strategy of MI based on brain-computer interface (BCI) has been used in rehabilitation training and daily assistance for patients with hemiplegia in recent years. However, it is difficult to maintain the consistency and timeliness of receiving external stimulation to neural activation in most subjects owing to the high variability of electroencephalogram (EEG) representation across trials/subjects. Moreover, in practical application, MI-BCI cannot highly activate the motor cortex and provide stable interaction owing to the weakness of the EEG feature and lack of an effective mode of activation. Approach. In this study, a novel hybrid BCI paradigm based on MI and vestibular stimulation motor imagery (VSMI) was proposed to enhance the capability of feature response for MI. Twelve subjects participated in a group of controlled experiments containing VSMI and MI. Three indicators, namely, activation degree, timeliness, and classification accuracy, were adopted to evaluate the performance of the task. Main results. Vestibular stimulation could significantly strengthen the suppression of alpha and beta bands of contralateral brain regions during MI, that is, enhance the activation degree of the motor cortex (p< 0.01). Compared with MI, the timeliness of EEG feature-response achieved obvious improvements in VSMI experiments. Moreover, the averaged classification accuracy of VSMI and MI was 80.56% and 69.38%, respectively. Significance. The experimental results indicate that specific vestibular activity contributes to the oscillations of the motor cortex and has a positive effect on spontaneous imagery, which provides a novel MI paradigm and enables the preliminary exploration of sensorimotor integration of MI.

Keyword :

brain computer interface activation degree motor imagery (MI) vestibular stimulation

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GB/T 7714 Zhang, Kai , Xu, Guanghua , Du, Chenghang et al. Enhancement of capability for motor imagery using vestibular imbalance stimulation during brain computer interface [J]. | JOURNAL OF NEURAL ENGINEERING , 2021 , 18 (5) .
MLA Zhang, Kai et al. "Enhancement of capability for motor imagery using vestibular imbalance stimulation during brain computer interface" . | JOURNAL OF NEURAL ENGINEERING 18 . 5 (2021) .
APA Zhang, Kai , Xu, Guanghua , Du, Chenghang , Liang, Renghao , Han, Chenchen , Zheng, Xiaowei et al. Enhancement of capability for motor imagery using vestibular imbalance stimulation during brain computer interface . | JOURNAL OF NEURAL ENGINEERING , 2021 , 18 (5) .
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Multi-scale noise transfer and feature frequency detection in SSVEP based on FitzHugh-Nagumo neuron system EI SCIE PubMed
期刊论文 | 2021 , 18 (5) | JOURNAL OF NEURAL ENGINEERING
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Objective. The steady-state visual evoked potential (SSVEP) is one of the most commonly used control signals for brain-computer interfaces (BCIs) due to its excellent interactive potential, such as high tolerance to noises and robust performance across users. In addition, it has a stable cycle, obvious characteristics and minimal training requirements. However, the SSVEP is extremely weak and companied with strong and multi-scale noise, resulting in a poor signal-to-noise ratio in practice. Common algorithms for classification are based on the principle of template matching and spatial filtering, which cannot obtain satisfied performance of SSVEP detection under the multi-scale noise. Therefore, using linear methods to extract SSVEP with obvious nonlinear and non-stationary characteristics, the useful signal will be attenuated or lost. Approach. To address this issue, two novel frameworks based on a two-dimensional nonlinear FitzHugh-Nagumo (FHN) neuron system are proposed to extract feature frequency of SSVEP. Results. In order to evaluate the effectiveness of the proposed methods, this research recruit 22 subjects to participate the experiment. Experimental results show that nonlinear FHN neuron model can force the energy of noise to be transferred into SSVEP and hence amplifying the amplitude of the target frequency. Compared with the traditional methods, the FHN and FHNCCA methods can achieve higher classification accuracy and faster processing speed, which effectively improves the information transmission rate of SSVEP-based BCI.

Keyword :

FHN and FHNCCA methods brain-computer interfaces information transmission rate steady-state visual evoked potential FHN neuron model

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GB/T 7714 Chen, Ruiquan , Xu, Guanghua , Zhang, Xun et al. Multi-scale noise transfer and feature frequency detection in SSVEP based on FitzHugh-Nagumo neuron system [J]. | JOURNAL OF NEURAL ENGINEERING , 2021 , 18 (5) .
MLA Chen, Ruiquan et al. "Multi-scale noise transfer and feature frequency detection in SSVEP based on FitzHugh-Nagumo neuron system" . | JOURNAL OF NEURAL ENGINEERING 18 . 5 (2021) .
APA Chen, Ruiquan , Xu, Guanghua , Zhang, Xun , Han, Chengcheng , Zhang, Sicong . Multi-scale noise transfer and feature frequency detection in SSVEP based on FitzHugh-Nagumo neuron system . | JOURNAL OF NEURAL ENGINEERING , 2021 , 18 (5) .
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Waveform feature extraction and signal recovery in single-channel TVEP based on Fitzhugh-Nagumo stochastic resonance EI SCIE PubMed
期刊论文 | 2021 , 18 (5) | JOURNAL OF NEURAL ENGINEERING
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Objective. Transient visual evoked potential (TVEP) can reflect the condition of the visual pathway and has been widely used in brain-computer interface. TVEP signals are typically obtained by averaging the time-locked brain responses across dozens or even hundreds of stimulations, in order to remove different kinds of interferences. However, this procedure increases the time needed to detect the brain status in realistic applications. Meanwhile, long repeated stimuli can vary the evoked potentials and discomfort the subjects. Therefore, a novel unsupervised framework was developed in this study to realize the fast extraction of single-channel TVEP signals with a high signal-to-noise ratio. Approach. Using the principle of nonlinear aperiodic FitzHugh-Nagumo (FHN) model, a fast extraction and signal restoration technology of TVEP waveform based on FHN stochastic resonance is proposed to achieve high-quality acquisition of signal features with less average times. Results: A synergistic effect produced by noise, aperiodic signal and nonlinear system can force the energy of noise to be transferred into TVEP and hence amplifying the useful P100 feature while suppressing multi-scale noise. Significance. Compared with the conventional average and average-singular spectrum analysis-independent component analysis(average-SSA-ICA) method, the average-FHN method has a shorter stimulation time which can greatly improve the comfort of patients in clinical TVEP detection and a better performance of TVEP waveform i.e. a higher accuracy of P100 latency. The FHN recovery method is not only highly correlated with the original signal, but also can better highlight the P100 amplitude, which has high clinical application value.

Keyword :

FHN stochastic resonance brain-computer interface the FHN recovery method single-channel TVEP signals the average-FHN method

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GB/T 7714 Chen, Ruiquan , Xu, Guanghua , Zheng, Yang et al. Waveform feature extraction and signal recovery in single-channel TVEP based on Fitzhugh-Nagumo stochastic resonance [J]. | JOURNAL OF NEURAL ENGINEERING , 2021 , 18 (5) .
MLA Chen, Ruiquan et al. "Waveform feature extraction and signal recovery in single-channel TVEP based on Fitzhugh-Nagumo stochastic resonance" . | JOURNAL OF NEURAL ENGINEERING 18 . 5 (2021) .
APA Chen, Ruiquan , Xu, Guanghua , Zheng, Yang , Yao, Pulin , Zhang, Sicong , Yan, Li et al. Waveform feature extraction and signal recovery in single-channel TVEP based on Fitzhugh-Nagumo stochastic resonance . | JOURNAL OF NEURAL ENGINEERING , 2021 , 18 (5) .
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