Flexible Tactile Sensors for 3D Force Detection.

As tactile force sensing has become increasingly significant in the field of machine haptics, achieving multidimensional force sensing remains a challenge. We propose a 3D flexible force sensor that consists of an axisymmetric hemispherical protrusion and four equally sized quarter-circle electrodes. By simulating the device using a force and electrical field model, it has been found that the magnitude and direction of the force can be expressed through the voltage relationship of the four electrodes when the magnitude of the shear force remains constant and its direction varies within 0-360°. The experimental results show that a resolution of 15° can be achieved in the range 0-90°. Additionally, we installed the sensor on a robotic hand, enabling it to perceive the magnitude and direction of touch and grasp actions. Based on this, the designed 3D flexible tactile force sensor provides valuable insights for multidimensional force detection and applications.

Filter bank second-order underdamped stochastic resonance analysis for implementing a short-term high-speed SSVEP detection.

OBJECTIVE: The progression of brain-computer interfaces (BCIs) has been propelled by breakthroughs in neuroscience, signal processing, and machine learning, marking it as a dynamic field of study over the past few decades. Nevertheless, the nonlinear and non-stationary characteristics of steady-state visual evoked potentials (SSVEPs), coupled with the incongruity between frequently employed linear techniques and nonlinear signal attributes, resulted in the subpar performance of mainstream non-training algorithms like canonical correlation analysis (CCA), multivariate synchronization index (MSI), and filter bank CCA (FBCCA) in short-term SSVEP detection. METHODS: To tackle this problem, the novel fusions of common filter bank analysis, CCA dimensionality reduction methods, USSR models, and MSI recognition models are used in SSVEP signal recognition. RESULTS: Unlike conventional linear techniques such as CCA, MSI, and FBCCA, the filter bank second-order underdamped stochastic resonance (FBUSSR) analysis demonstrates superior efficacy in the detection of short-term high-speed SSVEPs. CONCLUSION: This research enlists 32 subjects and uses a public dataset to assess the proposed approach, and the experimental outcomes indicate that the non-training method can attain greater recognition precision and stability. Furthermore, under the conditions of the newly proposed fusion method and light stimulation, the USSR model exhibits the most optimal enhancement effect. SIGNIFICANCE: The findings of this study underscore the expansive potential for the application of BCI systems in the realm of neuroscience and signal processing.

Hybrid Triboelectric-Electromagnetic Magnetic Energy Harvester-Based Sensing for Wireless Monitoring of Transmission Lines.

Magnetic energy is an abundant and persistent form of energy radiating from various sources. Here, a hybrid triboelectric-electromagnetic magnetic energy harvester (HMEH) system consisting of a modified pendulum unit is proposed, interacting mechanically with two multilayered TENGs and remotely with Cu coils. Systematic studies are conducted on magneto-mechano-energy conversion from power transmission lines. The pendulum is made out of a thin PET plate, with two permanent magnets stuck at each side of the free end of the PET plate. Two multilayered TENGs (each of which has one layer fixed at the same angle while other layers are set free) are located at both sides of the pendulum unit. The coils and the magnets make up the electromagnetic generator (EMG). Multilayered TENGs are connected in parallel with the EMG (each unit is connected to an independent rectifying bridge), and it is possible to charge a 100 µF capacitor to 4.78 V within 55 s. The HMEH system is used to power up a thermometer continuously via a 47 µF capacitor. Furthermore, a design for a wireless early warning system for potential fire hazards due to overheating is realized, revealing potential applications for self-powered wireless monitoring of transmission lines.

Affleck-Dine Leptogenesis from Higgs Inflation.

We find that the triplet Higgs of the type-II seesaw mechanism can simultaneously generate the neutrino masses and observed baryon asymmetry while playing a role in inflation. We survey the allowed parameter space and determine that this is possible for triplet masses as low as a TeV, with a preference for a small vacuum expectation value for the triplet v_{Δ}<10 keV. This requires that the triplet Higgs must decay dominantly into the leptonic channel. Additionally, this model will be probed at the future 100 TeV collider, upcoming lepton flavor violation experiments such as Mu3e, and neutrinoless double beta decay experiments. Thus, this simple framework provides a unified solution to the three major unknowns of modern physics-inflation, the neutrino masses, and the observed baryon asymmetry-while simultaneously providing unique phenomenological predictions that will be probed terrestrially at upcoming experiments.

Effects of Paradigm Color and Screen Brightness on Visual Fatigue in Light Environment of Night Based on Eye Tracker and EEG Acquisition Equipment.

Nowadays, more people tend to go to bed late and spend their sleep time with various electronic devices. At the same time, the BCI (brain−computer interface) rehabilitation equipment uses a visual display, thus it is necessary to evaluate the problem of visual fatigue to avoid the impact on the training effect. Therefore, it is very important to understand the impact of using electronic devices in a dark environment at night on human visual fatigue. This paper uses Matlab to write different color paradigm stimulations, uses a 4K display with an adjustable screen brightness to jointly design the experiment, uses eye tracker and g.tec Electroencephalogram (EEG) equipment to collect the signal, and then carries out data processing and analysis, finally obtaining the influence of the combination of different colors and different screen brightness on human visual fatigue in a dark environment. In this study, subjects were asked to evaluate their subjective (Likert scale) perception, and objective signals (pupil diameter, θ + α frequency band data) were collected in a dark environment (<3 lx). The Likert scale showed that a low screen brightness in the dark environment could reduce the visual fatigue of the subjects, and participants preferred blue to red. The pupil data revealed that visual perception sensitivity was more vulnerable to stimulation at a medium and high screen brightness, which is easier to deepen visual fatigue. EEG frequency band data concluded that there was no significant difference between paradigm colors and screen brightness on visual fatigue. On this basis, this paper puts forward a new index­the visual anti-fatigue index, which provides a valuable reference for the optimization of the indoor living environment, the improvement of satisfaction with the use of electronic equipment and BCI rehabilitation equipment, and the protection of human eyes.

Domain-Adaptive Prototype-Recalibrated Network with Transductive Learning Paradigm for Intelligent Fault Diagnosis under Various Limited Data Conditions.

In real industrial scenarios, intelligent fault diagnosis based on data-driven methods has been widely researched in the past decade. However, data scarcity is widespread in fault diagnosis tasks owning to the difficulties in collecting adequate data. As a result, there is an increasing demand for both researchers and engineers for fault identification with scarce data. To address this issue, an innovative domain-adaptive prototype-recalibrated network (DAPRN) based on a transductive learning paradigm and prototype recalibration strategy (PRS) is proposed, which has the potential to promote the generalization ability from the source domain to target domain in a few-shot fault diagnosis. Within this scheme, the DAPRN is composed of a feature extractor, a domain discriminator, and a label predictor. Concretely, the feature extractor is jointly optimized by the minimization of few-shot classification loss and the maximization of domain-discriminative loss. The cosine similarity-based label predictor, which is promoted by the PRS, is exploited to avoid the bias of naïve prototypes in the metric space and recognize the health conditions of machinery in the meta-testing process. The efficacy and advantage of DAPRN are validated by extensive experiments on bearing and gearbox datasets compared with seven popular and well-established few-shot fault diagnosis methods. In practical application, the proposed DAPRN is expected to solve more challenging few-shot fault diagnosis scenarios and facilitate practical fault identification problems in modern manufacturing.

Toxin-antitoxin HicAB regulates the formation of persister cells responsible for the acid stress resistance in Acetobacter pasteurianus.

Elucidation of the acetic acid resistance (AAR) mechanisms is of great significance to the development of industrial microbial species, specifically to the acetic acid bacteria (AAB) in vinegar industry. Currently, the role of population heterogeneity in the AAR of AAB is still unclear. In this study, we investigated the persister formation in AAB and the physiological role of HicAB in Acetobacter pasteurianus Ab3. We found that AAB were able to produce a high level of persister cells (10-2 to 100 in frequency) in the exponential-phase cultures. Initial addition of acetic acid and ethanol reduced the ratio of persister cells in A. pasteurianus by promoting the intracellular ATP level. Further, we demonstrated that HicAB was an important regulator of AAR in A. pasteurianus Ab3. Strains lacking hicAB showed a decreased survival under acetic acid exposure. Deletion of hicAB significantly diminished the acetic acid production, acetification rate, and persister formation in A. pasteurianus Ab3, underscoring the correlation between hicAB, persister formation, and acid stress resistance. By transcriptomic analysis (RNA-seq), we revealed that HicAB contributed to the survival of A. pasteurianus Ab3 under high acid stress by upregulating the expression of genes involved in the acetic acid over-oxidation and transport, 2-methylcitrate cycle, and oxidative phosphorylation. Collectively, the results of this study refresh our current understanding of the AAR mechanisms in A. pasteurianus, which may facilitate the development of novel ways for improving its industrial performance and direct the scaled-up vinegar production. KEY POINTS: • AAB strains form persister cells with different frequencies. • A. pasteurianus are able to form acid-tolerant persister cells. • HicAB contributes to the AAR and persister formation in A. pasteurianus Ab3.

Investigation of lipid profile in Acetobacter pasteurianus Ab3 against acetic acid stress during vinegar production.

Elucidation of the acetic acid resistance (AAR) mechanisms of Acetobacter pasteurianus is significant for vinegar production. In this study, cell membrane lipid profile of A. pasteurianus Ab3 was investigated by gas chromatography-mass spectrometer (GC-MS) and high performance liquid chromatography-electrospray ionization (HPLC-ESI) combined with high resolution accurate mass/mass spectrometry (HRAM/MS). We observed that cell remodeled the membrane physical state by decreasing the ratio of saturated fatty acids (SFAs)/unsaturated fatty acids (UFAs), and increasing the chain length of fatty acids (FAs) and the content of cyclopropane FAs in response to extreme acid stress. Noticeably, the content of octadecadienoic acid (C18:2) elevated remarkably. Moreover, a continuous reduction in cell membrane fluidity and a "V-type" variance in permeability were discovered. The content of glycerophospholipid and ceramide increased significantly in cells harvested from culture with acidity of 75 g/L and 95 g/L compared to that with acidity of 30 g/L. Among the identified lipid species, the content of phosphatidylcholine (e.g. PC 19:0/18:2 and 19:1/18:0), ceramide (e.g. Cer d18:0/16:1 and d18:0/16:1 + O), and dimethylphosphatidylethanolamine (e.g. dMePE 19:1/16:1) increased notably with increasing acidity. Collectively, these findings refresh our current understanding of the AAR mechanisms in A. pasteurianus Ab3, and should direct future strain breeding and vinegar fermentation.

Comparison of the performance of six stimulus paradigms in visual acuity assessment based on steady-state visual evoked potentials.

PURPOSE: There are several stimulus paradigms used in objective visual acuity assessment based on steady-state visual evoked potentials (SSVEPs). The aim of this study was to explore the difference and performance of common used six stimulus paradigms (reverse vertical sinusoidal gratings, reverse horizontal sinusoidal gratings, reverse vertical square-wave gratings, brief-onset vertical sinusoidal gratings, reversal checkerboards and oscillating expansion-contraction concentric-rings) of SSVEP acuity assessment. METHODS: We tested subjective visual acuity both by tumbling E and Freiburg Visual Acuity and Contrast Test (FrACT) in 11 subjects. SSVEPs were induced by 11 spatial frequencies for each paradigm, and then a threshold determination criterion was used to define the objective SSVEP visual acuity. RESULTS: After SSVEP signal analysis, we found there was difference in SSVEP response of harmonic components and no difference in sensitive electrode placement for the six paradigms. We selected six electrodes (PO3, POz, PO4, O1, Oz and O2) as the sensitive electrodes to use in data processing for each paradigm. The results showed that except for brief-onset vertical sinusoidal gratings, the correlation and agreement between objective SSVEP and subjective FrACT acuity were all quite good, demonstrating good performance in acuity detection for the rest five paradigms. CONCLUSION: Except for brief-onset vertical sinusoidal gratings, all the five stimulus paradigms of reverse vertical sinusoidal gratings, reverse horizontal sinusoidal gratings, reverse vertical square-wave gratings, reversal checkerboards and oscillating expansion-contraction concentric-rings performed quite well in objective SSVEP visual acuity assessment.

Transcriptome response of Acetobacter pasteurianus Ab3 to high acetic acid stress during vinegar production.

Acetic acid accumulation is a universal limiting factor to the vinegar manufacture because of the toxic effect of acetic acid on the acid producing strain, such as Acetobacter pasteurianus. In this study, we aimed to investigate the genome-wide transcriptional response of A. pasteurianus Ab3 to high acid stress during vinegar production. By comparing the transcriptional landscape of cells harvested from a long-term cultivation with high acidity (70 ± 3 g/L) to that of low acidity (10 ± 2 g/L), we demonstrated that 1005 genes were differentially expressed. By functional enrichment analysis, we found that the expression of genes related to the two-component systems (TCS) and toxin-antitoxin systems (TAS) was significantly regulated under high acid stress. Cells increased the genome stability to withstand the intracellular toxicity caused by the acetic acid accumulation by repressing the expression of transposases and integrases. Moreover, high acid stress induced the expression of genes involved in the pathways of peptidoglycan, ceramide, and phosphatidylcholine biosynthesis as well as the Tol-Pal and TonB-ExbB systems. In addition, we observed that cells increased and diversified the ATP production to resist high acid stress. Transcriptional upregulation in the pathways of pyrroloquinoline quinone (PQQ) synthesis and thiamine metabolism suggested that cells may increase the production of prosthetic groups to ensure the enzyme activity upon high acid stress. Collectively, the results of this study increase our current understanding of the acetic acid resistance (AAR) mechanisms in A. pasteurianus and provide opportunities for strain improvement and scaled-up vinegar production.Key Points• TCS and TAS are responsive to the acid stress and constitute the regulating networks.• Adaptive expression changes of cell envelope elements help cell resist acid stress.• Cells promote genome stability and diversify ATP production to withstand acid stress.

Objective and quantitative assessment of visual acuity and contrast sensitivity based on steady-state motion visual evoked potentials using concentric-ring paradigm.

PURPOSE: The traditional assessment of visual acuity and contrast sensitivity depends more on subjective judgments. Steady-state motion visual evoked potentials (SSMVEPs) can provide an objective and quantitative method to evaluate visual functions such as visual acuity and contrast sensitivity. Here, we explored the possibility of objective SSMVEP visual acuity and contrast sensitivity testing, and compared its performance with that of psychophysical methods. METHODS: In this study, we designed a specific concentric ring with oscillating expansion and contraction SSMVEP paradigm to assess visual acuity and contrast sensitivity. By changing the parameters of the paradigm, the SSMVEP paradigm with different contrasts and spatial frequencies corresponding to different visual acuity and contrast sensitivity was designed. Moreover, we proposed a threshold determination criterion to define the corresponding objective SSMVEP visual acuity and contrast sensitivity. RESULTS: We tested visual acuity and contrast sensitivity of sixteen healthy adults utilizing this paradigm with an electroencephalography system. Our data suggested that there was no significant difference between objective visual acuity and contrast sensitivity measurements based on the SSMVEPs and subjective psychophysical ones. CONCLUSION: Our study proved that SSMVEPs can be an objective and quantitative method to measure visual acuity and contrast sensitivity.

The Role of Visual Noise in Influencing Mental Load and Fatigue in a Steady-State Motion Visual Evoked Potential-Based Brain-Computer Interface.

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 α, θ, θ + α powers, θ/α 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.

Effects of combined therapy with glipizide and Aralia root bark extract on glycemic control and lipid profiles in patients with type 2 diabetes mellitus.

BACKGROUND: The root bark of Aralia is a rich source of bioactive components that may improve glycemic control and lipid status. In this study, 148 patients with type 2 diabetes mellitus (T2DM) were assigned randomly to receive either glipizide alone or glipizide plus Aralia root bark extract (ARBE) for 8 weeks to test the effects of ARBE plus glipizide therapy on glycemic control and lipid profiles in these patients. RESULTS: Levels of HbA1c, fasting plasma glucose (FPG) and 2 h postprandial plasma glucose (2-h PPG) in both groups significantly decreased from baseline. Glycated hemoglobin (HbA1c) decreased marginally significantly in participants taking glipizide plus ARBE compared with the glipizide group (P = 0.06). Participants in the combination group had significant decreases in total cholesterol (TC) and low-density lipoprotein cholesterol (LDL-C), and the between-group difference achieved statistical significance for LDL-C (P = 0.04). Reduction in HbA1c in the combination group was significantly associated with changes in TC (r = 0.32; P = 0.006) and LDL-C (r = 0.34; P = 0.005), and the change in FPG was inversely correlated with LDL-C reduction (r = 0.34; P = 0.004). CONCLUSIONS: In patients with T2DM, combination therapy with glipizide and ARBE resulted in moderately lowering HbA1c and LDL-C levels compared with glipizide alone.

Investigating the effects of rare ginsenosides on hyperuricemia and associated sperm damage via nontargeted metabolomics and gut microbiota.

ETHNOPHARMACOLOGICAL RELEVANCE: In ancient times, ginseng was used for hyperuricemia treatment as described in the classic traditional Chinese medical text Shang Han Lun. Recent studies have shown that common ginsenosides and rare ginsenosides (RGS) are the main active compounds in ginseng. RGS have higher activity and are less studied in the treatment of hyperuricemia. AIM OF THE STUDY: To determine whether RGS prevents and ameliorates potassium oxonate(PO)-induced hyperuricemia and concomitant spermatozoa damage in mice and the possible underlying mechanisms. MATERIALS AND METHODS: Potassium oxonate (PO, 300 mg/kg) induced hyperuricemia in mice via the oral administration of RGS (50, 100, or 200 mg/kg) or allopurinol (ALL, 5 mg/kg) for 35 days. Uric acid (UA) and xanthine oxidase (XO) levels were measured to assess the degree of histopathological damage in the liver, kidney, and testis, and renal creatinine (CRE), urea nitrogen (BUN), malondialdehyde (MDA), superoxide dismutase (SOD), glutathione (GSH), and inflammatory factor (IL-1ß) levels were measured to calculate the sperm density. Mechanisms were also explored based on blood and urine metabolomics and the gut microbiota. RESULTS: In this study, we demonstrated that RGS containing Rg3, Rk1, Rg6, and Rg5 could reduce serum UA levels, inhibit serum and hepatic XO activity, reduce renal CRE and BUN levels, further restore renal SOD and GSH activities, reduce the accumulation of MDA in the kidneys, and attenuate the production of renal IL-1ß. RGS was able to restore sperm density. Metabolomic analysis revealed that RGS improved sphingolipid metabolism, pyrimidine metabolism, and other metabolic pathways. 16S rDNA sequencing revealed that RGS could increase gut microbial diversity, restore the Firmicutes/Bacteroidetes (F/B) ratio, and adjust the intestinal microbial balance. Spearman's correlation analysis revealed a correlation between differentially metabolites and the gut microbiota. Lactobacillus and Akkermansia are the core genera. CONCLUSION: RGS can be a candidate for the prevention and amelioration of hyperuricemia and concomitant sperm damage. Its mechanism of action is closely related to sphingolipid metabolism, pyrimidine metabolism, and the modulation of gut microbiota, such as Lactobacillus and Akkermansia.

Flexible Sensor for Real-Time Monitoring of Motion Artifacts in Magnetic Resonance Imaging.

In recent years, magnetic resonance imaging has been widely used in the medical field. During the scan, if the human body moves, then there will be motion artifacts on the scan image, which will interfere with the diagnosis and only be found after the end of the scan sequence, resulting in a waste of manpower and resources. However, there is a lack of technology that halts scanning once motion artifacts arise. Here, we designed a real-time monitoring sensor (RMS) to dynamically perceive the movement of the human body and to pause in time when the movement exceeds a certain amplitude. The sensor has an array structure that can accurately sense the position of the human body in real time. The selection of the RMS ensures that there is no additional interference with the scanning results. Based on this design, the RMS can achieve the monitoring function of motion artifact generation.

20.2% Efficiency Organic Photovoltaics Employing a π-Extension Quinoxaline-Based Acceptor with Ordered Arrangement.

Organic solar cells, as a cutting-edge sustainable renewable energy technology, possess a myriad of potential applications, while the bottleneck problem of less than 20% efficiency limits the further development. Simultaneously achieving an ordered molecular arrangement, appropriate crystalline domain size, and reduced nonradiative recombination poses a significant challenge and is pivotal for overcoming efficiency limitations. This study employs a dual strategy involving the development of a novel acceptor and ternary blending to address this challenge. A novel non-fullerene acceptor, SMA, characterized by a highly ordered arrangement and high lowest unoccupied molecular orbital energy level, is synthesized. By incorporating SMA as a guest acceptor in the PM6:BTP-eC9 system, it is observed that SMA staggered the liquid-solid transition of donor and acceptor, facilitating acceptor crystallization and ordering while maintaining a suitable domain size. Furthermore, SMA optimized the vertical morphology and reduced bimolecular recombination. As a result, the ternary device achieved a champion efficiency of 20.22%, accompanied by increased voltage, short-circuit current density, and fill factor. Notably, a stabilized efficiency of 18.42% is attained for flexible devices. This study underscores the significant potential of a synergistic approach integrating acceptor material innovation and ternary blending techniques for optimizing bulk heterojunction morphology and photovoltaic performance.

A Training-Free Infant Spontaneous Movement Assessment Method for Cerebral Palsy Prediction Based on Videos.

OBJECTIVE: Early diagnosis of infant cerebral palsy (CP) is very important for infant health. In this paper, we present a novel training-free method to quantify infant spontaneous movements for predicting CP. METHODS: Unlike other classification methods, our method turns the assessment into a clustering task. First, the joints of the infant are extracted by the current pose estimation algorithm, and the skeleton sequence is segmented into multiple clips through a sliding window. Then we cluster the clips and quantify infant CP by the number of cluster classes. RESULTS: The proposed method was tested on two datasets, and achieved state-of-the-arts (SOTAs) on both datasets using the same parameters. What's more, our method is interpretable with visualized results. CONCLUSION: The proposed method can quantify abnormal brain development in infants effectively and be used in different datasets without training. SIGNIFICANCE: Limited by small samples, we propose a training-free method for quantifying infant spontaneous movements. Unlike other binary classification methods, our work not only enables continuous quantification of infant brain development, but also provides interpretable conclusions by visualizing the results. The proposed spontaneous movement assessment method significantly advances SOTAs in automatically measuring infant health.

A quantization algorithm of visual fatigue based on underdamped second order stochastic resonance for steady state visual evoked potentials.

Introduction: In recent years, more and more attention has been paid to the visual fatigue caused by steady state visual evoked potential (SSVEP) paradigm. It is well known that the large-scale application of brain-computer interface is closely related to SSVEP, and the fatigue caused by SSVEP paradigm leads to the reduction of application effect. At present, the mainstream method of objectively quantifying visual fatigue in SSVEP paradigm is based on traditional canonical correlation analysis (CCA). Methods: In this paper, we propose a new SSVEP paradigm visual fatigue quantification algorithm based on underdamped second-order stochastic resonance (USSR) to accurately quantify visual fatigue caused by SSVEP paradigm in different working modes using single-channel electroencephalogram (EEG) signals. This scheme uses the fixed-step energy parameter optimization algorithm we designed, combined with the USSR model, to significantly improve the signal-to-noise ratio of the processed signal at the target characteristic frequency. We not only compared the new algorithm with CCA, but also with the traditional subjective quantitative visual fatigue gold standard Likert fatigue scale. Results: There was no significant difference (p = 0.090) between the quantitative value of paradigm fatigue obtained by the single channel SSVEP processed by the new algorithm and the gold standard of subjective fatigue quantification, while there was a significant difference (p < 0.001***) between the quantitative value of paradigm fatigue obtained by the traditional multi-channel CCA algorithm and the gold standard of subjective fatigue quantification. Discussion: The conclusion shows that the quantization value obtained by the new algorithm can better match the subjective gold standard score, which also shows that the new algorithm is more reliable, which reflects the superiority of the new algorithm.

Enhancement of Time-Frequency Energy for the Classification of Motor Imagery Electroencephalogram Based on an Improved FitzHugh-Nagumo Neuron System.

Brain-computer interface (BCI) based on motor imagery (MI) electroencephalogram (EEG) has become an essential way for rehabilitation, because of the activation and interaction of motor neurons between the brain and rehabilitation devices in recent years. However, due to the discrepancies between individuals, the frequency ranges can be different even for the same rhythm component of EEG recordings, which brings difficulties to the extraction of features for MI classification. Typical algorithms for MI classification such as common spatial patterns (CSP) require multi-channel analysis and lack frequency information. With the development of BCI, the single-channel BCI system has become indispensable for simplicity of use. However, the currently available single-channel detection methods have low classification accuracy. To address this issue, two novel frameworks based on an improved two-dimensional nonlinear FitzHugh-Nagumo (FHN) neuron system are proposed to extract features of the single-channel MI. To evaluate the effectiveness of the proposed methods, this research utilized an open-access database (BCI competition IV dataset 2a), an offline database, and a 10-fold cross-validation procedure. Experimental results showed that the improved nonlinear FHN system can transfer the energy of noise into MI, thereby effectively enhancing the time-frequency energy. Compared with the traditional methods, the proposed methods can achieve higher classification accuracy and robustness.

A Precise Frequency Recognition Method of Short-Time SSVEP Signals Based on Signal Extension.

OBJECTIVE: Improving the Information Transfer Rate (ITR) is a popular research topic in steady-state visual evoked potential (SSVEP)-based brain-computer interfaces (BCIs). The higher recognition accuracy of short-time SSVEP signal is critical to improving ITR and achieving high-speed SSVEP-BCIs. However, the existing algorithms have unsatisfactory performance on recognizing short-time SSVEP signals, especially for calibration-free methods. METHOD: This study for the first time proposed improving the recognition accuracy of short-time SSVEP signals based on the calibration-free method by extending the SSVEP signal length. A signal extension model based on Multi-channel adaptive Fourier decomposition with different Phase (DP-MAFD) is proposed to achieve signal extension. Then the Canonical Correlation Analysis based on signal extension (SE-CCA) is proposed to complete the recognition and classification of SSVEP signals after extension. RESULT: The similarity study and SNR comparison analysis on public SSVEP datasets demonstrate that the proposed signal extension model has the ability to extend SSVEP signals. The classification results show that the proposed method outperforms Canonical Correlation Analysis (CCA) and Filter Bank Canonical Correlation Analysis (FBCCA) significantly in the measure of classification accuracy and information transmission rate (ITR), especially for short-time signals. The highest ITR of SE-CCA is improved to 175.61 bits/min at around 1s, while CCA is 100.55 bits/min at 1.75s and FBCCA is 141.76 bits/min at 1.25s. CONCLUSION: The signal extension method can improve the recognition accuracy of short-time SSVEP signals and further improve the ITR of SSVEP-BCIs.