Fractional-order state space reconstruction: a new frontier in multivariate complex time series.

This paper presents a novel approach to the phase space reconstruction technique, fractional-order phase space reconstruction (FOSS), which generalizes the traditional integer-order derivative-based method. By leveraging fractional derivatives, FOSS offers a novel perspective for understanding complex time series, revealing unique properties not captured by conventional methods. We further develop the multi-span transition entropy component method (MTECM-FOSS), an advanced complexity measurement technique that builds upon FOSS. MTECM-FOSS decomposes complexity into intra-sample and inter-sample components, providing a more comprehensive understanding of the dynamics in multivariate data. In simulated data, we observe that lower fractional orders can effectively filter out random noise. Time series with diverse long- and short-term memory patterns exhibit distinct extremities at different fractional orders. In practical applications, MTECM-FOSS exhibits competitive or superior classification performance compared to state-of-the-art algorithms when using fewer features, indicating its potential for engineering tasks.

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.

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.

Nitrogen Atom Induced Contrast Effect on the Mechanofluorochromic Characteristics of Anthracene-Based Acceptor-Donor-Acceptor Fluorescent Molecules.

The mechanofluorochromic (MFC) characteristics of anthracene-based acceptor-donor-acceptor (A-D-A) fluorescent molecules are explored through a comprehensive investigation of their photophysical behaviors. Six 9,10-diheteroarylanthracene derivatives with varying acceptor groups (pyridin-4-yl, pyridin-3-yl, pyridin-2-yl, pyrimidin-5-yl, pyrazinyl and quinoxalinyl) are synthesized and systematically characterized. The photophysical properties in both solution and solid-state are examined, revealing subtle yet significant influences of the spatial arrangement and number of nitrogen atoms within the acceptor group on fluorescence emission. Single-crystal structures of these compounds provide insights into their steric configurations and intermolecular packing modes, offering valuable insights into the fundamental mechanisms that underlie the observed MFC properties. This study illuminates the intricate interplay between MFC properties and the refined molecular structure, thus presenting promising avenues for the design and advancement of novel MFC materials.

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.

Enhancement of capability for motor imagery using vestibular imbalance stimulation during brain computer interface.

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 ofαandßbands 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.

Enhancing Performance of SSVEP-Based Visual Acuity via Spatial Filtering.

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.

Iron-Catalyzed, Site-Selective Difluoromethylthiolation (-SCF2H) and Difluoromethylselenation (-SeCF2H) of Unactivated C(sp3)-H Bonds in N-Fluoroamides.

The iron-catalyzed δ-C(sp3)-H bond difluoromethylthiolation and difluoromethylselenation of aliphatic amides with high site selectivity are reported. Essential to the success is the employment of an amide radical formed in situ to activate the inert C(sp3)-H bond and the utilization of the easily handled PhSO2SCF2H and PhSO2SeCF2H as coupling reagents under mild conditions. This scalable protocol exhibits a broad substrate scope bearing versatile functional groups. Mechanistic studies indicate that the reaction proceeds through -SCF2H and -SeCF2H radical transfer.

Real-time, precise, rapid and objective visual acuity assessment by self-adaptive step SSVEPs.

Objective. This study aimed to explore an online, real-time, and precise method to assess steady-state visual evoked potential (SSVEP)-based visual acuity more rapidly and objectively with self-adaptive spatial frequency steps.Approach. Taking the vertical sinusoidal reversal gratings with different spatial frequencies and temporal frequencies as the visual stimuli, according to the psychometric function for visual acuity assessment, a self-adaptive procedure, the best parameter estimation by sequential testing algorithm, was used to calculate the spatial frequency sequence based on all the previous spatial frequencies and their significance of the SSVEP response. Simultaneously, the canonical correlation analysis (CCA) method with a signal-to-noise ratio (SNR) significance detection criterion was used to judge the significance of the SSVEP response.Main results.After 18 iterative trails, the spatial frequency to be presented converged to a value, which was exactly defined as the SSVEP visual acuity threshold. Our results indicated that this SSVEP acuity had a good agreement and correlation with subjective Freiburg Visual Acuity and Contrast Test acuity, and the test-retest repeatability was also good.Significance. The self-adaptive step SSVEP procedure combined with the CCA method and SNR significance detection criterion appears to be an alternative method in the real-time SSVEP acuity test to obtain objective visual acuity more rapidly and precisely.

Assessing the Effect of the Refresh Rate of a Device on Various Motion Stimulation Frequencies Based on Steady-State Motion Visual Evoked Potentials.

The refresh rate is one of the important parameters of visual presentation devices, and assessing the effect of the refresh rate of a device on motion perception has always been an important direction in the field of visual research. This study examined the effect of the refresh rate of a device on the motion perception response at different stimulation frequencies and provided an objective visual electrophysiological assessment method for the correct selection of display parameters in a visual perception experiment. In this study, a flicker-free steady-state motion visual stimulation with continuous scanning frequency and different forms (sinusoidal or triangular) was presented on a low-latency LCD monitor at different refresh rates. Seventeen participants were asked to observe the visual stimulation without head movement or eye movement, and the effect of the refresh rate was assessed by analyzing the changes in the intensity of their visual evoked potentials. The results demonstrated that an increased refresh rate significantly improved the intensity of motion visual evoked potentials at stimulation frequency ranges of 7-28 Hz, and there was a significant interaction between the refresh rate and motion frequency. Furthermore, the increased refresh rate also had the potential to enhance the ability to perceive similar motion. Therefore, we recommended using a refresh rate of at least 120 Hz in motion visual perception experiments to ensure a better stimulation effect. If the motion frequency or velocity is high, a refresh rate of≥240 Hz is also recommended.