Introduction An objective and precise pain evaluation is of significant clinical value, electroencephalography as a non-invasive physiological signal has been demonstrated to correlate with subjective perception. This study aimed analyze the EEG changes in patients lumbar disk herniation (LDH) under traditional Chinese medicine small needle knife further explore feasibility an indicator assessment LDH. Methods conducted resting-state on 20 LDH before after treatment healthy controls,...

Intermittent theta burst stimulation (iTBS) is a non-invasive technique frequently employed to induce neural plastic changes and enhance visual attention. Currently, most studies utilized single iTBS session on healthy subjects short-term within tens of minutes post-stimulation investigate its single-session effect attention performance. Few have conducted multiple sessions the cerebellum explore long-term effects cerebral cortex daily In this study, 18 were involved in randomized,...

Introduction Visual hallucination is a prevalent psychiatric disorder characterized by the occurrence of false visual perceptions due to misinterpretation in brain. Individuals with Parkinson’s disease often experience both minor and complex hallucinations. The underlying mechanism hallucinations patients commonly attributed dysfunction pathway attention network. However, there limited research on Methods To address this gap, we conducted an experiment involving 13 hallucinations, without...

This paper deals with target-detection issues in extremely heterogeneous environments, a multichannel synthetic-aperture-radar-based ground moving-target indication (SAR-GMTI) system, and proposes new detector the aim of addressing such environments. The proposed is multistage one: first detection stage implements conventional Displaced Phase Center Array test, but second which called Degree Radial-Velocity Consistency (DRVC) test. We will show that newly developed DRVC test possesses two...

Maneuvering target tracking is a problem of state estimation where the system undergoes abrupt changes. Traditional model-based approaches to this are threatened by performance degradation caused model mismatch and estimator usually has limited statistical precision in practice. Developed from what machine sees as mathematically optimal data, deep neural network-based methods not sensitive variant models long interested motions fully contained training data. Besides, having access true while...

Human movement is closely linked with muscle activities. Research has indicated that predicting human movements surface electromyography signals feasible. However, the classification accuracy of signal–based still limited due to low signal noise ratio, especially when multiple categories are investigated. In this study, six representative time-domain feature extraction techniques and four frequency-domain three different types classifiers (the statistical classifier Gaussian mixture model,...

In traditional hand function assessment, patients and physicians always need to accomplish complex activities rating tasks. This paper proposes a novel wearable glove system for assessment. A sensing consisting of 12 nine-axis inertial magnetic unit (IMMU) sensors is used obtain the acceleration, angular velocity, geomagnetic orientation human movements. complementary filter algorithm applied calculate angles joints after sensor calibration. virtual model also developed map with in Unity...

AbstractSAR image shadow is the geometric distortion caused by scene elevation and downs. Shadow contour of SAR contains local spatial characteristic target, use a target’s in synthetic aperture radar (SAR) imaging has garnered much attention for automated target recognition applications. Due to special mechanism, not as clear that optical image. Aiming at recognition, this paper presents an segmentation method based on Partial Differential De-noising Marker-controlled, then automatic can be...

Pulse compression radar usually has undesirables range sidelobe, which makes it difficult to detect weak targets nearby strong targets. Low sidelobe level at the receiving end can suppress interference from target returns, and hence is an attractive feature for systems. In this paper, we study a waveform design method that jointly optimize phase coded mismatch filter. The principal idea minimize peak (PSL) of sidelobes after mismatched filtering with constraint signal-to-noise ratio (SNR)...

This paper presents a novel reconfigurable crawling robot based on an origami twisted tower structure. Compared with other structures, the can achieve extension, contraction, and bending motions as flexible body parts in robotic designs. The kinematics of one-layer were analyzed rotation angles. mechanical properties one-layer, two-layer, four-layer towers compared compression experiments. A rope-motor-driven was designed to realize forward, backward, left-turning, right-turning motions. Two...

Transcranial magnetic stimulation is a widely used brain intervention technique in clinical settings. In recent years, the role of cerebellum learning and memory has become one hotspots field cognitive neuroscience. this study, we recruited 36 healthy college or graduate students as subjects divided them into groups, with 10 to 14 each group. We performed 5 Hz 20 repeated transcranial sham on Crus II subregion different then let complete 2-back working task before after stimulation....

Automatic target recognition (ATR) is a crucial application for synthetic aperture radar (SAR). This paper presents an ATR method with the scattering centre (SC) based on world view vector (WVV) and weighted bipartite graph model (WBGM). Targets are separated by filter-based cluster size insensitive enhanced fuzzy c-mean (csiEnFCM) algorithm before feature extraction. Later, WVV-based set constructed extracted SCs. Subsequently, WBGM applied to recognize matching its templates. Experiments...

The error-related potential (ErrP) is a weak explicit representation of the human brain for individual wrong behaviors. Previously, ErrP-related research usually focused on design automatic correction and error mechanisms high-risk pipeline-type judgment systems. Mounting evidence suggests that cerebellum plays an important role in various cognitive processes. Thus, this study introduced cerebellar information to enhance online classification effect potentials. We regional characteristics...

Cerebellar intermittent theta burst stimulation (iTBS) modulates the excitability of cerebral cortex and may enhance attentional performance. To date, few studies have conducted iTBS on healthy subjects for one week used electroencephalography (EEG) to investigate effect multiple sessions resting-state functional brain networks daily

Human motion is closely related to muscle activities. Numerous researches have proved that it feasible predict human motions by using sEMG (surface Electromyography) signals. But due the low signal-to-noise ratio of signals, recognition accuracy based still limited, especially when there are multiple categories. In this paper, a multi-class AdaBoost algorithm introduced combine prediction ten component BP neural networks. From results recognizing 8 wrist and 12 finger motions, reveals...

Radar-based vital sign monitoring, a promising technique for medical guidance and versatile applications, faces challenges in complex environments with low signal-to-noise ratio substantial interference. This article focuses on accurate frequency estimation, particularly weak heartbeat estimation the presence of harmonics innovative method involves constructing an enhanced multiplication spectrum performing harmonic order recognition to effectively eliminate effect cardiopulmonary...

Doppler shift compensation (DSC) is a unique feature observed in certain species of echolocating bats and hypothesized to be an adaptation detecting fluttering insects. However, current research on DSC has primarily focused that are not engaged foraging activities. In this study, we investigated the performance Pratt's roundleaf bat, Hipposideros pratti, which was trained pursue insects various motion states within laboratory setting. Our study yielded three main results. First, H. pratti...

Resolution of synthetic aperture radar (SAR) images is limited by imaging hardware. To improve SAR image resolution, interpolation needs to be carried out on a image. An algorithm with good effect incurs high computational cost and cannot used in real-time scenario. This paper applies Compute Unified Device Architecture (CUDA) speed up the piece-wise autoregressive model for acquiring high-quality images. A partial differential carry de-noising. After de-noising, divide based local window...

In various applications, such as disease diagnosis, surgical navigation, human brain atlas analysis, and other neuroimage processing scenarios, extraction is typically regarded the initial stage in MRI image processing. Whole-brain semantic segmentation algorithms, U-Net, have demonstrated ability to achieve relatively satisfactory results even with a limited number of training samples. order enhance precision segmentation, frameworks been developed, including 3D slice auto-context U-Net....

Due to special imaging mechanism, shadow contour of SAR image is not as clear that optical image. Aiming at target recognition, this paper presents a segmentation method based on Partial Differential De-noising and Marker-Controlled, carries out automatic recognition result segmentation. Experimental results show that, using the paper, can classify effectively.

Recent studies have discovered that functional connections are impaired in patients with Parkinson’s disease (PD) accompanied by hallucinations (PD-H), even at the preclinical stage. The cerebellum has been implicated playing a role cognitive processes. However, connectivity (FC) between sub-regions of PD needs further clarification. Resting-state magnetic resonance imaging (rs-fMRI) data were collected from three groups (17 PD-H patients, 13 not (PD-NH), and 26 healthy controls (HC)). this...

Currently, the classification accuracy of surface electromyography (sEMG) signals is high in literature, but conventional recognition system may classify untrained movements or trained low reliability to one its target classes by mistake. If such a used for prosthetic control, sometimes it cause disaster. A two-layer classifier that fuses Gaussian mixture model (GMM) and k-nearest neighbor (kNN) sequential structure proposed this study. The algorithm can reject with efficient rejecting...