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Abstract Ionic conductive hydrogels (ICHs) have recently gained prominence in biosensing, indicating their potential to redefine future biomedical applications. However, the integration of these hydrogels into sensor technologies and their long‐term efficacy in practical applications pose substantial challenges, including a synergy of features, such as mechanical adaptability, conductive sensitivity, self‐adhesion, self‐regeneration, and microbial resistance. To address these challenges, this study introduces a novel hydrogel system using an imidazolium salt with a ureido backbone (UL) as the primary monomer. Fabricated via a straightforward one‐pot copolymerization process that includes betaine sulfonate methacrylate (SBMA) and acrylamide (AM), the hydrogel demonstrates multifunctional properties. The innovation of this hydrogel is attributed to its robust mechanical attributes, outstanding strain responsiveness, effective water retention, and advanced self‐regenerative and healing capabilities, which collectively lead to its superior performance in various applications. Moreover, this hydrogel exhibited broad‐spectrum antibacterial activity. Its potential for biomechanical monitoring, especially in tandem with contact and noncontact electrocardiogram (ECG) devices, represents a noteworthy advancement in precise real‐time cardiac monitoring in clinical environments. In addition, the conductive properties of the hydrogel make it an ideal substrate for electrophoretic patches aimed at treating infected wounds and consequently enhancing the healing process.

IntroductionUpper limb rehabilitation assessment plays a pivotal role in the recovery process of stroke patients. The current clinical assessment tools often rely on subjective judgments of healthcare professionals. Some existing research studies have utilized physiological signals for quantitative assessments. However, most studies used single index to assess the motor functions of upper limb. The fusion of surface electromyography (sEMG) and functional near-infrared spectroscopy (fNIRS) presents an innovative approach, offering simultaneous insights into the central and peripheral nervous systems.MethodsWe concurrently collected sEMG signals and brain hemodynamic signals during bilateral elbow flexion in 15 stroke patients with subacute and chronic stages and 15 healthy control subjects. The sEMG signals were analyzed to obtain muscle synergy based indexes including synergy stability index (SSI), closeness of individual vector (CV) and closeness of time profile (CT). The fNIRS signals were calculated to extract laterality index (LI).ResultsThe primary findings were that CV, SSI and LI in posterior motor cortex (PMC) and primary motor cortex (M1) on the affected hemisphere of stroke patients were significantly lower than those in the control group (p

The present study utilizes the significant differences in θ, α, and β band power spectra observed in electroencephalograms (EEGs) during distracted versus focused driving. Three subtasks, visual distraction, auditory distraction, and cognitive distraction, were designed to appear randomly during driving simulations. The θ, α, and β band power spectra of the EEG signals of the four driving attention states were extracted, and SVM, EEGNet, and GRU-EEGNet models were employed for the detection of the driving attention states, respectively. Online experiments were conducted. The extraction of the θ, α, and β band power spectrum features of the EEG signals was found to be a more effective method than the extraction of the power spectrum features of the whole EEG signals for the detection of driving attention states. The driving attention state detection accuracy of the proposed GRU-EEGNet model is improved by 6.3% and 12.8% over the EEGNet model and PSD_SVM method, respectively. The EEG decoding method combining EEG features and an improved deep learning algorithm, which effectively improves the driving attention state detection accuracy, was manually and preliminarily selected based on the results of existing studies.

IntroductionRhythmic visual cues (RVCs) may influence gait initiation by modulating cognition resources. However, it is unknown how RVCs modulate cognitive resources allocation during gait movements. This study focused on investigating the effects of RVCs on cortical hemodynamic response features during stepping to evaluate the changes of cognitive resources.MethodsWe recorded cerebral hemoglobin concentration changes of 14 channels in 17 healthy subjects using functional near-infrared spectroscopy (fNIRS) during stepping tasks under exposure to RVCs and non-rhythmic visual cues (NRVCs). We reported mean oxygenated hemoglobin (HbO) concentration changes, β-values, and functional connectivity (FC) between channels.ResultsThe results showed that, the RVC conditions revealed lower HbO responses compared to the NRVC conditions during the preparation and early stepping. Correspondingly, the β-values reflected that RVCs elicited lower hemodynamic responses than NRVCs, and there was a decreasing trend in stimulus-evoked cortical activation as the task progressed. However, the FC between channels were stronger under RVCs than under NRVCs during the stepping progress, and there were more significant differences in FC during the early stepping.DiscussionIn conclusion, there were lower cognitive demand and stronger FC under RVC conditions than NRVC conditions, which indicated higher efficiency of cognitive resources allocation during stepping tasks. This study may provide a new insight for further understanding the mechanism on how RVCs alleviate freezing of gait.

IntroductionThe time-varying and individual variability of surface electromyographic signals (sEMG) can lead to poorer motor intention detection results from different subjects and longer temporal intervals between training and testing datasets. The consistency of using muscle synergy between the same tasks may be beneficial to improve the detection accuracy over long time ranges. However, the conventional muscle synergy extraction methods, such as non-negative matrix factorization (NMF) and principal component analysis (PCA) have some limitations in the field of motor intention detection, especially in the continuous estimation of upper limb joint angles.MethodsIn this study, we proposed a reliable multivariate curve-resolved-alternating least squares (MCR-ALS) muscle synergy extraction method combined with long-short term memory neural network (LSTM) to estimate continuous elbow joint motion by using the sEMG datasets from different subjects and different days. The pre-processed sEMG signals were then decomposed into muscle synergies by MCR-ALS, NMF and PCA methods, and the decomposed muscle activation matrices were used as sEMG features. The sEMG features and elbow joint angular signals were input to LSTM to establish a neural network model. Finally, the established neural network models were tested by using sEMG dataset from different subjects and different days, and the detection accuracy was measured by correlation coefficient.ResultsThe detection accuracy of elbow joint angle was more than 85% by using the proposed method. This result was significantly higher than the detection accuracies obtained by using NMF and PCA methods. The results showed that the proposed method can improve the accuracy of motor intention detection results from different subjects and different acquisition timepoints.DiscussionThis study successfully improves the robustness of sEMG signals in neural network applications using an innovative muscle synergy extraction method. It contributes to the application of human physiological signals in human-machine interaction.

Rhythmic visual cues can affect the allocation of cognitive resources during gait initiation (GI) and motor preparation. However, it is unclear how the input of rhythmic visual information modulates the allocation of cognitive resources and affects GI. The purpose of this study was to explore the effect of rhythmic visual cues on the dynamic allocation of cognitive resources by recording electroencephalographic (EEG) activity during exposure to visual stimuli. This study assessed event-related potentials (ERPs), event-related synchronization/desynchronization (ERS/ERD), and EEG microstates at 32 electrodes during presentation of non-rhythmic and rhythmic visual stimuli in 20 healthy participants. The ERP results showed that the amplitude of the C1 component was positive under exposure to rhythmic visual stimuli, while the amplitude of the N1 component was higher under exposure to rhythmic visual stimuli compared to their non-rhythmic counterparts. Within the first 200 ms of the onset of rhythmic visual stimuli, ERS in the theta band was highly pronounced in all brain regions analyzed. The results of microstate analysis showed that rhythmic visual stimuli were associated with an increase in cognitive processing over time, while non-rhythmic visual stimuli were associated with a decrease. Overall, these findings indicated that, under exposure to rhythmic visual stimuli, consumption of cognitive resources is lower during the first 200 ms of visual cognitive processing, but the consumption of cognitive resources gradually increases over time. After approximately 300 ms, cognitive processing of rhythmic visual stimuli consumes more cognitive resources than processing of stimuli in the non-rhythmic condition. This indicates that the former is more conducive to the completion of gait-related motor preparation activities, based on processing of rhythmic visual information during the later stages. This finding indicates that the dynamic allocation of cognitive resources is the key to improving gait-related movement based on rhythmic visual cues.

Visual or haptic feedback based on error modulation has been used to improve the effect of robot-assisted rehabilitation training. However, there are several investigations on the effects of error modulation-based visual and haptic feedback fusion strategies on motor learning and motivation. To observe the influence of different feedback fusion strategies on motor learning and motivation, a parallel controlled study was conducted, dividing 30 healthy subjects into three groups with similar skill levels. The no error modulation group received visual and haptic feedback without error modulation; the visual amplification haptic reduction group received visual error amplification combined with haptic error reduction, and the visual reduction haptic amplification (VRHA) group received visual error reduction combined with haptic error amplification. Each subject implemented a trajectory-tracking task with an upper limb rehabilitation robot. They went through baseline, training, assessment, and generalization tests and completed 340 consecutive tracking movements. To evaluate motor learning and motivation, the average tracking error, the root mean square (RMS) of surface electromyography (sEMG) signals, and the intrinsic motivation inventory scale were all examined. In the assessment tests, the average tracking error was significantly decreased in all three groups. In particular, the VRHA group had a larger reduction in average tracking error in the generalization test, lower RMS of sEMG signals both in the assessment and generalization tests and higher perceived competence in the assessment tests. The VRHA fusion strategy significantly improved the subjects’ motor learning and transfer ability, decreased muscle activation, and increased motor learning motivation. These findings may provide some new insights for multisensory feedback fusion technology in the application of rehabilitation robots.

Abstract Background Coronavirus disease 2019 (COVID-19) is associated with a high mortality rate, especially in patients with severe illness. We conducted a systematic review and meta-analysis to assess the potential predictors of mortality in patients with COVID-19. Methods PubMed, EMBASE, the Cochrane Library, and three electronic Chinese databases were searched from December 1, 2019 to April 29, 2020. Eligible studies reporting potential predictors of mortality in patients with COVID-19 were identified. Unadjusted prognostic effect estimates were pooled using the random-effects model if data from at least two studies were available. Adjusted prognostic effect estimates were presented by qualitative analysis. Results Thirty-six observational studies were identified, of which 27 were included in the meta-analysis. A total of 106 potential risk factors were tested, and the following important predictors were associated with mortality: advanced age, male sex, current smoking status, preexisting comorbidities (especially chronic kidney, respiratory, and cardio-cerebrovascular diseases), symptoms of dyspnea, complications during hospitalization, corticosteroid therapy and a severe condition. Additionally, a series of abnormal laboratory biomarkers of hematologic parameters, hepatorenal function, inflammation, coagulation, and cardiovascular injury were also associated with fatal outcome. Conclusion We identified predictors of mortality in patients with COVID-19. These findings could help healthcare providers take appropriate measures and improve clinical outcomes in such patients.

Linezolid is an oxazolidinone antibacterial drug, and its therapeutic drug monitoring and individualized treatment have been challenged since its approval. With the in-depth clinical research of linezolid, we have changed our attitude toward its therapeutic drug monitoring and our view of individualized treatment. On the basis of summarizing the existing clinical studies, and based on the practical experience of each expert in their respective professional fields, we have formed this expert consensus. Our team of specialists is a multidisciplinary team that includes pharmacotherapists, clinical pharmacology specialists, critical care medicine specialists, respiratory specialists, infectious disease specialists, emergency medicine specialists and more. We are committed to the safe and effective use of linezolid in patients in need, and the promotion of its therapeutic drug monitoring.

It is challenging to quantify anisotropic diffusion in biological systems. Here the authors report light-sheet imaging-based Fourier transform fluorescence recovery after photobleaching (LiFT-FRAP) to noninvasively determine 3D diffusion tensors of various biomolecules at physiological diffusivity.

Robot-assisted rehabilitation therapy has been proven to effectively improve upper-limb motor function in stroke patients. However, most current rehabilitation robotic controllers will provide too much assistance force and focus only on the patient’s position tracking performance while ignoring the patient’s interactive force situation, resulting in the inability to accurately assess the patient’s true motor intention and difficulty stimulating the patient’s initiative, thus negatively affecting the patient’s rehabilitation outcome. Therefore, this paper proposes a fuzzy adaptive passive (FAP) control strategy based on subjects’ task performance and impulse. To ensure the safety of subjects, a passive controller based on the potential field is designed to guide and assist patients in their movements, and the stability of the controller is demonstrated in a passive formalism. Then, using the subject’s task performance and impulse as evaluation indicators, fuzzy logic rules were designed and used as an evaluation algorithm to quantitively assess the subject’s motor ability and to adaptively modify the stiffness coefficient of the potential field and thus change the magnitude of the assistance force to stimulate the subject’s initiative. Through experiments, this control strategy has been shown to not only improve the subject’s initiative during the training process and ensure their safety during training but also enhance the subject’s motor learning ability.

BackgroundPosaconazole is confirmed to be more effective for preventing invasive fungal infections (IFIs) than first-generation triazoles (fluconazole and itraconazole), but its economic value has not been comprehensively evaluated in China. This study compared the cost-effectiveness of these two antifungal prophylaxis regimens in hematological-malignancy patients at high risk for IFIs from the Chinese healthcare perspective.MethodsA hybrid decision tree and Markov model were built using published data to estimate the total costs and quality-adjusted life-years (QALYs) of antifungal prophylaxis with posaconazole oral suspension and first-generation triazoles. Regimens with an incremental cost-effectiveness ratio (ICER) lower than the threshold of willingness to pay (WTP) were considered cost-effective. One-way and probabilistic sensitivity analyses were performed to assess model robustness. The regional imbalance of economic development and the tablet formulation of posaconazole were considered in the scenario analyses.ResultsIn the base-case analysis, posaconazole oral suspension provided an additional 0.109 QALYs at an incremental cost of $954.7, yielding an ICER of $8,784.4/QALY, below the national WTP threshold of $31,315/QALY. One-way and probabilistic sensitivity analyses showed that the results were robust. Scenario analyses showed that the base-case ICER was consistently below the WTP thresholds of all 31 Chinese provinces, with the likelihood of posaconazole being cost-effectiveness ranging from 78.1 to 99.0%. When the posaconazole oral suspension was replaced by the tablet formulation, the ICER increased to $29,214.1/QALY, still below the national WTP threshold and WTP thresholds of 12 provinces.ConclusionsPosaconazole oral suspension is a highly cost-effective regimen for preventing IFI in high-risk hematological-malignancy patients from the Chinese healthcare perspective. Posaconazole tablets may also be considered in some high-income regions of China.

Objectives: A systematic review and meta-analysis were conducted to re-assess the efficacy and safety of daptomycin compared with linezolid treatment for vancomycin-resistant enterococcal (VRE) bacteraemia and to explore whether high-dose daptomycin is beneficial. Methods: PubMed, EMBASE, the Cochrane Library, and meeting abstracts were searched from inception to February 2019. Studies evaluating daptomycin and linezolid treatment for VRE bacteraemia were included. Results: Twenty-two observational studies were identified. A non-significant higher mortality (OR 1.27; 95% CI 0.99–1.63) and significantly lower risk of thrombocytopenia (OR 0.78; 95% CI 0.61–0.99) were found with daptomycin compared with linezolid treatment. Clinical response (OR 0.88; 95% CI 0.59–1.33), microbiological cure (OR 0.82; 95% CI 0.53–1.28), recurrence of bacteraemia (OR 0.96; 95% CI 0.70–1.32), and risk of creatine kinase elevation (OR 0.82; 95% CI 0.46–1.47) were similar for the two agents. In the subgroup analysis of studies focusing on high-dose daptomycin treatment, similar mortality was observed (OR 0.92; 95% CI 0.46–1.84). Moreover, patients receiving daptomycin tended to show a higher clinical response (OR 1.61; 95% CI 0.37–7.09) and microbiological cure (OR 2.09; 95% CI 0.43–10.1) and a lower risk of bacteraemia relapse (OR 0.47; 95% CI 0.15–1.45), although the difference was not significant. Conclusions: Compared with linezolid treatment, daptomycin treatment showed comparable clinical and microbiological outcomes but a lower incidence of thrombocytopenia. Because of the dose-dependent effect that was observed, high-dose daptomycin should be considered for patients with VRE bacteraemia.

Electroencephalogram (EEG) was used to analyze the mechanisms and differences in brain neural activity of drivers in visual, auditory, and cognitive distracted vs. normal driving emergency braking conditions. A pedestrian intrusion emergency braking stimulus module and three distraction subtasks were designed in a simulated experiment, and 30 subjects participated in the study. The common activated brain regions during emergency braking in different distracted driving states included the inferior temporal gyrus, associated with visual information processing and attention; the left dorsolateral superior frontal gyrus, related to cognitive decision-making; and the postcentral gyrus, supplementary motor area, and paracentral lobule associated with motor control and coordination. When performing emergency braking under different driving distraction states, the brain regions were activated in accordance with the need to process the specific distraction task. Furthermore, the extent and degree of activation of cognitive function-related prefrontal regions increased accordingly with the increasing task complexity. All distractions caused a lag in emergency braking reaction time, with 107.22, 67.15, and 126.38 ms for visual, auditory, and cognitive distractions, respectively. Auditory distraction had the least effect and cognitive distraction the greatest effect on the lag.

Objective The use of the vancomycin minimum inhibitory concentration (MIC) as a prognostic predictor in patients with methicillin-susceptible Staphylococcus aureus (MSSA) has been debated in the last decade. We performed a systematic review and meta-analysis to investigate whether an elevated vancomycin MIC is associated with a worse prognosis for patients with MSSA bacteraemia.Design Systematic review and meta-analysis.Data sources PubMed, Embase and the Cochrane Library were searched from inception to December 2019.Eligibility criteria Randomised controlled trials or observational studies were considered eligible if they provided clinical outcomes of patients with MSSA bacteraemia, stratified by vancomycin MIC.Data synthesis Primary outcome was mortality. Secondary outcomes included septic thrombophlebitis, persistent bacteraemia and complicated bacteraemia. Pooled ORs and 95% CIs were calculated. Subgroup analyses included the susceptibility testing method.Results Fifteen observational studies were included. Bacteraemia due to MSSA isolates with high vancomycin MICs was associated with higher mortality than isolates with low MICs (OR 1.44; 95% CI 1.12 to 1.84; I2=40.3%). Additionally, significantly greater septic thrombophlebitis (OR 3.16; 95% CI 1.11 to 9.00; I2=58.6%) and a trend towards more persistent bacteraemia (OR 1.79; 95% CI 0.97 to 3.31; I2=0%) were observed in patients with high vancomycin MICs than in patients with low MICs. Differences in complicated bacteraemia were not significant. Similar findings were obtained in subgroup analyses using Etest. However, significant differences in outcomes were not observed between the high and low vancomycin MICs detected using broth microdilution.Conclusion The available data suggest an association between elevated vancomycin MICs detected using Etest and adverse clinical outcomes for patients with MSSA bacteraemia. Future studies should validate these findings and explore the potential mechanisms.PROSPERO registration number CRD42018090547.

The upper-limb rehabilitation robots can be developed as an efficient tool for motor function assessments. Circle-drawing has been used as a specific task for robot-based motor function measurement. The upper-limb movement-related kinematic and kinetic parameters measured by motion and force sensors embedded in the rehabilitation robots have been widely studied. However, the muscle synergies characterized by multiple surface electromyographic (sEMG) signals in upper limbs during human-robot interaction (HRI) with circle-drawing movements are rarely investigated. In this research, the robot-assisted and constrained circle-drawing movements for upper limb were used to increase the consistency of muscle synergy features. Both clockwise and counterclockwise circle-drawing tasks were implemented by all healthy subjects using right hands. The sEMG signals were recorded from six muscles in upper limb, and nonnegative matrix factorization (NMF) analysis was utilized to obtain muscle synergy information. Both synergy pattern and activation coefficient were calculated to represent the spatial and temporal features of muscle synergies, respectively. The results obtained from the experimental study confirmed that high structural similarity of muscle synergies was found among the subjects during HRI with circle-drawing movement by healthy subjects, which indicates healthy people may share a common underlying muscle control mechanism during constrained upper-limb circle-drawing movement. This study indicates the muscle synergy analysis during the HRI with constrained circle-drawing movement could be considered as a task for upper-limb motor function assessment.

Based on evidence from the previous research in rehabilitation robot control strategies, we found that the common feature of the effective control strategies to promote subjects’ engagement is creating a reward–punishment feedback mechanism. This article proposes a reward–punishment feedback control strategy based on energy information. Firstly, an engagement estimated approach based on energy information is developed to evaluate subjects’ performance. Secondly, the estimated result forms a reward–punishment term, which is introduced into a standard model-based adaptive controller. This modified adaptive controller is capable of giving the reward–punishment feedback to subjects according to their engagement. Finally, several experiments are implemented using a wrist rehabilitation robot to evaluate the proposed control strategy with 10 healthy subjects who have not cardiovascular and cerebrovascular diseases. The results of these experiments show that the mean coefficient of determination ( R 2 ) of the data obtained by the proposed approach and the classical approach is 0.7988, which illustrate the reliability of the engagement estimated approach based on energy information. And the results also demonstrate that the proposed controller has great potential to promote patients’ engagement for wrist rehabilitation.

Abstract Background Antistaphylococcal penicillins (ASPs) and cefazolin have become the most frequent choices for the treatment of methicillin-susceptible Staphylococcus aureus (MSSA) infections. However, the best therapeutic agent to treat MSSA bacteremia remains to be established. Methods We conducted a systematic review and meta-analysis to evaluate the efficacy and safety of these two regimens for the treatment of MSSA bacteremia. PubMed, EMBASE and the Cochrane Library from inception to February 2018 were searched. The primary outcome was mortality. The secondary outcomes included treatment failure, recurrence of bacteremia, adverse effects (AEs) and discontinuation due to AEs. Data were extracted and pooled odds ratios (ORs) and 95% confidence intervals (CIs) were calculated. Results A total of ten observational studies met the inclusion criteria. The results indicate that compared to ASPs, cefazolin was associated with significant reduction in mortality (OR, 0.69; 95% CI, 0.58 to 0.82; I2 = 3.4%) and clinical failure (OR, 0.56; 95% CI, 0.37 to 0.85; I2 = 44.9%) without increasing the recurrence of bacteremia (OR, 1.12; 95% CI, 0.94 to 1.34; I2 = 0%). There were no significant differences for the risk of anaphylaxis (OR, 0.91; 95% CI, 0.36 to 2.99; I2 = 0%) or hematotoxicity (OR, 0.56; 95% CI, 0.17 to 1.88; I2 = 0%). However, nephrotoxicity (OR, 0.36; 95% CI, 0.16 to 0.81; I2 = 0%) and hepatotoxicity (OR, 0.12; 95% CI, 0.04 to 0.41; I2 = 0%) were significantly lower in the cefazolin group. Moreover, cefazolin was associated with lower probability of discontinuation due to AEs compared with the ASPs (OR, 0.24; 95% CI, 0.12 to 0.48; I2 = 18%). Conclusion The results of present study favor the application of cefazolin and should be regarded as important evidence to help make clinical decisions in choosing a treatment option for treating MSSA bacteremia.

In this paper, we present a novel muscle synergy extraction method based on multivariate curve resolution–alternating least squares (MCR-ALS) to overcome the limitation of the nonnegative matrix factorization (NMF) method for extracting non-sparse muscle synergy, and we study its potential application for evaluating motor function of stroke survivors. Nonnegative matrix factorization (NMF) is the most widely used method for muscle synergy extraction. However, NMF is susceptible to components’ sparseness and usually provides inferior reliability, which significantly limits the promotion of muscle synergy. In this study, MCR-ALS was employed to extract muscle synergy from electromyography (EMG) data. Its performance was compared with two other matrix factorization algorithms, NMF and self-modeling mixture analysis (SMMA). Simulated data sets were utilized to explore the influences of the sparseness and noise on the extracted synergies. As a result, the synergies estimated by MCR-ALS were the most similar to true synergies as compared with SMMA and NMF. MCR-ALS was used to analyze the muscle synergy characteristics of upper limb movements performed by healthy (n = 11) and stroke (n = 5) subjects. The repeatability and intra-subject consistency were used to evaluate the performance of MCR-ALS. As a result, MCR-ALS provided much higher repeatability and intra-subject consistency as compared with NMF, which were important for the reliability of the motor function evaluation. The stroke subjects had lower intra-subject consistency and seemingly had more synergies as compared with the healthy subjects. Thus, MCR-ALS is a promising muscle synergy analysis method for motor function evaluation of stroke patients.

Surface electromyography (sEMG) sensors are widely used in the fields of ergonomics, sports science, and medical research. However, current sEMG sensors cannot recognize the various exercise intensities efficiently because of the strain interference, low conductivity, and poor skin-conformability of their electrodes. Here, we present a highly conductive, strain-insensitive, and low electrode−skin impedance elastic sEMG electrode, which consists of a three-layered structure (polydimethylsiloxane/galinstan + polydimethylsiloxane/silver-coated nickel + polydimethylsiloxane). The bottom layer of the electrode consists of vertically conductive magnetic particle paths, which are insensitive to stretching strain, collect sEMG charge from human skin, and finally transfer it to processing circuits via an intermediate layer. Our skin-friendly electrode exhibits high conductivity (0.237 and 1.635 mΩ·cm resistivities in transverse and longitudinal directions, respectively), low electrode−skin impedance (47.23 kΩ at 150 Hz), excellent strain-insensitivity (10% change of electrode−skin impedance within the 0−25% strain range), high fatigue resistance (>1500 cycles), and good conformability with skin. During various exercise intensities, the signal-to-noise ratio (SNR) of our electrode increased by 22.53 dB, which is 206% and 330% more than that of traditional Ag/AgCl and copper electrode, respectively. The ability of our electrode to efficiently recognize various exercise intensities confirms its great application potential for the field of sports health.

Recently, using the patient's genotype to guide warfarin dosing has gained interest; however, whether pharmacogenetics-based dosing (PD) improves clinical outcomes compared to conventional dosing (CD) remains unclear. Thus, we performed a meta-analysis to evaluate these two strategies.The PubMed, Embase, Cochrane Library, China National Knowledge Infrastructure (CNKI), Chinese VIP and Chinese Wan-fang databases were searched. The Cochrane Collaboration's tool was used to assess the risk of bias in randomized controlled trials (RCTs). The primary outcome was time within the therapeutic range (TTR); the secondary end points were the time to maintenance dose and time to first therapeutic international normalized ratio (INR), an INR greater than 4, adverse events, major bleeding, thromboembolism and death from any cause.A total of 11 trials involving 2,678 patients were included in our meta-analysis. The results showed that PD did not improve the TTR compared to CD, although PD significantly shortened the time to maintenance dose (MD = -8.80; 95% CI: -11.99 to -5.60; P

This paper proposes a structured model for the identification of green tea, as well as tracing its geographical origins. Considering that the features of different types of green tea are similar under THz time-domain spectroscopy, we designed a program to perform principal component analysis (PCA) of the spectroscopic data of various green tea samples and to determine the data sequences of principal components. We then established a training set for the principal components to train a support vector machine (SVM) model via a genetic algorithm (GA). We used this model to optimize the parameters and develop a GA-based SVM model with an identification rate of 96.25% for the tested samples. Taken together, our results confirm that THz time-domain spectroscopy combined with GA-SVM can be effectively applied to rapidly identify types of green tea with different geographical origins.

Terahertz (THz) time-domain spectroscopy (TDS) imaging is considered a nondestructive evaluation method for composite materials used for examining various defects of carbon fiber reinforced polymer (CFRP) composites and fire-retardant coatings in the reflective imaging modality. We demonstrate that hidden defects simulated by Teflon artificial inserts are imaged clearly in the perpendicular polarization mode. The THz TDS technique is also used to measure the thickness of thin fire-retardant coatings on CFRP composites with a typical accuracy of about 10 micrometers. In addition, coating debonding is successfully imaged based on the time-delay difference of the time-domain waveforms between closely adhered and debonded sample locations.