Ureido-Ionic Liquid Mediated Conductive Hydrogel: Superior Integrated Properties for Advanced Biosensing Applications.

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.

An Improved SSVEP-based Brain-Computer Interface with Low Contrast Visual Stimulation and its Application in UAV Control.

Efficient communication and regulation are crucial for advancing brain-computer interfaces (BCIs), with the steady-state visual evoked potential (SSVEP) paradigm demonstrating high accuracy and information transfer rates. However, the conventional SSVEP paradigm encounters challenges related to visual occlusion and fatigue. In this study, we propose an improved SSVEP paradigm that addresses these issues by lowering the contrast of visual stimuli. visual stimulation. The improved paradigms outperform the traditional paradigm in the experiments, significantly reducing the visual stimulation of the SSVEP paradigm. Furthermore, we apply this enhanced paradigm to a BCI navigation system, enabling two-dimensional navigation of Unmanned Aerial Vehicles (UAVs) through a first-person perspective. Experimental results indicate the enhanced SSVEP-based BCI system's accuracy in performing navigation and search tasks. Our findings highlight the feasibility of the enhanced SSVEP paradigm in mitigating visual occlusion and fatigue issues, presenting a more intuitive and natural approach for BCIs to control external equipment.

Upper limb motor assessment for stroke with force, muscle activation and interhemispheric balance indices based on sEMG and fNIRS.

Introduction: Upper 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. Methods: We 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). Results: The 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 < 0.05). Moreover, CV, SSI and LI in PMC were also significantly different between affected and unaffected upper limb movements (p < 0.05). Furthermore, a linear regression model was used to predict the value of the Fugl-Meyer score of upper limb (FMul) (R2 = 0.860, p < 0.001). Discussion: This study established a linear regression model using force, CV, and LI features to predict FMul scale values, which suggests that the combination of force, sEMG and fNIRS hold promise as a novel method for assessing stroke rehabilitation.

Detoxification and underlying mechanisms towards toxic alkaloids by Traditional Chinese Medicine processing: A comprehensive review.

BACKGROUND: Alkaloids have attracted enduring interest worldwide due to their remarkable therapeutic effects, including analgesic, anti-inflammatory, and anti-tumor properties, thus offering a rich source for lead compound design and new drug discovery. However, some of these alkaloids possess intrinsic toxicity. Processing (Paozhi) is a pre-treatment step before the application of herbal medicines in traditional Chinese medicine (TCM) clinics, which has been employed for centuries to mitigate the toxicity of alkaloid-rich TCMs. PURPOSE: To explore the toxicity phenotypes, chemical basis, mode of action, detoxification processing methods, and underlying mechanisms, we can gain crucial insights into the safe and rational use of these toxic alkaloid-rich herbs. Such insights have the great potential to offer new strategies for drug discovery and development, ultimately improving the quality of life for millions of people. METHODS: Literatures published or early accessed until December 31, 2023, were retrieved from databases including PubMed, Web of Science, and CNKI. The following keywords, such as "toxicity", "alkaloid", "detoxification", "processing", "traditional Chinese medicine", "medicinal plant", and "plant", were used in combination or separately for screening. RESULTS: Toxicity of alkaloids in TCM includes hepatotoxicity, nephrotoxicity, neurotoxicity, cardiotoxicity, and other forms of toxicity, primarily induced by pyrrolizidines, quinolizidines, isoquinolines, indoles, pyridines, terpenoids, and amines. Factors such as whether the toxic-alkaloid enriched part is limited or heat-sensitive, and whether toxic alkaloids are also therapeutic components, are critical for choosing appropriate detoxification processing methods. Mechanisms of alkaloid detoxification includes physical removal, chemical decomposition or transformation, as well as biological modifications. CONCLUSION: Through this exploration, we review toxic alkaloids and the mechanisms underlying their toxicity, discuss methods to reduce toxicity, and unravel the intricate mechanisms behind detoxification. These offers insights into the quality control of herbs containing toxic alkaloids, safe and rational use of alkaloid-rich TCMs in clinics, new strategies for drug discovery and development, and ultimately helping improve the quality of life for millions of people.

Short Step Length Estimation for Parkinson's Disease Patients by Using Fusion Data From Camera-IMU in Smart Glasses.

Shortened step length is a prominent motor abnormality in Parkinson's disease (PD) patients. Current methods for estimating short step length have the limitation of relying on laboratory scenarios, wearing multiple sensors, and inaccurate estimation results from a single sensor. In this paper, we proposed a novel method for estimating short step length for PD patients by fusing data from camera and inertial measurement units in smart glasses. A simultaneous localization and mapping technique and acceleration thresholding-based step detection technique were combined to realize the step length estimation. Two sets of experiments were conducted to demonstrate the performance of our method. In the first set of experiments with 12 healthy subjects, the proposed method demonstrated an average error of 8.44% across all experiments including six fixed step lengths below 30 cm. The second set of straightly walking experiments were implemented with 12 PD patients, the proposed method exhibited an average error of 4.27% compared to a standard gait evaluation technique in total walking distance. Notably, among the results of step lengths below 40 cm, our method agreed with the standard technique (R 2=0.8659). This study offers a promising approach for estimating short step length for PD patients during smart glasses-based gait training.

Effects of rhythmic visual cues on cortical activation and functional connectivity features during stepping: an fNIRS study.

Introduction: Rhythmic 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. Methods: We 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, ß-values, and functional connectivity (FC) between channels. Results: The results showed that, the RVC conditions revealed lower HbO responses compared to the NRVC conditions during the preparation and early stepping. Correspondingly, the ß-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. Discussion: In 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.

[Research on mode adjustment control strategy of upper limb rehabilitation robot based on fuzzy recognition of interaction force].

In the process of robot-assisted training for upper limb rehabilitation, a passive training strategy is usually used for stroke patients with flaccid paralysis. In order to stimulate the patient's active rehabilitation willingness, the rehabilitation therapist will use the robot-assisted training strategy for patients who gradually have the ability to generate active force. This study proposed a motor function assessment technology for human upper-limb based on fuzzy recognition on interaction force and human-robot interaction control strategy based on assistance-as-needed. A passive training mode based on the calculated torque controller and an assisted training mode combined with the potential energy field were designed, and then the interactive force information collected by the three-dimensional force sensor during the training process was imported into the fuzzy inference system, the degree of active participation σ was proposed, and the corresponding assisted strategy algorithms were designed to realize the adaptive adjustment of the two modes. The significant correlation between the degree of active participation σ and the surface electromyography signals (sEMG) was found through the experiments, and the method had a shorter response time compared to a control strategy that only adjusted the mode through the magnitude of interaction force, making the robot safer during the training process.

MCR-ALS-based muscle synergy extraction method combined with LSTM neural network for motion intention detection.

Introduction: The 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. Methods: In 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. Results: The 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. Discussion: This 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.

Using different matrix factorization approaches to identify muscle synergy in stroke survivors.

Over the past several decades, many scholars have investigated muscle synergy as a promising tool for evaluating motor function. However, it is challenging to obtain favorable robustness using the general muscle synergy identification algorithms, namely non-negative matrix factorization (NMF), independent component analysis (ICA), and factor analysis (FA). Some scholars have proposed improved muscle synergy identification algorithms to overcome the shortcomings of these approaches, such as singular value decomposition NMF (SVD-NMF), sparse NMF (S-NMF), and multivariate curve resolution-alternating least squares (MCR-ALS). However, performance comparisons of these algorithms are seldom conducted. In this study, experimental electromyography (EMG) data collected from healthy individuals and stroke survivors were applied to assess the repeatability and intra-subject consistency of NMF, SVD-NMF, S-NMF, ICA, FA, and MCR-ALS. MCR-ALS presented higher repeatability and intra-subject consistencies than the other algorithms. More synergies and lower intra-subject consistencies were observed in stroke survivors than in healthy individuals. Thus, MCR-ALS is considered a favorable muscle synergy identification algorithm for patients with neural system disorders.

Prevalence of inappropriate use of nirmatrelvir-ritonavir antiviral therapy in hospitalized patients: A multi-centre retrospective study in China.

BACKGROUND: Nirmatrelvir-ritonavir (NMVr) is a recently developed antiviral agent for treating coronavirus disease 2019 (COVID-19); however, data describing its appropriate use are scarce. This study examined the prevalence of inappropriate use of NMVr in a Chinese hospital setting. METHODS: A multi-centre retrospective chart review was performed for all hospitalized patients who received NMVr between 15 December 2022 and 15 February 2023 in four university-affiliated hospitals in Hangzhou, China. A multi-disciplinary team of experts developed the evaluation criteria. A group of senior clinical pharmacists examined and verified the suitability of NMVr prescriptions. RESULTS: In total, 247 patients received NMVr during the study period, of which 13.4% (n=31) met all the criteria for appropriate use of NMVr. The main types of inappropriate use of NMVr were delayed initiation of treatment (n=147, 59.5%), no dose adjustment for moderate renal impairment (n=46, 18.6%), use in patients with severe-to-critical COVID-19 (n=49, 19.8%), presence of contra-indicated drug‒drug interactions with other medications (n=36, 14.6%), and prescription for patients without a confirmed diagnosis of COVID-19 (n=36, 14.6%). CONCLUSIONS: The proportion of inappropriate use of NMVr was particularly high in the Chinese hospital setting, highlighting the urgent need to improve the appropriate use of NMVr.

Allocation of cognitive resources in cognitive processing of rhythmic visual stimuli before gait-related motor initiation.

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.

Fuzzy Adaptive Passive Control Strategy Design for Upper-Limb End-Effector Rehabilitation Robot.

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.

Emergency Braking Evoked Brain Activities during Distracted Driving.

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.

Expert consensus statement on therapeutic drug monitoring and individualization of linezolid.

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.

Cost-Effectiveness of Posaconazole vs. First-Generation Triazoles for the Prevention of Invasive Fungal Infections Among High-Risk Patients With Hematological Malignancies in China.

Background: Posaconazole 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. Methods: A 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. Results: In 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. Conclusions: Posaconazole 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.

A pharmacoeconomic evaluation of the pharmacotherapeutic options for painful diabetic neuropathy.

INTRODUCTION: Painful diabetic neuropathy (PDN) is a high incidence and severe complication of diabetes mellitus, significantly compromising patients' quality of life and causing tremendous economic burden. Considering drug costs becomes part of treatment decisions, with the growing choice of monotherapy or combination treatment strategies for PDN treatment. AREAS COVERED: This systematic review aims to identify the cost-effectiveness of pharmacotherapies in PDN, summarize key findings, and assess the quality of studies to inform healthcare resource allocation decisions and future research. Economic evaluations were identified by searching PubMed, Web of Science, Scopus and health technology assessment (HTA) databases, as well as screening reference lists of previously identified studies. Relevant data was extracted, and the CHEERS checklist was used to assess the quality of the studies. EXPERT OPINION: Collectively, the findings indicate that more pharmacoeconomics research is urgently needed to directly compare high-quality research for PDN combination medication/sequential treatment, and which is performed from a societal perspective. Simultaneously, to strengthen the reliability of the analysis, metrics such as adherence, incidence of adverse drug reactions, and pain levels utility value should be examined to verify the robustness of the basic results.

Effect of renal function on the risk of thrombocytopaenia in patients receiving linezolid therapy: A systematic review and meta-analysis.

AIMS: The association of renal function and linezolid-induced thrombocytopaenia (LIT) remains controversial. We performed a meta-analysis to determine whether impaired renal function is associated with an increased LIT risk. METHODS: We conducted a systematic search of PubMed, EMBASE and the Cochrane Library from inception to February 2021 for eligible studies evaluating the relationship between renal function and LIT. Indicators of renal function included renal impairment (RI), severe RI, haemodialysis status, creatinine clearance rate (Ccr) and estimated glomerular filtration rate (eGFR). Unadjusted and adjusted estimates and 95% confidence intervals (CIs) were calculated separately using a random-effect model. RESULTS: A total of 24 studies with 3580 patients were included in the meta-analysis. RI patients had an increased LIT risk compared to non-RI patients in both the unadjusted (OR 3.54; 95% CI 2.27, 5.54; I2 = 77.7%) and adjusted analyses (OR 2.51; 95% CI 1.82, 3.45; I2 = 17.9%). This association persisted in the subset of studies involving only patients receiving a fixed conventional dose (600 mg every 12 h) and other subgroup analyses by ethnicity, sample size and study quality. Moreover, the LIT risk was significantly higher in patients with severe RI and haemodialysis than in patients without severe RI and haemodialysis. The eGFR and Ccr were significantly lower in LIT patients than in non-LIT patients. CONCLUSIONS: Impaired renal function is associated with an increased risk of LIT. A reduced linezolid dose may be considered in RI patients at a low risk of treatment failure, ideally guided by therapeutic drug monitoring.

Incidence, risk factors and mortality of invasive pulmonary aspergillosis in patients with influenza: A systematic review and meta-analysis.

BACKGROUND: An increasing number of cases of invasive pulmonary aspergillosis (IPA) complicating influenza have been described. We performed a meta-analysis to estimate the incidence, risk factors and outcomes of IPA in patients with influenza. METHODS: A systematic search was conducted in the PubMed, EMBASE and Cochrane Library databases from their inception to 31 August 2021 for eligible studies. Data on the incidence and risk factors of and mortality due to IPA in influenza patients were pooled using a random-effects model. Sensitivity analyses restricted to severe influenza requiring intensive care unit (ICU) support and multiple subgroup analyses were performed. RESULTS: Fourteen studies involving 6024 hospitalised patients with influenza were included. IPA was estimated to occur in 10% of influenza patients, with a mortality rate of 52%. Similar incidence (11%) and mortality (54%) estimates for IPA were observed in the sensitivity analysis including severe cases requiring ICU support. Subgroup analysis by geographical location showed a similar IPA rate between European (10%) and non-European (11%) studies. The IPA rate in the subset of nine studies using the modified AspICU criteria was 13%. Most subgroup analyses showed ≥50% mortality in IPA patients. Several predictors for IPA susceptibility were identified, including male sex, smoking history, chronic lung disease, influenza A (H1N1), severe conditions requiring supportive therapy, corticosteroid use before admission, solid organ transplant and haematological malignancy. CONCLUSIONS: The IPA is common in individuals with severe influenza, and the prognosis is particularly poor. Influenza patients, especially those with high-risk factors, should be thoroughly screened for IPA.

Upper-Limb Muscle Synergy Features in Human-Robot Interaction with Circle-Drawing Movements.

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.

Predictors of mortality in patients with coronavirus disease 2019: a systematic review and meta-analysis.

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.