Monitoring the remediation of groundwater polluted by MSW landfill leachates by activated carbon and zeolite with spectral induced polarization technique.

The municipal solid waste (MSW) landfill in Hangzhou, China utilized zeolite and activated carbon (AC) as permeable reactive barrier (PRB) fill materials to remediate groundwater contaminated with MSW leachates containing ammonium, chemical oxygen demand (COD), and heavy metals. The spectral induced polarization (SIP) technique was chosen for monitoring the PRB because of its sensitivity to pore fluid chemistry and mineral-fluid interface composition. During the experiment, authentic groundwater collected from the landfill site was used to permeate two columns filled with zeolite and AC, and the SIP responses were measured at the inlet and outlet over a frequency range of 0.01-1000 Hz. The results showed that zeolite had a higher adsorption capacity for COD (7.08 mg/g) and ammonium (9.15 mg/g) compared to AC (COD: 2.75 mg/g, ammonium: 1.68 mg/g). Cation exchange was found to be the mechanism of ammonium adsorption for both zeolite and AC, while FTIR results indicated that π-complexation, π-π interaction, and electrostatic attraction were the main mechanisms of COD adsorption. The Cole-Cole model was used to fit the SIP responses and determine the relaxation time (τ) and normalized chargeability (mn). The calculated characteristic diameters of zeolite and AC based on the Schwarz equation and relaxation time (τ) matched the pore sizes observed from SEM and MIP, providing valuable information on contaminant distribution. The mn of zeolite was positively linear with adsorbed ammonium (R2 = 0.9074) and COD (R2 = 0.8877), while the mn of AC was negatively linear with adsorbed ammonium (R2 = 0.8192) and COD (R2 = 0.7916), suggesting that mn could serve as a surrogate for contaminant saturation. The laboratory-based real-time non-invasive SIP results showed good performance in monitoring saturation and provide a strong foundation for future field PRB monitoring.

Semi-Supervised Representation Learning for Segmentation on Medical Volumes and Sequences.

Benefiting from the massive labeled samples, deep learning-based segmentation methods have achieved great success for two dimensional natural images. However, it is still a challenging task to segment high dimensional medical volumes and sequences, due to the considerable efforts for clinical expertise to make large scale annotations. Self/semi-supervised learning methods have been shown to improve the performance by exploiting unlabeled data. However, they are still lack of mining local semantic discrimination and exploitation of volume/sequence structures. In this work, we propose a semi-supervised representation learning method with two novel modules to enhance the features in the encoder and decoder, respectively. For the encoder, based on the continuity between slices/frames and the common spatial layout of organs across subjects, we propose an asymmetric network with an attention-guided predictor to enable prediction between feature maps of different slices of unlabeled data. For the decoder, based on the semantic consistency between labeled data and unlabeled data, we introduce a novel semantic contrastive learning to regularize the feature maps in the decoder. The two parts are trained jointly with both labeled and unlabeled volumes/sequences in a semi-supervised manner. When evaluated on three benchmark datasets of medical volumes and sequences, our model outperforms existing methods with a large margin of 7.3% DSC on ACDC, 6.5% on Prostate, and 3.2% on CAMUS when only a few labeled data is available. Further, results on the M&M dataset show that the proposed method yields improvement without using any domain adaption techniques for data from unknown domain. Intensive evaluations reveal the effectiveness of representation mining, and superiority on performance of our method. The code is available at https://github.com/CcchenzJ/BootstrapRepresentation.

Exoskeleton-Assisted Sit-to-Stand Training Improves Lower-Limb Function Through Modifications of Muscle Synergies in Subacute Stroke Survivors.

Abnormal muscle synergies during sit-to-stand (STS) transitions have been observed post-stroke, which are associated with deteriorated lower-limb function and mobility. Although exoskeletons have been used in restoring lower-limb function, their effects on muscle synergies and lower-limb motor recovery remain unclear. Here, we characterized normal muscle synergy patterns during STS activity in ten healthy adults as a reference, comparing with pathological muscle synergy patterns in ten participants with subacute stroke. Moreover, we assessed the effects of a 3-week exoskeleton-assisted STS training intervention on muscle synergies and clinical scores in seven stroke survivors. We also investigated correlations between neuromuscular complexity of muscle synergies and clinical scores. Our results showed that the STS task involved three motor modules representing distinct biomechanical functions among healthy subjects. In contrast, stroke participants showed 3 abnormal modules for the paretic leg and 2 modules for the non-paretic leg. After the intervention, muscle synergies partially shifted towards the normal pattern observed in healthy subjects on the paretic side. On the non-paretic side, the synergy modules increased to three and neuromuscular coordination improved. Furthermore, the significant intervention-induced increases in Fugl-Meyer Assessment of Lower Extremity and Berg Balance Scale scores were associated with improved muscle synergies on the non-paretic side. These results indicate that the paretic side demonstrates abnormal changes in muscle synergies post-stroke, while the non-paretic side can synergistically adapt to post-stroke biomechanical deviations. Our data show that exoskeleton-based training improved lower-limb function post-stroke by inducing modifications in muscle synergies.

Exoskeleton-Assisted Anthropomorphic Movement Training for the Upper Limb After Stroke: The EAMT Randomized Trial.

BACKGROUND: Robot-assisted arm training is generally delivered in the robot-like manner of planar or mechanical 3-dimensional movements. It remains unclear whether integrating upper extremity (UE) natural coordinated patterns into a robotic exoskeleton can improve outcomes. The study aimed to compare conventional therapist-mediated training to the practice of human-like gross movements derived from 5 typical UE functional activities managed with exoskeletal assistance as needed for patients after stroke. METHODS: In this randomized, single-blind, noninferiority trial, patients with moderate-to-severe UE motor impairment due to subacute stroke were randomly assigned (1:1) to receive 20 sessions of 45-minute exoskeleton-assisted anthropomorphic movement training or conventional therapy. Treatment allocation was masked from independent assessors, but not from patients or investigators. The primary outcome was the change in the Fugl-Meyer Assessment for Upper Extremity from baseline to 4 weeks against a prespecified noninferiority margin of 4 points. Superiority would be tested if noninferiority was demonstrated. Post hoc subgroup analyses of baseline characteristics were performed for the primary outcome. RESULTS: Between June 2020 and August 2021, totally 80 inpatients (67 [83.8%] males; age, 51.9±9.9 years; days since stroke onset, 54.6±38.0) were enrolled, randomly assigned to the intervention, and included in the intention-to-treat analysis. The mean Fugl-Meyer Assessment for Upper Extremity change in exoskeleton-assisted anthropomorphic movement training (14.73 points; [95% CI, 11.43-18.02]) was higher than that of conventional therapy (9.90 points; [95% CI, 8.15-11.65]) at 4 weeks (adjusted difference, 4.51 points [95% CI, 1.13-7.90]). Moreover, post hoc analysis favored the patient subgroup (Fugl-Meyer Assessment for Upper Extremity score, 23-38 points) with moderately severe motor impairment. CONCLUSIONS: Exoskeleton-assisted anthropomorphic movement training appears to be effective for patients with subacute stroke through repetitive practice of human-like movements. Although the results indicate a positive sign for exoskeleton-assisted anthropomorphic movement training, further investigations into the long-term effects and paradigm optimization are warranted. REGISTRATION: URL: https://www.chictr.org.cn; Unique identifier: ChiCTR2100044078.

Effects of repetitive peripheral magnetic stimulation for the upper limb after stroke: Meta-analysis of randomized controlled trials.

Introduction: Repetitive peripheral magnetic stimulation (rPMS) can stimulate profound neuromuscular tissues painlessly to evoke action potentials in motor axons and induce muscle contraction for treating neurological conditions. It has been increasingly used in stroke rehabilitation as an easy-to-administer approach for therapeutic neuromodulation. Objective: We performed this meta-analysis of randomized controlled trials to systematically evaluate the effects of rPMS for the upper limb in patients with stroke, including motor impairment, muscle spasticity, muscle strength, and activity limitation outcomes. Methods: The meta-analysis was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline. PubMed, EMBASE, Web of Science, Cochrane Library, and Physiotherapy Evidence Database (PEDro) were searched for articles published before June 2022. Forest plots were employed to estimate the pooled results of the included studies, and the I2 statistical analysis was used to identify the source of heterogeneity. Publication bias was examined by Egger's regression tests or visual inspection of the funnel plots. Results: The database searches yielded 1052 potential eligible literature; of them, five randomized controlled trials met the eligible criteria, involving a total of 188 participants. Patients in the rPMS group showed better improvement in motor impairment as measured by the FM-UE (MD: 5.39 [95% CI, 4.26 to 6.52]; P < 0.001; I2 = 0%) compared with the control group. Among the secondary outcomes, no difference was found in the improvement of muscle spasticity (SMD: 0.36 [95% CI, -0.05 to 0.77]; P = 0.08; I2 = 41%). There was a significant difference in the proximal (SMD: 0.58 [95% CI, 0.10 to 1.06]; P = 0.02; I2 = 0%) but not the distal muscle strength (SMD: 1.18 [95% CI, -1.00 to 3.36]; P = 0.29; I2 = 93%). Moreover, the activity limitation outcomes were significantly improved with rPMS intervention (SMD: 0.59 [95% CI, 0.08 to 1.10]; P = 0.02; I2 = 0%). Conclusion: This meta-analysis showed that rPMS might improve upper limb motor impairment, proximal muscle strength, and activity limitation outcomes but not muscle spasticity and distal strength in patients after stroke. Due to the limited number of studies, further randomized clinical trials are still warranted for more accurate interpretation and clinical recommendation.

Altered frontoparietal activity in acoustic startle priming tasks during reticulospinal tract facilitation: An fNIRS study.

Background: Because it is one of the important pathways for promoting motor recovery after cortical injury, the function of the reticulospinal tract (RST) has received increasing attention in recent years. However, the central regulatory mechanism of RST facilitation and reduction of apparent response time is not well understood. Objectives: To explore the potential role of RST facilitation in the acoustic startle priming (ASP) paradigm and observe the cortical changes induced by ASP reaching tasks. Methods: Twenty healthy participants were included in this study. The reaching tasks were performed with their left and right hands. Participants were instructed to get ready after the warning cue and complete the reach as soon as they heard the Go cue. Half of the testing trials were set as control trials with an 80-dB Go cue. The other half of the trials had the Go cue replaced with 114-dB white noise to evoke the StartleReact effect, inducing reticulospinal tract facilitation. The response of the bilateral sternocleidomastoid muscle (SCM) and the anterior deltoid was recorded via surface electromyography. Startle trials were labeled as exhibiting a positive or negative StartleReact effect, according to whether the SCM was activated early (30-130 ms after the Go cue) or late, respectively. Functional near-infrared spectroscopy was used to synchronously record the oxyhemoglobin and deoxyhemoglobin fluctuations in bilateral motor-related cortical regions. The ß values representing cortical responses were estimated via the statistical parametric mapping technique and included in the final analyses. Results: Separate analyses of data from movements of the left or right side revealed significant activation of the right dorsolateral prefrontal cortex during RST facilitation. Moreover, left frontopolar cortex activation was greater in positive startle trials than in control or negative startle trials during left-side movements. Furthermore, decreased activity of the ipsilateral primary motor cortex in positive startle trials during ASP reaching tasks was observed. Conclusion: The right dorsolateral prefrontal cortex and the frontoparietal network to which it belongs may be the regulatory center for the StartleReact effect and RST facilitation. In addition, the ascending reticular activating system may be involved. The decreased activity of the ipsilateral primary motor cortex suggests enhanced inhibition of the non-moving side during the ASP reaching task. These findings provide further insight into the SE and into RST facilitation.

Epidemiology of autism spectrum disorders: Global burden of disease 2019 and bibliometric analysis of risk factors.

Background: To explore the geographical pattern and temporal trend of autism spectrum disorders (ASD) epidemiology from 1990 to 2019, and perform a bibliometric analysis of risk factors for ASD. Methods: In this study, ASD epidemiology was estimated with prevalence, incidence, and disability-adjusted life-years (DALYs) of 204 countries and territories by sex, location, and sociodemographic index (SDI). Age-standardized rate (ASR) and estimated annual percentage change (EAPC) were used to quantify ASD temporal trends. Besides, the study performed a bibliometric analysis of ASD risk factors since 1990. Publications published were downloaded from the Web of Science Core Collection database, and were analyzed using CiteSpace. Results: Globally, there were estimated 28.3 million ASD prevalent cases (ASR, 369.4 per 100,000 populations), 603,790 incident cases (ASR, 9.3 per 100,000 populations) and 4.3 million DALYs (ASR, 56.3 per 100,000 populations) in 2019. Increases of autism spectrum disorders were noted in prevalent cases (39.3%), incidence (0.1%), and DALYs (38.7%) from 1990 to 2019. Age-standardized rates and EAPC showed stable trend worldwide over time. A total of 3,991 articles were retrieved from Web of Science, of which 3,590 were obtained for analysis after removing duplicate literatures. "Rehabilitation", "Genetics & Heredity", "Nanoscience & Nanotechnology", "Biochemistry & Molecular biology", "Psychology", "Neurosciences", and "Environmental Sciences" were the hotspots and frontier disciplines of ASD risk factors. Conclusions: Disease burden and risk factors of autism spectrum disorders remain global public health challenge since 1990 according to the GBD epidemiological estimates and bibliometric analysis. The findings help policy makers formulate public health policies concerning prevention targeted for risk factors, early diagnosis and life-long healthcare service of ASD. Increasing knowledge concerning the public awareness of risk factors is also warranted to address global ASD problem.

Sketch guided and progressive growing GAN for realistic and editable ultrasound image synthesis.

Ultrasound (US) imaging is widely used for anatomical structure inspection in clinical diagnosis. The training of new sonographers and deep learning based algorithms for US image analysis usually requires a large amount of data. However, obtaining and labeling large-scale US imaging data are not easy tasks, especially for diseases with low incidence. Realistic US image synthesis can alleviate this problem to a great extent. In this paper, we propose a generative adversarial network (GAN) based image synthesis framework. Our main contributions include: (1) we present the first work that can synthesize realistic B-mode US images with high-resolution and customized texture editing features; (2) to enhance structural details of generated images, we propose to introduce auxiliary sketch guidance into a conditional GAN. We superpose the edge sketch onto the object mask and use the composite mask as the network input; (3) to generate high-resolution US images, we adopt a progressive training strategy to gradually generate high-resolution images from low-resolution images. In addition, a feature loss is proposed to minimize the difference of high-level features between the generated and real images, which further improves the quality of generated images; (4) the proposed US image synthesis method is quite universal and can also be generalized to the US images of other anatomical structures besides the three ones tested in our study (lung, hip joint, and ovary); (5) extensive experiments on three large US image datasets are conducted to validate our method. Ablation studies, customized texture editing, user studies, and segmentation tests demonstrate promising results of our method in synthesizing realistic US images.

Regional Cardiac Motion Scoring With Multi-Scale Motion-Based Spatial Attention.

Regional cardiac motion scoring aims to classify the motion status of each myocardium segment into one of the four categories (normal, hypokinetic, akinetic, and dyskinetic) from multiple short-axis MR sequences. It is essential for prognosis and early diagnosis for various cardiac diseases. However, the complex motion procedure of the myocardium and the invisible pattern differences pose great challenges, leading to low performance for automatic methods. Most existing works mitigate the task by differentiating the normal motion patterns from the abnormal ones, without fine-grained motion scoring. We propose an effective method for the task of cardiac motion scoring by connecting a bottom-up and another top-down branch with a novel motion-based spatial attention module in multi-scale space. Specifically, we use the convolution blocks for low-level feature extraction that acts as a bottom-up mechanism, and the task of optical flow for explicit motion extraction that acts as a top-down mechanism for high-level allocation of spatial attention. To this end, a newly designed Multi-scale Motion-based Spatial Attention (MMSA) module is used as the pivot connecting the bottom-up part and the top-down part, and adaptively weight the low-level features according to the motion information. Experimental results on a newly constructed dataset of 1440 myocardium segments from 90 subjects demonstrate that the proposed MMSA can accurately analyze the regional myocardium motion, with accuracies of 79.3% for 4-way motion scoring, 89.0% for abnormality detection, and correlation of 0.943 for estimation of motion score index. This work has great potential for practical assessmentof cardiac motion function.

Kinematic Evaluation via Inertial Measurement Unit Associated with Upper Extremity Motor Function in Subacute Stroke: A Cross-Sectional Study.

Kinematic evaluation via portable sensor system has been increasingly applied in neurological sciences and clinical practice. However, conventional kinematic evaluation rarely extends the context beyond the motor impairment level. In addition, kinematic tasks with numerous items could be complex and time consuming that pose a burden to test applications and data processing. The study aimed to explore the correlation of finger-to-nose task (FNT) kinematics via Inertial Measurement Unit with upper limb motor function in subacute stroke. In this study, six FNT kinematic variables were used to measure movement time, smoothness, and velocity in 37 participants with subacute stroke. Upper limb motor function was evaluated with the Fugl-Meyer Assessment for Upper Extremity (FMA-UE), Action Research Arm Test (ARAT), and modified Barthel Index (MBI). As a result, mean velocity, peak velocity, and the number of movement units were associated with the clinical assessments. The multivariable linear regression models could estimate 55%, 51%, and 32% of variance in FMA-UE, ARAT, and MBI, respectively. In addition, age, gender, type of stroke, and paretic side had no significant effects on these associations. Results show that FNT kinematic variables measured via Inertial Measurement Unit are associated with upper extremity motor function in individuals with subacute stroke. The objective kinematic evaluation may be suitable for predicting clinical measures of motor impairment and capacity to understand upper extremity motor recovery and clinical decision making after stroke. This trial is registered with ChiCTR1900026656.

Preliminary Assessment of a Postural Synergy-Based Exoskeleton for Post-Stroke Upper Limb Rehabilitation.

Upper limb exoskeletons have drawn significant attention in neurorehabilitation because of the anthropomorphic mechanical structure analogous to human anatomy. Whereas, the training movements are typically unorganized because most exoskeletons ignore the natural movement characteristic of human upper limbs, particularly inter-joint postural synergy. This paper introduces a newly developed exoskeleton (Armule) for upper limb rehabilitation with a postural synergy design concept, which can reproduce activities of daily living (ADL) motion with the characteristics of human natural movements. The semitransparent active control strategy with the interactive force guidance and visual feedback ensured the active participation of users. Eight participants with hemiplegia due to a first-ever, unilateral stroke were recruited and included. They participated in exoskeleton therapy sessions for 4 weeks, with passive/active training under trajectories and postures with the characteristics of human natural movements. The primary outcome was the Fugl-Meyer Assessment for Upper Extremities (FMA-UE). The secondary outcomes were the Action Research Arm Test(ARAT), modified Barthel Index (mBI), and metric measured with the exoskeleton After the 4-weeks intervention, all subjects showed significant improvements in the following clinical measures: the FMA-UE (difference, 11.50 points, p = 0.002), the ARAT (difference, 7.75 points ), and the mBI (difference, 17.50 points, p = 0.003 ) score. Besides, all subjects showed significant improvements in kinematic and interaction force metrics measured with the exoskeleton. These preliminary results demonstrate that the Armule exoskeleton could improve individuals' motor control and ADL function after stroke, which might be associated with kinematic and interaction force optimization and postural synergy modification during functional tasks.

Robot-Assisted Arm Training in Stroke Individuals With Unilateral Spatial Neglect: A Pilot Study.

Background: Robot-assisted arm training (RAT) is an innovative exercise-based therapy that provides highly intensive, adaptive, and task-specific training, yet its effects for stroke individuals with unilateral spatial neglect remain to be explored. The study was aimed to investigate the effects of RAT on unilateral spatial neglect, arm motor function, activities of daily living, and social participation after stroke. Methods: In a pilot randomized controlled trial, individuals with unilateral spatial neglect after right hemisphere stroke were equally allocated to intervention group and control group, 45-min training daily, 5 days/week, for 4 weeks. Outcome measures included the Behavioral Inattention Test-conventional section (BIT-C), Catherine Bergego Scale (CBS), Fugl-Meyer Assessment for Upper Extremity (FMA-UE), Modified Barthel Index (MBI), and World Health Organization Disability Assessment Schedule Version 2.0 (WHODAS 2.0). Results: From November 2018 to February 2021, 20 stroke patients (mean age 47.40 ± 8.47) were enrolled in the study. Robot-assisted arm training was feasible and safe for individuals with unilateral spatial neglect. Both groups had significant improvements in all outcome measures. Participants assigned to RAT therapy had significantly greater improvements in BIT-C (difference, 7.70; 95% CI, 0.55-14.85, P = 0.04), FMA-UE (difference, 5.10; 95% CI, 1.52-8.68, P = 0.01), and WHODAS 2.0 (difference, -7.30; 95% CI, -12.50 to -2.10, P = 0.01). However, the change scores on CBS and MBI demonstrated no significance between the groups. Conclusion: Our findings provide preliminary support for introducing robot-assisted arm training to remediate unilateral spatial neglect after stroke. The training program focusing on neglect of contralateral space and affected upper extremity may be effective in neglect symptoms, motor function recovery, and social participation, while not generalizing into improvements in activities of daily living. Clinical Trial Registration: Chinese Clinical Trial Registry (http://www.chictr.org.cn/) on 17 October 2019, identifier: ChiCTR1900026656.

Exoskeleton-Assisted Anthropomorphic Movement Training (EAMT) for Poststroke Upper Limb Rehabilitation: A Pilot Randomized Controlled Trial.

OBJECTIVE: To investigate the feasibility of exoskeleton-assisted anthropomorphic movement training (EAMT) and its effects on upper extremity motor impairment, function, and kinematics after stroke. DESIGN: A single-blind pilot randomized controlled trial. SETTING: Stroke rehabilitation inpatient unit. PARTICIPANTS: Participants with a hemiplegia (N=20) due to a first-ever, unilateral, subacute stroke who had a score of 8-47 on the Fugl-Meyer Assessment for Upper Extremity (FMA-UE). INTERVENTIONS: The exoskeleton group received EAMT therapy that provided task-specific training under anthropomorphic trajectories and postures. The control group received conventional upper limb therapy. For both groups, therapy was delivered at the same intensity, frequency, and duration: 45 minutes daily, 5 days per week, for 4 weeks. MAIN OUTCOME MEASURES: Primary outcome: feasibility analysis. SECONDARY OUTCOMES: FMA-UE, Action Research Arm Test (ARAT), modified Barthel Index (MBI), and kinematic metrics during exoskeleton therapy. RESULTS: Twenty participants with subacute stroke were recruited and completed all therapy sessions. EAMT therapy was feasible and acceptable for the participants. The recruitment rate, retention rate, and number of therapists required for EAMT therapy were acceptable compared with other robotic trials. EAMT was determined to be safe, as no adverse event occurred except tolerable muscle fatigue in 2 participants. There were significant between-group differences in the change scores of FMA-UE (difference, 4.30 points; P=.04) and MBI (difference, 8.70 points; P=.03) in favor of EAMT therapy. No significant between-group difference was demonstrated for the change scores of ARAT (P=.18). Participants receiving EAMT showed significant improvements in kinematic metrics after treatment (P<.01). CONCLUSIONS: Our results indicate that EAMT is a feasible approach and may improve upper extremity motor impairment, activities of daily living, and kinematics after stroke. However, fully powered randomized controlled trials are warranted to confirm the results of this pilot study and explore the underlying mechanisms by which EAMT therapy might work.

Association Between Finger-to-Nose Kinematics and Upper Extremity Motor Function in Subacute Stroke: A Principal Component Analysis.

BACKGROUND: Kinematic analysis facilitates interpreting the extent and mechanisms of motor restoration after stroke. This study was aimed to explore the kinematic components of finger-to-nose test obtained from principal component analysis (PCA) and the associations with upper extremity (UE) motor function in subacute stroke survivors. METHODS: Thirty-seven individuals with subacute stroke and twenty healthy adults participated in the study. Six kinematic metrics during finger-to-nose task (FNT) were utilized to perform PCA. Clinical assessments for stroke participants included the Fugl-Meyer Assessment for Upper Extremity (FMA-UE), Action Research Arm Test (ARAT), and Modified Barthel Index (MBI). RESULTS: Three principal components (PC) accounting for 91.3% variance were included in multivariable regression models. PC1 (48.8%) was dominated by mean velocity, peak velocity, number of movement units (NMU) and normalized integrated jerk (NIJ). PC2 (31.1%) described percentage of time to peak velocity and movement time. PC3 (11.4%) profiled percentage of time to peak velocity. The variance explained by principal component regression in FMA-UE (R 2 = 0.71) were higher than ARAT (R 2 = 0.59) and MBI (R 2 = 0.29) for stroke individuals. CONCLUSION: Kinematic components during finger-to-nose test identified by PCA are associated with UE motor function in subacute stroke. PCA reveals the intrinsic association among kinematic metrics, which may add value to UE assessment and future intervention targeted for kinematic components for stroke individuals. CLINICAL TRIAL REGISTRATION: Chinese Clinical Trial Registry (http://www.chictr.org.cn/) on 17 October 2019, identifier: ChiCTR1900026656.

Action observation treatment-based exoskeleton (AOT-EXO) for upper extremity after stroke: study protocol for a randomized controlled trial.

BACKGROUND: Stroke produces multiple symptoms, including sensory, motor, cognitive and psychological dysfunctions, among which motor deficit is the most common and is widely recognized as a major contributor to long-term functional disability. Robot-assisted training is effective in promoting upper extremity muscle strength and motor impairment recovery after stroke. Additionally, action observation treatment can enhance the effects of physical and occupational therapy by increasing neural activation. The AOT-EXO trial aims to investigate whether action observation treatment coupled with robot-assisted training could enhance motor circuit activation and improve upper extremity motor outcomes. METHODS: The AOT-EXO trial is a multicentre, prospective, three-group randomized controlled trial (RCT). We will screen and enrol 132 eligible patients in the trial implemented in the Department of Rehabilitation Medicine of Tongji Hospital, Optical Valley Branch of Tongji Hospital and Hubei Province Hospital of Integrated Chinese & Western Medicine in Wuhan, China. Prior to study participation, written informed consent will be obtained from eligible patients in accordance with the Declaration of Helsinki. The enrolled stroke patients will be randomized to three groups: the CT group (conventional therapy); EXO group (exoskeleton therapy) and AOT-EXO group (action observation treatment-based exoskeleton therapy). The patients will undergo blinded assessments at baseline, post-intervention (after 4 weeks) and follow-up (after 12 weeks). The primary outcome will be the Fugl-Meyer Assessment for Upper Extremity (FMA-UE). Secondary outcomes will include the Action Research Arm Test (ARAT), modified Barthel Index (MBI), kinematic metrics assessed by inertial measurement unit (IMU), resting motor threshold (rMT), motor evoked potentials (MEP), functional magnetic resonance imaging (fMRI) and safety outcomes. DISCUSSION: This trial will provide evidence regarding the feasibility and efficacy of the action observation treatment-based exoskeleton (AOT-EXO) for post-stroke upper extremity rehabilitation and elucidate the potential underlying kinematic and neurological mechanisms. TRIAL REGISTRATION: Chinese Clinical Trial Registry ChiCTR1900026656 . Registered on 17 October 2019.

Modality alignment contrastive learning for severity assessment of COVID-19 from lung ultrasound and clinical information.

The outbreak of COVID-19 around the world has caused great pressure to the health care system, and many efforts have been devoted to artificial intelligence (AI)-based analysis of CT and chest X-ray images to help alleviate the shortage of radiologists and improve the diagnosis efficiency. However, only a few works focus on AI-based lung ultrasound (LUS) analysis in spite of its significant role in COVID-19. In this work, we aim to propose a novel method for severity assessment of COVID-19 patients from LUS and clinical information. Great challenges exist regarding the heterogeneous data, multi-modality information, and highly nonlinear mapping. To overcome these challenges, we first propose a dual-level supervised multiple instance learning module (DSA-MIL) to effectively combine the zone-level representations into patient-level representations. Then a novel modality alignment contrastive learning module (MA-CLR) is presented to combine representations of the two modalities, LUS and clinical information, by matching the two spaces while keeping the discriminative features. To train the nonlinear mapping, a staged representation transfer (SRT) strategy is introduced to maximumly leverage the semantic and discriminative information from the training data. We trained the model with LUS data of 233 patients, and validated it with 80 patients. Our method can effectively combine the two modalities and achieve accuracy of 75.0% for 4-level patient severity assessment, and 87.5% for the binary severe/non-severe identification. Besides, our method also provides interpretation of the severity assessment by grading each of the lung zone (with accuracy of 85.28%) and identifying the pathological patterns of each lung zone. Our method has a great potential in real clinical practice for COVID-19 patients, especially for pregnant women and children, in aspects of progress monitoring, prognosis stratification, and patient management.

Startle Increases the Incidence of Anticipatory Muscle Activations but Does Not Change the Task-Specific Muscle Onset for Patients After Subacute Stroke.

Objectives: To demonstrate the task-specificities of anticipatory muscle activations (AMAs) among different forward-reaching tasks and to explore the StartleReact Effect (SE) on AMAs in occurrence proportions, AMA onset latency or amplitude within these tasks in both healthy and stroke population. Methods: Ten healthy and ten stroke subjects were recruited. Participants were asked to complete the three forward-reaching tasks (reaching, reaching to grasp a ball or cup) on the left and right hand, respectively, with two different starting signals (warning-Go, 80 dB and warning-startle, 114 dB). The surface electromyography of anterior deltoid (AD), flexor carpi radialis (FCR), and extensor carpi radialis (ECR) on the moving side was recorded together with signals from bilateral sternocleidomastoid muscles (SCM), lower trapezius (LT), latissimus dorsi (LD), and tibialis anterior (TA). Proportions of valid trials, the incidence of SE, AMA incidence of each muscle, and their onset latency and amplitude were involved in analyses. The differences of these variables across different move sides (healthy, non-paretic, and paretic), normal or startle conditions, and the three tasks were explored. The ECR AMA onset was selected to further explore the SE on the incidence of AMAs. Results: Comparisons between move sides revealed a widespread AMA dysfunction in subacute stroke survivors, which was manifested as lower AMA onset incidence, changed onset latency, and smaller amplitude of AMAs in bilateral muscles. However, a significant effect of different tasks was only observed in AMA onset latency of muscle ECR (F = 3.56, p = 0.03, η 2 p = 0.011), but the significance disappeared in the subsequent analysis of the stroke subjects only (p > 0.05). Moreover, the following post-hoc comparison indicated significant early AMA onsets of ECR in task cup when comparing with reach (p < 0.01). For different stimuli conditions, a significance was only revealed on shortened premotor reaction time under startle for all participants (F = 60.68, p < 0.001, η p 2 = 0.056). Furthermore, stroke survivors had a significantly lower incidence of SE than healthy subjects under startle (p < 0.01). But all performed a higher incidence of ECR AMA onset (p < 0.05) than with normal signal. In addition, the incidence of ECR AMAs of both non-paretic and paretic sides could be increased significantly via startle (p ≤ 0.02). Conclusions: Healthy people have task-specific AMAs of muscle ECR when they perform forward-reaching tasks with different hand manipulations. However, this task-specific adjustment is lost in subacute stroke survivors. SE can improve the incidence of AMAs for all subjects in the forward-reaching tasks involving precision manipulations, but not change AMA onset latency and amplitude.

Robot-Assisted Arm Training versus Therapist-Mediated Training after Stroke: A Systematic Review and Meta-Analysis.

Background: More than two-thirds of stroke patients have arm motor impairments and function deficits on hospital admission, leading to diminished quality of life and reduced social participation. Robot-assisted training (RAT) is a promising rehabilitation program for upper extremity while its effect is still controversial due to heterogeneity in clinical trials. We performed a systematic review and meta-analysis to compare robot-assisted training (RAT) versus therapist-mediated training (TMT) for arm rehabilitation after stroke. Methods: We searched the following electronic databases: MEDLINE, EMBASE, Cochrane EBM Reviews, and Physiotherapy Evidence Database (PEDro). Studies of moderate or high methodological quality (PEDro score ≥4) were included and analyzed. We assessed the effects of RAT versus TMT for arm rehabilitation after stroke with testing the noninferiority of RAT. A small effect size of -2 score for mean difference in Fugl-Meyer Assessment of the Upper Extremity (FMA-UE) and Cohen's d = -0.2 for standardized mean difference (SMD) were set as noninferiority margin. Results: Thirty-five trials with 2241 participants met inclusion criteria. The effect size for arm motor impairment, capacity, activities of daily living, and social participation were 0.763 (WMD, 95% CI: 0.404 to 1.123), 0.109 (SMD, 95% CI: -0.066 to 0.284), 0.049 (SMD, 95% CI: -0.055 to 0.17), and -0.061 (SMD, 95% CI: -0.196 to 0.075), respectively. Conclusion: This systematic review and meta-analysis demonstrated that robot-assisted training was slightly superior in motor impairment recovery and noninferior to therapist-mediated training in improving arm capacity, activities of daily living, and social participation, which supported the use of RAT in clinical practice.