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Abstract Post-stroke motor recovery processes remain unknown. Timescales and patterns of upper-limb (UL) recovery suggest a major impact of biological factors, with modest contributions from rehabilitation. We assessed a novel impairment-based training motivated by motor control theory where reaching occurs within the spasticity-free elbow range. Patients with subacute stroke (≤ 6 month; n = 46) and elbow flexor spasticity were randomly allocated to a 10-day UL training protocol, either personalized by restricting reaching to the spasticity-free elbow range defined by the tonic stretch reflex threshold (TSRT) or non-personalized (non-restricted) and with/without anodal transcranial direct current stimulation. Outcomes assessed before, after, and 1 month post-intervention were elbow flexor TSRT angle and reach-to-grasp arm kinematics (primary) and stretch reflex velocity sensitivity, clinical impairment, and activity (secondary). Results were analyzed for 3 groups as well as those of the effects of impairment-based training. Clinical measures improved in both groups. Spasticity-free range training resulted in faster and smoother reaches, smaller (i.e., better) arm-plane path length, and closer-to-normal shoulder/elbow movement patterns. Non-personalized training improved clinical scores without improving arm kinematics, suggesting that clinical measures do not account for movement quality. Impairment-based training within a spasticity-free elbow range is promising since it may improve clinical scores together with arm movement quality. Clinical Trial Registration: URL: http://www.clinicaltrials.gov . Unique Identifier: NCT02725853; Initial registration date: 01/04/2016.

Aim: To explore the feasibility and accuracy of virtual reality (VR) derived from cardiac computed angiography (CCTA) data to predict left atrial appendage occlusion (LAAO) device size. Method: Retrospective data of patients who underwent LAAO according to clinical indication were reviewed; all patients underwent a pre-procedural CCTA. Measurements of the left atrial appendage (LAA) orifice diameters by CCTA, VR, and transesophageal echocardiography (TEE) (acquired during the procedure) were compared to the implanted device size. The LAA perimeter was calculated using the Ramanujan approximation. Statistical analyses included Lin's Concordance Correlation Coefficient (ρc), the mean difference, and the mean square error (MSE). Results: The sample was composed of 20 patients (mean age 75.7 ± 7.5 years, 60% males) who underwent successful LAAO insertion (ACP™ N = 8, Watchman™ N = 12). The CCTA, VR, and TEE maximal diameter ρc was 0.52, 0.78 and 0.60, respectively with mean differences of +0.92 ± 4.0 mm, −1.12 ± 2.3 mm, and −3.45 ± 2.69 mm, respectively. The CCTA, VR, and TEE perimeter calculations ρc were 0.49, 0.54, and 0.39 respectively with mean differences of +4.69 ± 11.5 mm, −9.88 ± 8.0 mm, and −16.79 ± 7.8 respectively. Discussion: A VR visualization of the LAA ostium in different perspectives allows for a better understanding of its funnel-shaped structure. VR measurement of the maximal ostium diameter had the strongest correlation with the diameter of the inserted device. VR may thus provide new imaging possibilities for the evaluation of complex pre-procedural structures such as the LAA.

Abstract Downward gazing is often observed when walking requires guidance. This gaze behavior is thought to promote walking stability through anticipatory stepping control. This study is part of an ongoing effort to investigate whether downward gazing also serves to enhance postural control, which can promote walking stability through a feedback/reactive mechanism. Since gaze behavior alone gives no indication as to what information is gathered and the functions it serves, we aimed to investigate the cognitive demands associated with downward gazing, as they are likely to differ between anticipatory and feedback use of visual input. To do so, we used a novel methodology to compromise walking stability in a manner that could not be resolved through modulation of stepping. Then, using interference methodology and neuroimaging, we tested for (1) interference related to dual tasking, and (2) changes in prefrontal activity. The novel methodology resulted in an increase in the time spent looking at the walking surface. Further, while some dual-task interference was observed, indicating that this gaze behavior is cognitively demanding, several gaze parameters pertaining to downward gazing and prefrontal activity correlated. These correlations revealed that a greater tendency to gaze onto the walking surface was associated with lower PFC activity, as is expected when sensory information is used through highly automatic, and useful, neural circuitry. These results, while not conclusive, do suggest that gazing onto the walking surface can be used for purposes other than anticipatory stepping control, bearing important motor-control and clinical implications.

Objectives: Three-dimensional virtual reality (3D VR) permits precise reconstruction of computed tomography (CT) images, and these allow precise measurements of colonic anatomical parameters. Colonoscopy proves challenging in a subset of patients, and thus CT colonoscopy (CTC) is often required to visualize the entire colon. The aim of the study was to determine whether 3D reconstructions of the colon could help identify and quantify the key anatomical features leading to colonoscopy failure. Design: Retrospective observational study. Methods: Using 3D VR technology, we reconstructed and compared the length of various colonic segments and number of bends and colonic width in 10 cases of CTC in technically failed prior colonoscopies to 10 cases of CTC performed for non-technically failure indications. Results: We found significant elongation of the sigmoid colon (71 ± 23 cm versus 35 ± 9; p = 0.01) and of pancolonic length (216 ± 38 cm versus 158 ± 20 cm; p = 0.001) in cases of technically failed colonoscopy. There was also a significant increase in the number of colonic angles (17.7 ± 3.2 versus 12.7 ± 2.4; p = 0.008) in failed colonoscopy cases. Conclusion: Increased sigmoid and pancolonic length and more colonic bends are novel factors associated with technical failure of colonoscopy.

BackgroundAdvanced age and brain damage have been reported to increase the propensity to gaze down while walking, a behavior that is thought to enhance stability through anticipatory stepping control. Recently, downward gazing (DWG) has been shown to enhance postural steadiness in healthy adults, suggesting that it can also support stability through a feedback control mechanism. These results have been speculated to be the consequence of the altered visual flow when gazing down. The main objective of this cross-sectional, exploratory study was to investigate whether DWG also enhances postural control in older adults and stroke survivors, and whether such effect is altered with aging and brain damage.MethodsPosturography of older adults and stroke survivors, performing a total of 500 trials, was tested under varying gaze conditions and compared with a cohort of healthy young adults (375 trials). To test the involvement of the visual system we performed spectral analysis and compared the changes in the relative power between gaze conditions.ResultsReduction in postural sway was observed when participants gazed down 1 and 3 meters ahead whereas DWG towards the toes decreased steadiness. These effects were unmodulated by age but were modulated by stroke. The relative power in the spectral band associated with visual feedback was significantly reduced when visual input was unavailable (eyes-closed condition) but was unaffected by the different DWG conditions.ConclusionsLike young adults, older adults and stroke survivors better control their postural sway when gazing down a few steps ahead, but extreme DWG can impair this ability, especially in people with stroke.

Abstract Background The lower-extremity motor coordination test (LEMOCOT) is a performance-based measure used to assess motor coordination deficits after stroke. We aimed to automatically quantify performance on the LEMOCOT and to extract additional performance parameters based on error analysis in persons with stroke (PwS) and healthy controls. We also aimed to explore whether these parameters provide additional information regarding motor control deficit that is not captured by the traditional LEMOCOT score. In addition, the associations between the LEMOCOT score, parameters of error and performance-based measures of lower-extremity impairment and gait were tested. Methods Twenty PwS (age: 62 ± 11.8 years, time after stroke onset: 84 ± 83 days; lower extremity Fugl-Meyer: 30.2 ± 3.7) and 20 healthy controls (age: 42 ± 15.8 years) participated in this cross-sectional exploratory study. Participants were instructed to move their big toe as fast and accurately as possible between targets marked on an electronic mat equipped with force sensors (Zebris FDM-T, 60 Hz). We extracted the contact surface area of each touch, from which the endpoint location, the center of pressure (COP), and the distance between them were computed. In addition, the absolute and variable error were calculated. Results PwS touched the targets with greater foot surface and demonstrated a greater distance between the endpoint location and the location of the COP. After controlling for the number of in-target touches, greater absolute and variable errors of the endpoint were observed in the paretic leg than in the non-paretic leg and the legs of controls. Also, the COP variable error differentiated between the paretic, non-paretic, and control legs and this parameter was independent of in-target counts. Negative correlations with moderate effect size were found between the Fugl Meyer assessment and the error parameters. Conclusions PwS demonstrated lower performance in all outcome measures than did controls. Several parameters of error indicated differences between legs (paretic leg, non-paretic leg and controls) and were independent of in-target touch counts, suggesting they may reflect motor deficits that are not identified by the traditional LEMOCOT score.

Introduction: Simpson's rule is generally used to estimate cardiac volumes. By contrast, modern methods such as Virtual Reality (VR) utilize mesh modeling to present the object's surface spatial structure, thus enabling intricate volumetric calculations. In this study, two types of semiautomated VR models for cardiac volumetric analysis were compared to the standard Philips dedicated cardiac imaging platform (PDP) which is based on Simpson's rule calculations. Methods: This retrospective report examined the cardiac computed tomography angiography (CCTA) of twenty patients with atrial fibrillation obtained prior to a left atrial appendage occlusion procedure. We employed two VR models to evaluate each CCTA and compared them to the PDP: a VR model with Philips-similar segmentations (VR-PS) that included the trabeculae and the papillary muscles within the luminal volume, and a VR model that only included the inner blood pool (VR-IBP). Results: Comparison of the VR-PS and the PDP left ventricle (LV) volumes demonstrated excellent correlation with a ρc of 0.983 (95% CI 0.96, 0.99), and a small mean difference and range. The calculated volumes of the right ventricle (RV) had a somewhat lower correlation of 0.89 (95% CI 0.781, 0.95), a small mean difference, and a broader range. The VR-IBP chamber size estimations were significantly smaller than the estimates based on the PDP. Discussion: Simpson's rule and polygon summation algorithms produce similar results in normal morphological LVs. However, this correlation failed to emerge when applied to RVs and irregular chambers. Conclusions: The findings suggest that the polygon summation method is preferable for RV and irregular LV volume and function calculations.

BackgroundPatients use social media as an alternative information source, where they share information and provide social support. Although large amounts of health-related data are posted on Twitter and other social networking platforms each day, research using social media data to understand chronic conditions and patients’ lifestyles is limited. ObjectiveIn this study, we contributed to closing this gap by providing a framework for identifying patients with inflammatory bowel disease (IBD) on Twitter and learning from their personal experiences. We enabled the analysis of patients’ tweets by building a classifier of Twitter users that distinguishes patients from other entities. This study aimed to uncover the potential of using Twitter data to promote the well-being of patients with IBD by relying on the wisdom of the crowd to identify healthy lifestyles. We sought to leverage posts describing patients’ daily activities and their influence on their well-being to characterize lifestyle-related treatments. MethodsIn the first stage of the study, a machine learning method combining social network analysis and natural language processing was used to automatically classify users as patients or not. We considered 3 types of features: the user’s behavior on Twitter, the content of the user’s tweets, and the social structure of the user’s network. We compared the performances of several classification algorithms within 2 classification approaches. One classified each tweet and deduced the user’s class from their tweet-level classification. The other aggregated tweet-level features to user-level features and classified the users themselves. Different classification algorithms were examined and compared using 4 measures: precision, recall, F1 score, and the area under the receiver operating characteristic curve. In the second stage, a classifier from the first stage was used to collect patients' tweets describing the different lifestyles patients adopt to deal with their disease. Using IBM Watson Service for entity sentiment analysis, we calculated the average sentiment of 420 lifestyle-related words that patients with IBD use when describing their daily routine. ResultsBoth classification approaches showed promising results. Although the precision rates were slightly higher for the tweet-level approach, the recall and area under the receiver operating characteristic curve of the user-level approach were significantly better. Sentiment analysis of tweets written by patients with IBD identified frequently mentioned lifestyles and their influence on patients’ well-being. The findings reinforced what is known about suitable nutrition for IBD as several foods known to cause inflammation were pointed out in negative sentiment, whereas relaxing activities and anti-inflammatory foods surfaced in a positive context. ConclusionsThis study suggests a pipeline for identifying patients with IBD on Twitter and collecting their tweets to analyze the experimental knowledge they share. These methods can be adapted to other diseases and enhance medical research on chronic conditions.

Abstract Background Hemiparesis following stroke is often accompanied by spasticity. Spasticity is one factor among the multiple components of the upper motor neuron syndrome that contributes to movement impairment. However, the specific contribution of spasticity is difficult to isolate and quantify. We propose a new method of quantification and evaluation of the impact of spasticity on the quality of movement following stroke. Methods Spasticity was assessed using the Tonic Stretch Reflex Threshold (TSRT). TSRT was analyzed in relation to stochastic models of motion to quantify the deviation of the hemiparetic upper limb motion from the normal motion patterns during a reaching task. Specifically, we assessed the impact of spasticity in the elbow flexors on reaching motion patterns using two distinct measures of the ‘distance’ between pathological and normal movement, (a) the bidirectional Kullback–Liebler divergence (BKLD) and (b) Hellinger’s distance (HD). These measures differ in their sensitivity to different confounding variables. Motor impairment was assessed clinically by the Fugl-Meyer assessment scale for the upper extremity (FMA-UE). Forty-two first-event stroke patients in the subacute phase and 13 healthy controls of similar age participated in the study. Elbow motion was analyzed in the context of repeated reach-to-grasp movements towards four differently located targets. Log-BKLD and HD along with movement time, final elbow extension angle, mean elbow velocity, peak elbow velocity, and the number of velocity peaks of the elbow motion were computed. Results Upper limb kinematics in patients with lower FMA-UE scores (greater impairment) showed greater deviation from normality when the distance between impaired and normal elbow motion was analyzed either with the BKLD or HD measures. The severity of spasticity, reflected by the TSRT, was related to the distance between impaired and normal elbow motion analyzed with either distance measure. Mean elbow velocity differed between targets, however HD was not sensitive to target location. This may point at effects of spasticity on motion quality that go beyond effects on velocity. Conclusions The two methods for analyzing pathological movement post-stroke provide new options for studying the relationship between spasticity and movement quality under different spatiotemporal constraints.

Quality 4.0, the correspondent quality practice fit to address the Industry 4.0 mindset, is expected to provide models and processes endorsed by continuous improvement and data-driven proofs, especially given the exponential growth in available data. The research consolidates the reality of big data availability (part of Quality 4.0) with a generic aspect of quality—managing nonconformities. Its purpose is to suggest a model to improve the initiation step for dealing with nonconformity by prioritizing these events. The new concept in the model suggested is incorporating the risk management method of prioritizing into the nonconformity’s management. These tools are designed to transform qualitative data into quantitative ones and enable easier decision-making, in this case, choosing which issue to deal with first. The research approach is developing and testing the suggested model as a pilot in a real production environment to establish its impact and define key guidelines for utilizing it in various processes and, in addition, to conduct a survey among quality experts from different organizations for reference. Two main outcomes were achieved during the research: The quality experts’ survey welcomed the model concept as a structured tool based on the solid risk management methodology. Implementing the model on actual production lines resulted in a significant reduction of NC financial impact as the events were solved as per their impact.

When walking on an uneven surface or complex terrain, humans tend to gaze downward. This behaviour is usually interpreted as an attempt to acquire useful information to guide locomotion. Visual information, however, is not used exclusively for guiding locomotion; it is also useful for postural control. Both locomotive and postural control have been shown to be sensitive to the visual flow arising from the respective motion of the individual and the three-dimensional environment. This flow changes when a person gazes downward and may present information that is more appropriate for postural control. To investigate whether downward gazing can be used for postural control, rather than exclusively for guiding locomotion, we quantified the dynamics of standing and walking posture in healthy adults, under several visual conditions. Through these experiments we were able to demonstrate that gazing downward, just a few steps ahead, resulted in a steadier standing and walking posture. These experiments indicate that gazing downward may serve more than one purpose and provide sufficient evidence of the possible interplay between the visual information used for guiding locomotion and that used for postural control. These findings contribute to our understanding of the control mechanism/s underlying gait and posture and have possible clinical implications.

This study explored pedestrians’ understanding of Fully Autonomous Vehicles (FAVs) intention to stop and what influences pedestrians’ decision to cross the road over time, i.e., learnability. Twenty participants saw fixed simulated urban road crossing scenes with a single FAV on the road as if they were pedestrians intending to cross. Scenes differed from one another in the FAV’s, distance from the crossing place, its physical size, and external Human-Machine Interfaces (e-HMI) message by background color (red/green), message type (status/advice), and presentation modality (text/symbol). Eye-tracking data and decision measurements were collected. Results revealed that pedestrians tend to look at the e-HMI before making their decision. However, they did not necessarily decide according to the e-HMIs’ color or message type. Moreover, when they complied with the e-HMI proposition, they tended to hesitate before making the decision. Overall, a learning effect over time was observed in all conditions regardless of e- HMI features and crossing context. Findings suggest that pedestrians’ decision making depends on a combination of the e-HMI implementation and the car distance. Moreover, since the learning curve exists in all conditions and has the same proportion, it is critical to design an interaction that would encourage higher probability of compatible decisions from the first phase. However, to extend all these findings, it is necessary to further examine dynamic situations.

The effect of camera viewpoint and fruit orientation on the performance of a sweet pepper maturity level classification algorithm was evaluated. Image datasets of sweet peppers harvested from a commercial greenhouse were collected using two different methods, resulting in 789 RGB—Red Green Blue (images acquired in a photocell) and 417 RGB-D—Red Green Blue-Depth (images acquired by a robotic arm in the laboratory), which are published as part of this paper. Maturity level classification was performed using a random forest algorithm. Classifications of maturity level from different camera viewpoints, using a combination of viewpoints, and different fruit orientations on the plant were evaluated and compared to manual classification. Results revealed that: (1) the bottom viewpoint is the best single viewpoint for maturity level classification accuracy; (2) information from two viewpoints increases the classification by 25 and 15 percent compared to a single viewpoint for red and yellow peppers, respectively, and (3) classification performance is highly dependent on the fruit’s orientation on the plant.

One of the key applications of next-generation sequencing (NGS) technologies is RNA-Seq for transcriptome genome-wide analysis. Although multiple studies have evaluated and benchmarked RNA-Seq tools dedicated to gene level analysis, few studies have assessed their effectiveness on the transcript-isoform level. Alternative splicing is a naturally occurring phenomenon in eukaryotes, significantly increasing the biodiversity of proteins that can be encoded by the genome. The aim of this study was to assess and compare the ability of the bioinformatics approaches and tools to assemble, quantify and detect differentially expressed transcripts using RNA-Seq data, in a controlled experiment. To this end, in vitro synthesized mouse spike-in control transcripts were added to the total RNA of differentiating mouse embryonic bodies, and their expression patterns were measured. This novel approach was used to assess the accuracy of the tools, as established by comparing the observed results versus the results expected of the mouse controlled spiked-in transcripts. We found that detection of differential expression at the gene level is adequate, yet on the transcript-isoform level, all tools tested lacked accuracy and precision.

PURPOSE: To present a novel method for quantitative assessment of retinal vessel permeability using a fluorescein angiography-based computer algorithm. METHODS: Twenty-one subjects (13 with diabetic retinopathy, 8 healthy volunteers) underwent fluorescein angiography (FA). Image pre-processing included removal of non-retinal and noisy images and registration to achieve spatial and temporal pixel-based analysis. Permeability was assessed for each pixel by computing intensity kinetics normalized to arterial values. A linear curve was fitted and the slope value was assigned, color-coded and displayed. The initial FA studies and the computed permeability maps were interpreted in a masked and randomized manner by three experienced ophthalmologists for statistical validation of diagnosis accuracy and efficacy. RESULTS: Permeability maps were successfully generated for all subjects. For healthy volunteers permeability values showed a normal distribution with a comparable range between subjects. Based on the mean cumulative histogram for the healthy population a threshold (99.5%) for pathological permeability was determined. Clear differences were found between patients and healthy subjects in the number and spatial distribution of pixels with pathological vascular leakage. The computed maps improved the discrimination between patients and healthy subjects, achieved sensitivity and specificity of 0.974 and 0.833 respectively, and significantly improved the consensus among raters for the localization of pathological regions. CONCLUSION: The new algorithm allows quantification of retinal vessel permeability and provides objective, more sensitive and accurate evaluation than the present subjective clinical diagnosis. Future studies with a larger patients' cohort and different retinal pathologies are awaited to further validate this new approach and its role in diagnosis and treatment follow-up. Successful evaluation of vasculature permeability may be used for the early diagnosis of brain microvascular pathology and potentially predict associated neurological sequelae. Finally, the algorithm could be implemented for intraoperative evaluation of micovascular integrity in other organs or during animal experiments.