Principal Components Analysis Using Data Collected From Healthy Individuals on Two Robotic Assessment Platforms Yields Similar Behavioral Patterns

Assessment and recovery of visually guided reaching deficits following cerebellar stroke

The cerebellum is known to play an important role in the coordination and timing of limb movements. The present study focused on how reach kinematics are affected by cerebellar lesions to quantify both the presence of motor impairment, and recovery of motor function over time. In the current study, 12 patients with isolated cerebellar stroke completed clinical measures of cognitive and motor function, as well as a visually guided reaching (VGR) task using the Kinarm exoskeleton at baseline (∼2 weeks), as well as 6, 12, and 24-weeks post-stroke. During the VGR task, patients made unassisted reaches with visual feedback from a central 'start' position to one of eight targets arranged in a circle. At baseline, 6/12 patients were impaired across several parameters of the VGR task compared to a Kinarm normative sample (n = 307), revealing deficits in both feed-forward and feedback control. The only clinical measures that consistently demonstrated impairment were the Purdue Pegboard Task (PPT; 9/12 patients) and the Montreal Cognitive Assessment (6/11 patients). Overall, patients who were impaired at baseline showed significant recovery by the 24-week follow-up for both VGR and the PPT. A lesion overlap analysis indicated that the regions most commonly damaged in 5/12 patients (42% overlap) were lobule IX and Crus II of the right cerebellum. A lesion subtraction analysis comparing patients who were impaired (n = 6) vs. unimpaired (n = 6) on the VGR task at baseline showed that the region most commonly damaged in impaired patients was lobule VIII of the right cerebellum (40% overlap). Our results lend further support to the notion that the cerebellum is involved in both feedforward and feedback control during reaching, and that cerebellar patients tend to recover relatively quickly overall. In addition, we argue that future research should study the effects of cerebellar damage on visuomotor control from a perception-action theoretical framework to better understand how the cerebellum works with the dorsal stream to control visually guided action.

The Measure of Motion Similarity for Robotics Application

A new measure of motion similarity has been proposed. The formulation of this measure is presented and its logical basis is described. Unlike in most of other methods, the measure enables easy determination of the instantaneous synergies of the motion of body parts. To demonstrate how to use the measure, the data describing human movement is used. The movement is recorded using a professional motion capture system. Two different cases of non-periodic movements are discussed: stepping forward and backward, and returning to a stable posture after an unexpected thrust to the side (hands free or tied). This choice enables the identification of synergies in slow dynamics (stepping) and in fast dynamics (push recovery). The trajectories of motion similarity measures are obtained for point masses of the human body. The interpretation of these trajectories in relation to motion events is discussed. In addition, ordinary motion trajectories and footprints are shown in order to better illustrate the specificity of the discussed examples. The article ends with a discussion and conclusions.

Multi-level analysis reveals the association between diabetes, body mass index, and HbA1c in an Iraqi population

Type 2 diabetes (T2D) known as a complex metabolic disorder may cause health problems and changes in blood biochemical markers. A growing number of studies have looked into several biomarkers and their connections with T2D risk. However, few have explored the interconnection of these biomarkers, as well as the prospective alterations in the diabetes biomarker correlation network. We conducted a secondary analysis in order to introduce a multi-level approach to establish a relationship between diabetes, pre-diabetes, blood biochemical markers, age, and body mass index (BMI). The dataset was obtained from the Mendeley Data (available at https://data.mendeley.com/datasets/wj9rwkp9c2/1 . In this study, three groups were established: non-diabetic (n = 103), pre-diabetic (n = 53), and diabetic (n = 844). According to the Heatmap analysis, non-diabetic and pre-diabetic individuals had the lowest BMI, age, and HbA1c. Diabetes and pre-diabetes were correlated with BMI (r = 0.58 and - 0.27, respectively), age (r = 0.47 and - 0.28, respectively), and HbA1c (r = 0.55 and - 0.21, respectively) using Pearson analysis. Using multivariate analysis, we found that diabetes, BMI, age, HbA1c, cholesterol, triglyceride, LDL, VLDL, and HDL were all associated. Network analysis revealed a connection between BMI and diabetes at the highest cut-off point. Moreover, receiver operating characteristic (ROC) analysis validated the network findings, revealing that BMI (area under the ROC curve, AUC = 0.95), HbA1c (AUC = 0.94), and age (AUC = 0.84) were the best predictors of diabetes. In conclusion, our multi-step study revealed that identifying significant T2D predictors, such as BMI and HbA1c, required a series of mathematical analyses.

High intra-task and low inter-task correlations of motor skills in humans creates an individualized behavioural pattern

Our motor system allows us to generate an enormous breadth of voluntary actions, but it remains unclear whether and how much motor skill translates across tasks. For example, if an individual is good at gross motor control, are they also good at fine motor control? Previous research about the generalization across motor skills has been equivocal. Here, we compare human performance across five different motor skills. High correlation between task measures would suggest a certain level of underlying sensorimotor ability that dictates performance across all task types. Low correlation would suggest specificity in abilities across tasks. Performance on a reaching task, an object-hitting task, a bimanual coordination task, a rapid motion task and a target tracking task, was examined twice in a cohort of 25 healthy individuals. Across the cohort, we found relatively high correlations for different spatial and temporal parameters within a given task (16-53% of possible parameter pairs were significantly correlated, with significant r values ranging from 0.53 to 0.97) but relatively low correlations across different tasks (2.7-4.4% of possible parameter pairs were significantly correlated, with significant r values ranging from 0.53-0.71). We performed a cluster analysis across all individuals using 76 performance measures across all tasks for the two repeat testing sessions and demonstrated that repeat tests were commonly grouped together (16 of 25 pairs were grouped next to each other). These results highlight that individuals have different abilities across motor tasks, and that these patterns are consistent across time points.