Branching Condition of the Color-Word Interference Test Enhances Prediction of Meta-Tasking in Community-Dwelling Older Adults

Objectives: Meta-tasking (MT) is an aspect of executive functioning (EF) that involves the ability to branch (i.e., to apply “if-then” rules) and to effectively interleave sub-goals of one task with sub-goals of another task. As such, MT is crucial for successful planning, coordination, and execution of multiple complex tasks in daily life. Traditional tests of EF fail to adequately measure MT. This study examined whether Condition 4 of the Color-Word Interference Test (CWIT-4; the inhibition/switching condition that requires branching) predicted MT beyond Condition 3 (CWIT-3; inhibition-only condition) and beyond other subtests from the Delis–Kaplan Executive Function System (D-KEFS) that have a switching condition. Method: Ninety-eight non-Hispanic white community-dwelling older adults completed the first four subtests of the D-KEFS and an ecologically valid measure of MT. Results: Time to completion and total errors on CWIT-4 accounted for variance in MT above and beyond CWIT-3 and beyond the switching conditions of other D-KEFS subtests. Results remained virtually unchanged when controlling for demographics and general cognitive status. Conclusions: Among older adults, CWIT-4 is more strongly associated with MT than other D-KFES tasks. Future research should examine whether CWIT-4 relates to lapses in instrumental activities of daily living among older adults above and beyond other EF tests.

Improvements on the virtual obstacle method

While the artificial potential field has been widely employed to design path planning algorithms, it is well-known that artificial potential field-based algorithms suffer a severe problem that a robot may sink into a local minimum point. To address such problems, a virtual obstacle method has been developed in the literature. However, a robot may be blocked by virtual obstacles generated during performing the virtual obstacle method if the environments are complex. In this article, an improved virtual obstacle method for local path planning is designed via proposing a new minimum criterion, a new switching condition, and a new exploration force. All the three new contributions allow to overcome the drawbacks of the artificial potential field-based algorithms and the virtual obstacle method. As a consequence, feasible collision-free paths can be found in complex environments, as illustrated by final numerical simulations.

Cerebral Oxygenation Reserve: The Relationship Between Physical Activity Level and the Cognitive Load During a Stroop Task in Healthy Young Males

Introduction: Many studies have reported that regular physical activity is positively associated with cognitive performance and more selectively with executive functions. However, some studies reported that the association of physical activity on executive performance in younger adults was not as clearly established when compared to studies with older adults. Among the many physiological mechanisms that may influence cognitive functioning, prefrontal (PFC) oxygenation seems to play a major role. The aim of the current study was to assess whether executive function and prefrontal oxygenation are dependent on physical activity levels (active versus inactive) in healthy young males. Methods: Fifty-six healthy young males (22.1 ± 2.4 years) were classified as active (n = 26) or inactive (n = 30) according to the recommendations made by the World Health Organization (WHO) and using the Global Physical Activity Questionnaire (GPAQ). Bilateral PFC oxygenation was assessed using functional near-infrared spectroscopy (fNIRS) during a computerized Stroop task (which included naming, inhibition, and switching conditions). Accuracy (% of correct responses) and reaction times (ms) were used as behavioural indicators of cognitive performances. Changes in oxygenated (∆HbO2) and deoxygenated (∆HHb) hemoglobin were measured to capture neural changes. Several two-way repeated measures ANOVAs (Physical activity level x Stroop conditions) were performed to test the null hypothesis of an absence of interaction between physical activity level and executive performance in prefrontal oxygenation. Results: The analysis revealed an interaction between physical activity level and Stroop conditions on reaction time (p = 0.04; ES = 0.7) in which physical activity level had a moderate effect on reaction time in the switching condition (p = 0.02; ES = 0.8) but not in naming and inhibition conditions. At the neural level, a significant interaction between physical activity level and prefrontal oxygenation was found. Physical activity level had a large effect on ΔHbO2 in the switching condition in the right PFC (p = 0.04; ES = 0.8) and left PFC (p = 0.02; ES = 0.96), but not in other conditions. A large physical activity level effect was also found on ΔHHb in the inhibition condition in the right PFC (p < 0.01; ES = 0.9), but not in the left PFC or other conditions. Conclusion: The results of this cross-sectional study indicate that active young males performed better in executive tasks than their inactive counterparts and had a larger change in oxygenation in the PFC during these most complex conditions.

A Semi-Continuous PWA Model Based Optimal Control Method for Nonlinear Systems

To alleviate the mode mismatch of multiple model methods for nonlinear systems when completely discrete dynamical equations are adopted, a semi-continuous piecewise affine (SCPWA) model based optimal control method is proposed. Firstly, a SCPWA model is constructed where modes evolve in continuous time and continuous states evolve in discrete time. Thanks to this model, a piecewise affine (PWA) system can switch at any time instant whereas mode switching only occurs at sample instants when a completely discrete PWA model is adopted, which improves the prediction accuracy of multi-models. Secondly, the switching condition is relaxed such that operating subspaces have overlaps and switching condition parameters are introduced. As a consequence, an optimal control problem with fixed mode switching sequence is established. Finally, a SCPWA model based model predictive control (MPC) policy is designed for nonlinear systems. The convergence of the MPC algorithm is proved. Compared with widely used mixed logical dynamic (MLD) model based methods, the proposed method not only alleviates mode mismatch, but also lightens the computing burden, hence improves the control performance and reduces the computation time. Some numerical examples are provided as well to show the efficiency of the method.

Walking Stability of a Variable Length Inverted Pendulum Controlled with Virtual Constraints

Bipedal walking is a complex phenomenon that is not fully understood. Simplified models make it easier to highlight the important features. Here, the variable length inverted pendulum (VLIP) model is used, which has the particularity of taking into account the vertical oscillations of the center of mass (CoM). When the desired walking gait is defined as virtual constraints, i.e., as functions of a phasing variable and not on time, for the evolution of the swing foot and the vertical oscillation of the CoM, the walk will asymptotically converge to the periodic motion under disturbance with proper choice of the virtual constraints, thus a self-stabilization is obtained. It is shown that the vertical CoM oscillation, positions of the swing foot and the choice of the switching condition play crucial roles in stability. Moreover, a PI controller of the CoM velocity along the sagittal axis is also proposed such that the walking speed of the robot can converge to another periodic motion with a different walking speed. In this way, a natural walking gait is illustrated as well as the possibility of velocity adaptation as observed in human walking.