Effects of prior air pollution exposure on functional recovery after a myocardial infarction.

Air pollution is a major cardiovascular risk factor leading to higher rates of heart failure and myocardial infarction (MI), but its effects on functional recovery after an MI remain unknown. Cardiac rehabilitation is a cornerstone of post-MI care and leads to better performance and quality of life, but its benefits may be hampered in heavily polluted environments. To assess the effect of different pollutants on post-MI rehabilitation, we included 137 post-MI patients from 7 Spanish hospitals that were enrolled in a cardiac rehabilitation program who underwent two cardiopulmonary exercise tests (CPET) within a 12-week period.

Symbolic dynamics of joint brain states during dyadic coordination.

We propose a novel approach to investigate the brain mechanisms that support coordination of behavior between individuals. Brain states in single individuals defined by the patterns of functional connectivity between brain regions are used to create joint symbolic representations of brain states in two or more individuals to investigate symbolic dynamics that are related to interactive behaviors. We apply this approach to electroencephalographic data from pairs of subjects engaged in two different modes of finger-tapping coordination tasks (synchronization and syncopation) under different interaction conditions (uncoupled, leader-follower, and mutual) to explore the neural mechanisms of multi-person motor coordination.

Adaptive hip exoskeleton control using heart rate feedback reduces oxygen cost during ecological locomotion.

Despite their potential, exoskeletons have not reached widespread adoption in daily life, partly due to the challenge of seamlessly adapting assistance across various tasks and environments. Task-specific designs, reliance on complex sensing and extensive data-driven training often limit the practicality of the existing control strategies. To address this challenge, we introduce an adaptive control strategy for hip exoskeletons, emphasizing minimal sensing and ease of implementation.

- a large-scale dataset of 3D medical shapes for computer vision.

Objectives: The shape is commonly used to describe the objects. State-of-the-art algorithms in medical imaging are predominantly diverging from computer vision, where voxel grids, meshes, point clouds, and implicit surface models are used. This is seen from the growing popularity of ShapeNet (51,300 models) and Princeton ModelNet (127,915 models).