Kyoto, Japan -- A team of researchers at Kyoto University have demonstrated that the chaotic component of heartbeat variability is uniquely sensitive to cognitive brain activity. Conventional hear rate variability, HRV, indices show no consistent response, whereas chaos-based measures reveal clear and reproducible changes, providing a new non-invasive indicator of brain-heart interaction.

HRV is widely used as an indicator of autonomic nervous system function. However, its ability to reflect higher-order brain activity has remained unclear. In this study, the researchers applied nonlinear analysis and chaos theory to examine heartbeat dynamics under cognitive load.

The researchers had participants perform cognitive tasks designed to engage higher-order brain functions. They then analyzed heartbeat signals using both conventional HRV indices -- such as time-domain and frequency-domain measures -- and chaos-based metrics derived from nonlinear dynamics.

Nanyang Technological University, Singapore (NTU Singapore) will house the first two Max Planck Centres in Southeast Asia, the Max Planck – Singapore Centre for Data-Driven Chemistry and the Max Planck – NTU Singapore Centre for Biocultural Worlding.

These centres are flagship collaborative research initiatives between the Max Planck Society (MPG) in Germany and leading international research institutions. They serve as hubs of scientific excellence, bringing together top researchers from around the world to address frontier questions across diverse disciplines.

The Max Planck – Singapore Centre for Data Driven Chemistry aims to study how the complex volume of chemical research data can be digitalised and analysed effectively to better understand chemical processes and shed light on new reactions.

The Max Planck – NTU Singapore Centre for Biocultural Worlding will study how the close connection between nature and human cultures shape the future of our planet, and what kinds of knowledge and approaches are needed to respond effectively.

Self-powered flexible sensors exhibit revolutionary potential in next-generation wearable technologies owing to their exceptional sensitivity and self-sustaining energy harvesting capabilities. Nevertheless, their widespread deployment remains constrained by three fundamental challenges: dynamic mechanical mismatch between biological tissues and rigid devices, suboptimal energy conversion efficiency, and interfacial impedance fluctuation under deformation. Drawing inspiration from the unique negative Poisson’s ratio mesh architecture of lacewing wings, we present a bioinspired auxetic metastructure-engineered triboelectric nanogenerator. This innovative design integrates engineered collagen and micropatterned fluorinated ethylene propylene as triboelectric layers, unified by an auxetic framework with re-entrant hexagonal unit cells interconnected via triangular ligaments. The metastructure enables exceptional lateral expansion under longitudinal strain while simultaneously enhancing structural rigidity and deformation adaptability. This dual functionality effectively minimizes tissue–device mechanical mismatch, thereby significantly improving signal fidelity, sensitivity, and mechanical-to-electrical conversion efficiency during multi-axial deformations. The optimized device achieves remarkable performance metrics, delivering 478 V output voltage with 13.8% energy conversion efficiency in linear configuration, while demonstrating threefold enhanced stability (58 V, 7.58% efficiency) under complex bending compared to conventional designs. Integrated with a convolutional neural network-based machine learning enables exceptional classification accuracy (> 99%) across diverse material recognition tasks, validating its robustness as a next-generation platform for adaptive self-powered wearable sensing.