Upper-limb movement characterization is crucial for many applications, from research on motor control, to the extraction of relevant features for driving active prostheses. While this is usually performed using electrophysiological and/or kinematic measurements only, the collection of tactile data during grasping movements could enrich the overall information about interaction with external environment. We provide a dataset collected from 10 healthy volunteers performing 16 tasks, including simple movements (i.e., hand opening/closing, wrist pronation/supination and flexion/extension, tridigital grasping, thumb abduction, cylindrical and spherical grasping) and more complex ones (i.e., reaching and grasping). The novelty consists in the inclusion of several types of recordings, namely electromyographic -both with bipolar and high-density configuration, kinematic-both with motion capture system and a sensorized glove, and tactile. The data is organized following the Brain Imaging Data Structure standard format and have been validated to ensure its reliability. It can be used to investigate upper-limb movements in physiological conditions, and to test sensor fusion approaches and control algorithms for prosthetics and robotic applications.

The Tenth International brain–computer interface (BCI) meeting was held June 6–9, 2023, in the Sonian Forest in Brussels, Belgium. At that meeting, 21 master classes, organized by the BCI Society’s Postdoc & Student Committee, supported the Society’s goal of fostering learning opportunities and meaningful interactions for trainees in BCI-related fields. Master classes provide an informal environment where senior researchers can give constructive feedback to the trainee on their chosen and specific pursuit. The topics of the master classes span the whole gamut of BCI research and techniques. These include data acquisition, neural decoding and analysis, invasive and noninvasive stimulation, and ethical and transitional considerations. Additionally, master classes spotlight innovations in BCI research. Herein, we discuss what was presented within the master classes by highlighting each trainee and expert researcher, providing relevant background information and results from each presentation, and summarizing discussion and references for further study.

This work describes a dataset containing high-density EEG (hd-EEG) and surface electromiography (sEMG) to capture neuromechanical responses during a reaching task with and without the assistance of an upper-limb exoskeleton. It was designed to explore electrophysiological biomarkers for assessing assistive technologies. Data were collected from 40 healthy participants performing 10 repetitions of three standardized reaching tasks. A custom-designed touch panel was built to standardize and simulate natural upper-limb movements relevant to daily activities. The dataset is formatted according to the Brain Imaging Data Structure (BIDS) standard, in alignment with FAIR principles. To provide an overview of data quality, we present subject-level analyses of event-related spectral perturbation (ERSP), inter-trial coherence (ITC), and event-related synchronization/desynchronization (ERS/ERD) for EEG, along with time- and frequency- domain decomposition for EMG. Beyond providing a methodology for evaluating assistive technologies, this dataset can be used for biosignal processing research, particularly for artifact removal and denoising techniques. It is also valuable for machine learning-based feature extraction, classification, and studying neuromechanical modulations during goal-oriented movements. Additionally, it can support research on human-robot interaction in non-clinical settings, hybrid brain-computer interfaces (BCIs) for robotic control and biomechanical modeling of upper-limb movements.

Ongoing youth-based programmes providing educational expeditions to Antarctica have been developed by non-state actors, universities, and national Antarctic programs since the early 2000s. Despite the successes and impact of these educational programs, and despite the emergence and growth in recent decades of youth-led issues-based movements worldwide, there have been scarce opportunities for young people to have a voice in national and global networks for action on Antarctica. Furthermore, both Antarctic decision-makers and academia have not paid a great deal of attention to youth participation in Antarctic affairs. Drawing on a youth expedition to King George Island in February 2020, the authors designed the Antarctic Youth Coalition as an experiment in youth participation. As a result of the formation of the Antarctic Youth Coalition across five Antarctic gateway cities, we proposed that AYC to provides conceptual and practical platforms for a deeper interrogation of youth participation in Antarctic political, social, economic and environmental matters of concern. This article highlights sustained and active engagement with Antarctic youth projects and the role that young people can play in Antarctic cultural diplomacy.

Objective. This study investigates the neurophysiological correlates of user engagement (UE) during upper-limb exercises in mixed reality (MR)-based exergames. It explores whether MR environments modulate brain activity differently than traditional exercises and whether physical object interaction affects engagement. Methods. High-density electroencephalography (EEG) was recorded from fifteen healthy adults performing bilateral arm exercises under four conditions—with and without MR and physical object interaction. Engagement indices were derived from spectral features (theta, alpha, and their ratios) at both source- and sensor-levels across predefined cortical regions. Time-course dynamics and subjective user experience were also evaluated. Main results. MR-based exergames significantly increased theta power and decreased alpha power compared to non-MR conditions, indicating greater cognitive and attentional engagement. These effects were consistent across frontal, sensorimotor, and parietal regions and remained stable over time. Physical object interaction had no significant effect on engagement. Subjectively, MR conditions were rated higher in stimulation, efficiency, and novelty. Significance. The effectiveness of MR in rehabilitation depends on sustained UE, which is typically assessed through subjective questionnaires. This study demonstrates that EEG-derived metrics—particularly theta and alpha activity—objectively reflect engagement. These results support EEG as a real-time monitoring tool for developing adaptive, brain-responsive rehabilitation technologies.