EMG
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Related Articles from SNS
SoftPINCH: EMG-Driven Soft Exoskeleton Assistance for Finger Flexion and Grasping
arXiv:2606.04776v1 Announce Type: new Abstract: Surface electromyography (sEMG) provides a non-invasive interface for detecting hand-movement intention and controlling wearable assistive devices. However, reliable EMG-driven hand assistance remains challenging because EMG signals are affected by noise, motion artifacts, electrode placement, muscle fatigue, and inter-subject variability. At the same time, many hand exoskeletons remain mechanically restrictive or bulky, limiting comfort and...
A 1000-hour EEG-EMG-audio dataset of Japanese speech production
Announce Type: cross Abstract: We present a multimodal dataset of 1020 hours of simultaneously recorded scalp electroencephalography (EEG), facial electromyography (EMG), and speech audio from three healthy native Japanese speakers during open-vocabulary overt speech. Recordings were acquired with three EEG systems-an ultra-high-density system (g.Pangolin) and two cap-type systems (g.SCARABEO and eegosports), spanning 62-128 channels-across many sessions over several months. Each session...
Automated analysis of feeding dynamics from electromyographic recordings in a blood-sucking insect
Feeding behavior in blood-sucking insects relies on gustatory evaluation to decide on sustained ingestion, yet quantifying this process from electromyogram (EMG) recordings is labor-intensive. Here we developed MyoRec, an automated computational framework employing machine learning to analyse EMG signals from the triatomine bug Rhodnius prolixus. Using recordings under appetitive and aversive conditions, a convolutional neural network detected ingestion events with 97.7% accuracy.
Simulation-Driven Imitation Learning for Biosignals-Free Shared-Autonomy Prosthetic Grasping
arXiv:2606.07389v1 Announce Type: new Abstract: Biosignals-free shared-autonomy control of upper-limb prosthetic hands aims to enable natural and low-effort manipulation without relying on EMG or other physiological signals. Recent imitation-learning-based approaches have shown promising results, but their scalability is limited by the cost and variability of collecting large amounts of real-world human demonstration data. In this work, we present a scalable simulation framework that...
Stimulus-Specific and Generalized Taste Aversion Behaviors and Their Relationship to Cortical Dynamics
Aversive taste behaviors, such as gaping, are commonly viewed as fixed, hard-wired responses important for ejecting potentially toxic tastes from the mouth. Yet, taste responses are highly susceptible to modulation by experience and context; for instance, conditioned taste aversion (CTA), a form of learning in which rats are made to respond aversively to a sweet taste after it has been paired with gastric malaise, can cause gaping to previously acceptable tastes. Here, we compare aversive...
Cell-type targeted CRISPR/Cas9 Clock knockdown in mouse VTA dopamine neurons alter sleep, behavior, and cellular excitability
Bipolar disorder (BD) is a severe psychiatric disease characterized by recurrent mania, depression, and circadian rhythm disruption. Among circadian regulators implicated in mood-related dysfunction, Clock has emerged as a particularly strong mechanistic candidate. However, cell type-specific functions of Clock within mood-relevant circuits remain incompletely defined.
OLIVE: Online Low-Rank Incremental Learning for Efficient Adaptive Exoskeletons
Announce Type: new Abstract: Wearable exoskeleton systems hold promise for restoring mobility in individuals with physical impairments, yet most existing controllers rely on static gait policies that lack the ability to adapt to dynamic real-world environments or individual user characteristics. We present \olive (\underline{O}nline \underline{L}ow-rank \underline{I}ncremental Learning for Efficient Adapti\underline{ve} Exoskeletons), a parameter-efficient online adaptation framework that...
A 65-nm Privacy-Preserving Neuromorphic Encoder With 7.13-nJ Efficiency, 2.38-Mb/mm^2 Item-Memory Density, and Federated Learning Support
arXiv:2606.09460v1 Announce Type: new Abstract: The increasing demand for privacy-preserving personal data analytics in smart assistants, wearable health monitors, and context-aware systems calls for hardware that is both energy-efficient and secure. This work presents a 65-nm privacy-preserving neuromorphic encoder that leverages transistor-level process variation as physically unclonable entropy for hyperdimensional computing. The proposed 2T-2T entropy cell enables compact,...
Motion Tracking with Muscles: Predictive Control of a Parametric Musculoskeletal Canine Model
Announce Type: replace Abstract: We introduce a novel musculoskeletal model of a dog, procedurally generated from accurate 3D muscle meshes. Accompanying this model is a motion capture-based locomotion task compatible with a variety of control algorithms, as well as an improved muscle dynamics model designed to enhance convergence in differentiable control frameworks. We validate our approach by comparing simulated muscle activation patterns with experimentally obtained electromyography...
A Focus of Attention-Based Virtual Training Platform for Pre-Prosthetic Myoelectric Skill Acquisition: A Proof-of-Concept Study
arXiv:2605.31332v1 Announce Type: new Abstract: Advances in myoelectric prosthetic technology have substantially increased the functional potential of modern devices. Accordingly, heightened control demands have led to the acknowledgement of pre-prosthetic training as a key stage in the acquisition of myoelectric skills. Existing training paradigms largely emphasize internal muscle activation while external, goal-directed outcomes required for effective real-world use are often neglected.