TL;DR
Spectral-Guided Contrastive Learning (SpecCL), a novel physics-informed SSL framework, is proposed, which introduces sensor-realistic augmentations to construct physically meaningful learning pairs simulating real-world perturbations and distills physical priors into the learned temporal representations.
Despite the ubiquity of sensors in wearable and mobile devices and the abundance of human movement data they generate, translating unlabeled recordings into foundational motion models remains an open challenge. Self-supervised learning (SSL) has alleviated the need for costly annotations, yet existing approaches leave...
Human activity recognition (HAR) is increasingly important for healthcare, well-being, and daily monitoring ap- plications, for which detecting alimentary activities such as eating and drinking can provide actionable insight into dietary habits and chronic disease management. HAR systems, however, often underperform on...
Wearable sensor-based Human Activity Recognition (HAR) is important for continuous health monitoring, assistive systems, and context-aware systems. Despite recent progress, real-world deployment remains difficult due to issues such as sensor noise, missing data, device heterogeneity, and limited annotated samples. Alth...
This framework provides a potential scalable pathway for domains with critically limited annotated data using massive synthetic data without synthetic labels to train a lightweight classifier on limited clinical data.
The study separates the measured benefit of predictive representations from the physiological prior used to organize their training, and presents Phenomenon-Graph JEPA, a joint-embedding predictive architecture that learns from four processed one-dimensional streams without negative pairs or synthetic augmentation in i...
A three-stage Adaptive CNN-Enhanced Scale-fusion Network (ACESNet) for six-channel accelerometer–gyroscope activity recognition supports a favorable performance–efficiency trade-off relative to the selected baselines under the stated protocol.
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