Intelligent Processing of Biomedical Signals for Smart Health, Biometrics, and Human Well-Being

This Research Topic focuses on advances in intelligent processing of biomedical signals and artificial intelligence for next-generation health, biometric systems, and human well-being. The rapid evolution of smart sensing technologies, wearable platforms, and multimodal biomedical signal acquisition is transforming how physiological, behavioral, and environmental measurements are analyzed to support predictive, preventive, and personalized healthcare, as well as secure and human-centered biometric applications. We invite interdisciplinary contributions bridging biomedical signal processing, AI, biomedical engineering, and biometric science to develop innovative approaches for monitoring, modeling, and improving human health and identity-aware technologies.We particularly welcome submissions leveraging generative AI, including generative modeling of biomedical signals, synthetic data creation, simulation-driven learning, and foundation models for biomedical and biometric applications. Such approaches play a critical role in addressing data scarcity, privacy constraints, robustness, and generalization in real-world intelligent systems.The collection explicitly welcomes multimodal frameworks in which biomedical signals are jointly processed with imaging, spatial, or heterogeneous data sources. We encourage research on unified representations and cross-modal learning that integrate biosignals, visual data, and contextual measurements to improve robustness, interpretability, and predictive performance. The collection aims to highlight research on biomedical signal analysis, biometric intelligence, and multimodal data fusion with practical applications in healthcare, aging, mental well-being, secure identity systems, and sustainable living.This Research Topic is aligned with the scientific themes of the BioSMART conference series, which brings together researchers working on intelligent biomedical signal processing, biometrics, and AI for human-centered technologies. Authors presenting relevant work at BioSMART are encouraged to submit substantially extended versions of their contributions. Submissions are open to the broader research community and will undergo the journal’s standard independent peer-review process. Topic editors: Amine NAIT-ALI, Imad Rida Source: https://www.frontiersin.org/research-topics/81705/intelligent-processing-of-biomedical-signals-for-smart-health-biometrics-and-human-well-being