Edge AI for Biomedical Applications: Innovations in Sensing, Computing and Security

Dear Colleagues,

The increasing prevalence of edge devices, such as wearables, cyber-physical systems, and the Internet of Things (IoT), in smart environments has catalyzed the integration of artificial intelligence (AI) directly into edge computing systems, a paradigm known as Edge AI. Edge AI marks a promising era for biomedical applications, enabling transformative innovations in sensing, computing, and security. This Special Issue emphasizes solutions that enable real-time, energy-efficient, and privacy-preserving machine learning and deep learning operations directly on edge devices, with applications including intelligent wearable sensors, implantable medical devices, clinical decision support systems, and mobile healthcare platforms.

The scope of the Special Issue spans a wide range of topics, including the following:

Advanced Sensing: The development and integration of novel biosensors and sensor fusion techniques that leverage Edge AI for precise data acquisition and analysis in real-time.

Efficient Computing: Algorithm–hardware co-design for energy-efficient AI inference, optimized machine learning models for edge devices, and low-power biomedical signal and image processing.

Robust Security: Ensuring data integrity and privacy in edge-based biomedical systems, with a focus on secure data transmission, federated learning, and adversarial robustness.

Applications: The deployment of Edge AI in diverse biomedical applications such as remote patient monitoring, wearable health diagnostics, neuroprosthetics, and personalized healthcare.

This Special Issue aims to bring together a collection of original research and review papers showcasing the unique constraints and opportunities of edge computing and AI in healthcare, such as latency-sensitive decision-making, resource-constrained environments, and enhanced data security, while addressing the gap between centralized AI methodologies and the emerging need for decentralized, edge-based systems tailored for biomedical applications.

Dr. Md Maruf Hossain Shuvo
Dr. Krishna Roy
Dr. Sanchita Ghose
Guest Editors

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