Overview

This Special Issue Reprint, ""Sensors Fusion in Digital Healthcare Applications"", presents a collection of ten original research articles and one comprehensive systematic review exploring the transformative potential of integrating multimodal sensor data with advanced artificial intelligence. The contributions showcase the breadth of this rapidly evolving field, spanning applications from personalized support for children with autism spectrum disorders using sensors, to the objective biomechanical assessment of stair descent and gait disorders through depth cameras and motion sensors. Several papers address critical challenges in deploying these technologies in real-world settings, presenting solutions including methods for generating high-quality synthetic medical time-series data, hardware acceleration techniques for energy-efficient processing of sensors data on wearable devices, and intelligent signal processing strategies to improve patient tracking for nursing care. The recurring themes throughout this Reprint emphasize the importance of context-aware systems that adapt to individual patient characteristics, the development of XAI models to support clinical decision-making, and the validation of sensor fusion methodologies against clinical standard. Through bringing together cutting-edge research in healthcare infrastructure, and objective postural control evaluation, this collection serves as a valuable resource for researchers, clinicians, and engineers working at the intersection of sensor technology and digital health, providing a reference for both current best practices and inspiration for future innovations.

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