Advances in Wearables and Nearables for Healthcare Applications

This edited book covers original research, implementations, and comprehensive reviews to discuss recent achievements and emerging trends in wearable and nearable technology for health-related applications. The book covers aspects of signal acquisition, preprocessing, feature extraction, machine learning (ML), and deep learning (DL) methodologies specific to data from wearable and nearable technologies. It also covers practical issues related to data reliability, clinical validation, regulatory issues, and ethical issues, as well as cloud computing, Internet of Things (IoT), and Internet of Medical Things (IoMT) infrastructures.

Features:

· Explores advanced sensing and signal processing techniques for wearable and nearable health technologies.

· Discusses real-time monitoring, cloud-based analytics, and IoT/IoMT integration.

· Addresses clinical validation, regulatory, and ethical challenges of wearable and nearable systems.

· Presents case studies and applications in smart health monitoring, sleep analysis, cardiac, and respiratory assessment.

· Provides a comprehensive reference for graduate students, researchers, and professionals in biomedical and health informatics.

This book bridges the gap between theoretical foundations and practical applications in healthcare and may prove a useful resource for researchers, practitioners, and professionals working in biomedical engineering, signal processing, and intelligent health systems.