User Recognition Based on Human Body Impulse Response: A Feasibility Study

Human recognition technologies for security systems require high reliability and easy accessibility in the advent of the internet of things (IoT). While several biometric approaches have been studied for user recognition, there are demands for more convenient techniques suitable for the IoT devices. Recently, electrical frequency responses of the human body have been unveiled as one of promising biometric signals, but the pilot studies are inconclusive about the characteristics of human body as a transmission medium for electric signals. This paper provides a multi-domain analysis of human body impulse responses (HBIR) measured at the receiver when customized impulse signals are passed through the human body. We analyzed the impulse responses in the time, frequency, and wavelet domains and extracted representative feature vectors using a proposed accumulated difference metric in each domain. The classification performance was tested using the k-nearest neighbors (KNN) algorithm and the support vector machine (SVM) algorithm on 10-day data acquired from five subjects. The average classification accuracies of the simple classifier KNN for the time, frequency, and wavelet features reached 92.99%, 77.01%, and 94.55%, respectively. In addition, the kernel-based SVM slightly improved the accuracies of three features by 0.58%, 2.34%, and 0.42%, respectively. The result shows potential of the proposed approach for user recognition based on HBIR

A review of recent innovations in remote health monitoring

The development of remote health monitoring systems has focused on enhancing healthcare services’ efficiency and quality, particularly in chronic disease management and elderly care. These systems employ a range of sensors and wearable devices to track patients’ health status and offer real-time feedback to healthcare providers. This facilitates prompt interventions and reduces hospitalization rates. The aim of this study is to explore the latest developments in the realm of remote health monitoring systems. In this paper, we explore a wide range of domains, spanning antenna designs, small implantable antennas, on-body wearable solutions, and adaptable detection and imaging systems. Our research also delves into the methodological approaches used in monitoring systems, including the analysis of channel characteristics, advancements in wireless capsule endoscopy, and insightful investigations into sensing and imaging techniques. These advancements hold the potential to improve the accuracy and efficiency of monitoring, ultimately contributing to enhanced health outcomes for patients.Publisher's VersionQ2WOS:001130630400001PMID:3813832

Internet of Things for Sustainable Human Health

The sustainable health IoT has the strong potential to bring tremendous improvements in human health and well-being through sensing, and monitoring of health impacts across the whole spectrum of climate change. The sustainable health IoT enables development of a systems approach in the area of human health and ecosystem. It allows integration of broader health sub-areas in a bigger archetype for improving sustainability in health in the realm of social, economic, and environmental sectors. This integration provides a powerful health IoT framework for sustainable health and community goals in the wake of changing climate. In this chapter, a detailed description of climate-related health impacts on human health is provided. The sensing, communications, and monitoring technologies are discussed. The impact of key environmental and human health factors on the development of new IoT technologies also analyzed

5G Outlook – Innovations and Applications

5G Outlook - Innovations and Applications is a collection of the recent research and development in the area of the Fifth Generation Mobile Technology (5G), the future of wireless communications. Plenty of novel ideas and knowledge of the 5G are presented in this book as well as divers applications from health science to business modeling. The authors of different chapters contributed from various countries and organizations. The chapters have also been presented at the 5th IEEE 5G Summit held in Aalborg on July 1, 2016. The book starts with a comprehensive introduction on 5G and its need and requirement. Then millimeter waves as a promising spectrum to 5G technology is discussed. The book continues with the novel and inspiring ideas for the future wireless communication usage and network. Further, some technical issues in signal processing and network design for 5G are presented. Finally, the book ends up with different applications of 5G in distinct areas. Topics widely covered in this book are: • 5G technology from past to present to the future• Millimeter- waves and their characteristics• Signal processing and network design issues for 5G• Applications, business modeling and several novel ideas for the future of 5

Optics for AI and AI for Optics

Artificial intelligence is deeply involved in our daily lives via reinforcing the digital transformation of modern economies and infrastructure. It relies on powerful computing clusters, which face bottlenecks of power consumption for both data transmission and intensive computing. Meanwhile, optics (especially optical communications, which underpin today’s telecommunications) is penetrating short-reach connections down to the chip level, thus meeting with AI technology and creating numerous opportunities. This book is about the marriage of optics and AI and how each part can benefit from the other. Optics facilitates on-chip neural networks based on fast optical computing and energy-efficient interconnects and communications. On the other hand, AI enables efficient tools to address the challenges of today’s optical communication networks, which behave in an increasingly complex manner. The book collects contributions from pioneering researchers from both academy and industry to discuss the challenges and solutions in each of the respective fields