Wireless Health Monitoring using Passive WiFi Sensing

This paper presents a two-dimensional phase extraction system using passive WiFi sensing to monitor three basic elderly care activities including breathing rate, essential tremor and falls. Specifically, a WiFi signal is acquired through two channels where the first channel is the reference one, whereas the other signal is acquired by a passive receiver after reflection from the human target. Using signal processing of cross-ambiguity function, various features in the signal are extracted. The entire implementations are performed using software defined radios having directional antennas. We report the accuracy of our system in different conditions and environments and show that breathing rate can be measured with an accuracy of 87% when there are no obstacles. We also show a 98% accuracy in detecting falls and 93% accuracy in classifying tremor. The results indicate that passive WiFi systems show great promise in replacing typical invasive health devices as standard tools for health care.Comment: 6 pages, 8 figures, conference pape

BodyScan: Enabling Radio-based Sensing on Wearable Devices for Contactless Activity and Vital Sign Monitoring

Wearable devices are increasingly becoming mainstream consumer products carried by millions of consumers. However, the potential impact of these devices is currently constrained by fundamental limitations of their built-in sensors. In this paper, we introduce radio as a new powerful sensing modality for wearable devices and propose to transform radio into a mobile sensor of human activities and vital signs. We present BodyScan, a wearable system that enables radio to act as a single modality capable of providing whole-body continuous sensing of the user. BodyScan overcomes key limitations of existing wearable devices by providing a contactless and privacy-preserving approach to capturing a rich variety of human activities and vital sign information. Our prototype design of BodyScan is comprised of two components: one worn on the hip and the other worn on the wrist, and is inspired by the increasingly prevalent scenario where a user carries a smartphone while also wearing a wristband/smartwatch. This prototype can support daily usage with one single charge per day. Experimental results show that in controlled settings, BodyScan can recognize a diverse set of human activities while also estimating the user's breathing rate with high accuracy. Even in very challenging real-world settings, BodyScan can still infer activities with an average accuracy above 60% and monitor breathing rate information a reasonable amount of time during each day

Cooperative Human-Centric Sensing Connectivity

Human-centric sensing (HCS) is a new concept relevant to Internet of Things (IoT). HCS connectivity, referred to as “smart connectivity,” enables applications that are highly personalized and often time-critical. In a typical HCS scenario, there may be many hundreds of sensor stream connections, centered around the human, who would be the determining factor for the number, the purpose, the direction, and the frequency of the sensor streams. This chapter examines the concepts of HCS communications, outlines the challenges, and defines a roadmap for solutions for realizing HCS networks. This chapter is organized as follows. Section 1 introduces the concept of cooperation in information and communications technologies (ICT), and in the context of IoT. Section 2 discusses cooperation in the context of the personal and extra-personal user space and identifies the remaining open challenges and requirements for realizing the benefits of this approach to enabling more resources and services in a hyper-connected society. Section 3 defines a roadmap toward realizing simple, efficient, and trustable systems based on advanced technologies combining security, cloud, and IoT/big data technologies and outlines the challenges related to this vision. Section 4 concludes the chapter

Wireless Patient Monitoring over 4G Network

The purpose of this thesis is to explain how remote patient monitoring systems work over the 4G network using wearable sensors and corresponding interface devices. Gathered data from the sensing devices are carried over the Monitoring Wireless Sensor Network to the more elaborate 4G Network where the data is then relayed to the interface devices for reading, storage, interpretation and effective utilization. This thesis describes the underlying technologies and principles of sensors and sensor net-works, the concept of the 4G Network and how it integrates with the sensor network. The goal of Wireless Patient Monitoring over the 4G Network is link the spatial gap that exist between Healthcare and ICT, this will in turn enhance patients care efficiency while cutting costs, maximising profits and increase security while monitoring patients. This thesis is important in that it gives the reader an overview and basic idea of how a wireless patient monitoring system works over the 4G Network. An increasing number of ICT firms, healthcare and medical institutions are investing heavily on remote patient monitoring systems technologies and this thesis provides the reader the insight of how such systems work and how they can be implemented

Energy Neutral Activity Monitoring:Wearables Powered by Smart Inductive Charging Surfaces

Wearable technologies play a key role in the shift of traditional healthcare services towards eHealth and self-monitoring. Maintenance overheads, such as regular battery recharging, impose a limitation on the applicability of such technologies in some groups of the population. In this paper, we propose an activity monitoring system that is based on wearable sensors that are powered by textile inductive charging surfaces. By strategically positioning these surfaces on pieces of furniture that are routinely used, the system passively charges the wearable sensor whilst the user is present. As a proof-of-concept example, experiments conducted on a prototype implementation of the system suggest that 36 minutes of daily desktop computer usage are on average sufficient to maintain a wearable sensor energy neutral