Cyber Physical Security Solutions for Pervasive Health Monitoring Systems

With a rapidly aging population, the healthcare community will soon face severe medical personnel shortage and rising costs. Pervasive Health Monitoring Systems (PHMS) can help alleviate this situation. PHMS provides continuous real-time monitoring of a person’s health using a (usually wireless) network of medical and ambient sensors/devices on the host (patients), called Body Area Networks (BANs). The sensitive nature of health information collected by PHMS mandates that patient’s privacy be protected by securing the medical data from any unauthorized access. The authors’ approach for addressing these issues focuses on a key observation that PHMS are cyber-physical systems (CPS). Cyber-physical systems are networked, computational platforms, deeply embedded in specific physical processes for monitoring and actuation purposes. In this work, they therefore present a novel perspective on securing PHMS, called Cyber Physical Security (CYPSec) solutions. CYPSec solutions are environmentally-coupled security solutions, which operate by combining traditional security primitives along with environmental features. Its use results in not only secure operation of a system but also the emergence of additional “allied” properties which enhance its overall capabilities. The principal focus of this chapter is the development of a new security approach for PHMS called CYPsec that leverages their cyber-physical nature. The authors illustrate the design issues and principals of CYPSec through two specific examples of this generic approach: (a) Physiological Signal based key Agreement (PSKA) is designed to enable automated key agreement between sensors in the BAN based on physiological signals from the body; and (b) Criticality Aware Access Control (CAAC) which has the ability to provide controlled opening of the system for emergency management. Further, they also discuss aspects such as altered threat-model, increased complexity, non-determinism, and mixed critical systems, that must be addressed to make CYPSec a reality.

Is Your Automated Healthcare Information Secure?

Information security issues are a serious matter that organizations from all industries have to deal with. The healthcare industry is no exception. Personally identifiable healthcare information automated by the healthcare industry can be stolen, intercepted, altered, and misused. Acceptable safeguards, therefore, have to be in place in order to ensure the privacy and protection of this information. Without governmental intervention however, it seems unlikely that the healthcare industry will voluntarily implement such safeguards. The Health Insurance Portability and Accountability Act (HIPAA) security rule has emerged and been mandated by Congress from the need of such intervention. The quantitative investigation in this chapter is aimed at determining if covered entities in Washington State are HIPAA security rule ready after two years from the compliance deadline, and if the factors identified through the literature review are a hindrance to HIPAA security rule compliance. This research study revealed that HIPAA Security Rule full compliance is far from achieved; many factors have emerged as impediments to the compliance process, and the way to compliance is complex and costly. Tracking the compliance progress within healthcare institutions in Washington State over the last five years revealed that the reaction to the HIPAA Security Rule was strong around the mandated date; the response after the mandated date, however, has been weak. Covered entities should brace themselves to the new level of enforcement due to the recent American Recovery Reinvestment Act (ARRA).

Challenges of Mobile Health Applications in Developing Countries

Global health care has become an enormous industry worldwide, where trends such as aging populations, environmental and climate changes, catastrophic events, and the spread and evolution of diseases pose significant challenges. With the rapid growth of information technology (IT), wireless technologies, and mobile services, health care processes are able to increasingly benefit from new technological advances and applications built on top of them. Specifically, the area of “Mobile Health” or mHealth, which leverages mobile phone functionality to provide medical and public health services, has become a very promising trend. Wireless and mobile technologies have great potential in improving patient care, reducing costs, streamlining processes, allowing adherence to regulations, and many other health-related activities. However, the developing world faces numerous challenges in realizing the infrastructure and technical expertise required to adopt mHealth solutions and applications. In this chapter, we focus on these challenges in the developing world and highlight existing problems and risks in realizing mHealth applications and services. This chapter also proposes various solutions to overcome these problems.

A Full-Body Wireless Wearable UWB-Based Human Motion Capture and Gait Analysis System

Gait analysis is the systematic study of human walking. Clinical gait analysis, also termed as quantitative gait analysis, provides a detailed clinical introduction to understanding and treating walking disorders. Modern gait analysis is facilitated through the use of specialized equipment. Currently, accurate gait analysis requires dedicated laboratories with complex settings and highly skilled operators. Wearable locomotion tracking systems are available, but they are not sufficiently accurate for clinical gait analysis. On the other hand, wireless healthcare is evolving. Ultra wideband (UWB) is one technology that has the potential for accurate ranging and positioning in dense, multi-path environments. In particular, impulse radio UWB (IR-UWB) is suitable for low-power implementation, which makes it an attractive candidate for wearable and battery-powered health-monitoring systems. The goal of this chapter is to propose and investigate an accurate, full-body, wireless, wearable human locomotion tracking system using UWB radios, with specific application to clinical gait analysis.

A Cooperative Routing Algorithm to Increase QoS in Wireless E-Healthcare Systems

The recent increased interest in distributed and flexible wireless pervasive applications has drawn great attention to WNCS (Wireless Networked Control Systems) architectures based on WSANs (Wireless Sensor and Actuator Networks) and the resulting Quality of Service obtained in specific applications. Particularly, in wireless E-Healthcare systems based on WSANs, providing certain QoS specifications is crucial for the actuators as they perform actions based on the vital data received from sensors. This chapter is concerned with the performance evaluation of a cooperative routing algorithm QBAR (Queue Based Ad hoc Routing algorithm) for wireless E-Healthcare systems. Simulations have been carried out in order to quantify the impact of the proposed algorithm on the overall network performance, and a comparison with the existing AODV algorithm is presented. The algorithm performances are validated by the Matlab/Simulink-based simulator, TrueTime, which facilitates the co-simulation of controller task execution in real-time kernels and in a wireless network environment. The simulation results highlight that “cooperation” strategies between wireless healthcare devices can strongly improve the reliability of the wireless network, and hence, they are suitable and rewarding for the management of the future generation of E-Healthcare systems.

Prioritization of Patient Vital Signs Transmission Using Wireless Body Area Networks

Triage is the process of prioritizing patients based on the severity of their condition when resources are insufficient. Hospitals today are equipped with more and more electronic medical devices. This results in possibly high level of electromagnetic interference that may lead to the failure of medical monitoring devices. Moreover, a patient is usually moved between different hospital settings during triage. Accurate and quick prioritization of patient vital signs in such environments is crucial for making efficient and real-time decisions. In this chapter, a novel in-network solution to prioritize the transmission of patient vital signs using wireless body area networks is proposed; the solution relies on a distributed priority scheduling strategy based on the current patient condition and on the vital sign end-to-end delay/reliability requirement. The proposed solution was implemented in TinyOS, and its performance was tested in a real scenario.

Portable Wireless Device for Automated Agitation Detection

The objective of this chapter is to provide an overview of existing portable medical devices. The chapter then focuses on portable automated agitation detection. The design and prototyping of a device capable of portable wireless agitation detection is detailed. In addition, the agitation detection algorithm, which uses Support Vector Machines (SVM) based on the measurement of skin conductivity, skin temperature, and inter-beat interval, is described. Experimental results pertaining to the performance of the device and the agitation detection are provided. The chapter concludes with challenges to the development of medical portable devices in general and to agitation detection specifically. Some potential future research directions are highlighted.

Android-Based Telemedicine System for Patient-Monitoring

Telemedicine systems are based on a combination of advanced remote monitoring devices, telecommunication technology, and innovative software and hardware. As mobile phones become more powerful and perform more complex interactions between mobile devices to resident software and other server-based software, they have been recognized as effective tools for Telemedicine, and the merging of the Internet and mobile computing introduces new opportunities and challenges in the Telemedicine sector. This chapter describes the development and implementation of an Android-based Telemedicine system for patient-monitoring. The system utilizes Android devices as mobile access terminals for general inquiry and patient-monitoring services. Authorized users can also browse the patients’ general data and monitor blood pressure (BP) on the Web application. The Web applications, written in PHPScript, and embedded into HTML, reside in a content server to store BP readings, patient records, clinic and hospital information, and doctors’ appointments with patients. Moreover, a customized AJAX plugin is used to handle mapping and plotting. For testing our system, an Android phone was used to connect with the biosensor device that was clutched by the patient. Data were successfully retrieved from the sensor device and displayed on the Android phone as well as the website. The system shows how the Android based application can be feasible in remote patient-monitoring and patient data retrieval.

Situation-Aware Ambient Assisted Living and Ambient Intelligence Data Integration for Efficient Eldercare

Pervasive healthcare systems are designed to support elderly and care-dependent people to live an independent life. Recent developments are driven by technological advances of wireless sensor networks and mobile devices, which ease their application in the health- and homecare domain. The integration into pervasive healthcare systems helps to improve the impact and the efficiency of eldercare, while keeping financial efforts at a moderate level. The importance of these issues leads to the development of systems covering situation-aware, ambient assisted living and health data exchange between care institutions and ambient assistant solutions. Various projects within the Ambient Assisted Living (AAL) domain have proven that remarkable results can be achieved by using wireless sensor technology and mobile devices for data collection, but there are still several problems concerning the exchange and integration of healthcare data. This chapter gives an overview about AAL, healthcare related standards, and state of the art approaches for data integration. In addition, best practice projects, which deal with patient-oriented care information, ambient assisted living, as well as ambient intelligence, are covered.

Design and Deployment of a Mobile-Based Medical Alert System

The use of wireless technology for health care delivery is having great impacts in the health care sector on a global scale. However, alert systems in medical institutions are rare. As a result of this, patients find it hard to keep track of scheduled meetings with medical personnel; they also find it difficult to keep track of prescribed medications. These could have adverse impacts on patients’ health, especially for those with chronic diseases. This chapter therefore, presents the design, deployment and evaluation of a mobile-based medical alert system (MAS) for managing diseases where adherence or compliance is paramount for effective treatment. The system alerts the patients and medical practitioners about information and emergencies via text messaging on handheld devices such as mobile phones and PDAs. It also allows users to receive scheduled appointment and medication updates that will facilitate their treatment processes. The prototype application is developed by the incremental software process model and runs on a GSM network.