Home
Back
Intelligent Internet Systems

Towards Healthcare based on Ubiquitous Computing

Daming Shi and Richard Comley
School of Engineering and Information Sciences, Middlesex University, London NW4 4BT, UK

Abstract

Ubiquitous computing provides a pervasive networked human-computer interaction using many computational devices simultaneously in such a “transparent” way that the user may not need to be aware of how many devices involved in the use. With the rapid development of internet technologies, mobile phones and GPS, ubiquitous computing will be in every corner in our everyday life. On the other hand, ubiquitous computing for healthcare makes regular people able to afford continuous wellness maintenance and real-time illness diagnosis. With ubiquitous healthcare, trainees/patients can consult professional coaches/therapists through worldwide network and computational devices at all scales. This briefing article can be viewed as a piece of introductory work for the principles of healthcare based on ubiquitous computing, towards which our initial ubiquitous fitness instrument system was exhibited in World IT Show 2010, Seoul.

1. Introduction

The term ubiquitous computing can be interchangeably used with the term pervasive computing, although they emphasize slightly different aspects. Ubiquitous computing provides a pervasive networked human-computer interaction using many computational devices that distributed at all scales. It allows a single user to engage many computational devices simultaneously in such a “transparent” way that the user may not need to be aware of how many devices involved in the use. In the first wave of computing technologies, lots of people had to share one computer. What is happening today is that each person and his/her personal computer are staring uneasily at each other. Next comes ubiquitous computing, the third wave of computing, or “Third Paradigm” computing called by Alan Kay [1].

Mark Weiser coined the phrase "ubiquitous computing" around 1988, and proposed three basic forms for ubiquitous system devices, namely, Tabs in wearable centimetre size, Pads in handheld decimetre size and Boards in meter size [2]. Contemporary human-computer interaction devices available for ubiquitous computing include mobile phones, digital audio players, radio-frequency identification tags, GPS, and interactive whiteboards.

Healthcare can be classified into two relevant areas: illness and wellness. The former refers to treatments after diseases, whereas the latter the ways to prevent diseases. Statistics show that the worldwide population over age 65 is expected to more than double from 357 million in 1990 to 761 million in 2025 [3]. Such a situation demands continuous healthcare in an economic way. Ubiquitous healthcare, or called pervasive healthcare, is a key technology to make healthcare more scalable through ubiquitous computing, such that regular people can afford wellness maintenance, and real-time illness diagnosis. If integrated into a telemedical system, ubiquitous healthcare systems can even alert medical personnel when life-threatening changes occur [4]. With the help of ubiquitous healthcare technology, patient records could be accessed by health-care professionals from any given location by connection to the institution’s information system. Physicians’ access to patient history, laboratory results, pharmaceutical data, insurance information, and medical resources would be enhanced by mobile technology, thereby improving the quality of patient care [5].

The remainder of this paper is organized as follows. The enabling technologies, especially the communication protocol, for healthcare are discussed in Section 2. Section 3 introduces our initial ubiquitous fitness instrument system incorporated with virtual-reality technique. Section 4 concludes the paper.

2. Enabling Technologies for Ubiquitous Healthcare

Ubiquitous healthcare involves three most important enabling technologies: ubiquitous computing, ubiquitous communication, and intelligent user-friendly interfaces [6]. Ubiquitous computing enables the integration of computing devices; ubiquitous communication is concerned with the protocol of data transmission; and intelligent user-friendly interfaces enable natural interaction and control of the environment by the users of the ambient environment. Since ubiquitous communication protocols are different from application to application, it is relatively more important than the other two technologies in ubiquitous healthcare.

The most mature protocol of ubiquitous communication for healthcare is ISO/IEEE 11073, which is a set of standards that specify nomenclature, an abstract data model, a service model, and transport specifications for interoperable bedside devices. The primary goals of the standards are to provide real-time plug-and-play interoperability for patient-connected medical devices and facilitate the efficient exchange of vital signs and medical device data, acquired at the point-of-care, in all health care environments [7].

As shown in Fig. 1, an user end exchanges data with the other ends through a device-dependent drive that communicates with ISO/IEEE 11073 application layer, which can be split into three sub-layers: Association Control Service Element (ACSE), Remote Operations Service Element (ROSE) and an Object Layer (Obj.). The ACSE is responsible for association between the peer ACSE layers and messages to identify the protocol, its version, and any other pertinent information. The application layer is built around the notion of OBJECTS in the object layer. The ROSE defines primitive operations to act upon these objects, passing down the attribute and its value from one of the objects. Each object in ISO/IEEE 11073 is accessed indirectly, and referenced by its handle and attribute. To allow multiple instances of the same object type, each attribute is accessed by using its nomenclature code.


Fig. 1. Conceptual model of ISO/IEEE 11073 protocol

The ISO/IEEE 11073 protocol defines completely interchanged messages and sequence diagrams in a point-to-point medical device (MD) communication and distinguish two roles in that communication: agent that owns data to be transferred, and manager that accepts and processes the agent's data. The protocol also defines three components: the medical device that collects data from patients, the computer engine that receives and processes the data from MDs, and the monitoring server that receives all the processed data. However, one of the drawbacks of ISO/IEEE 11073 is its complexity, which discourages software engineers from developing it. Another drawback is that its transport interfaces are currently limited to serial port (RS-232) and infrared data association (IrDA) only [8].

3. A Fitness Instrument System for Ubiquitous Healthcare

Most of the existing fitness instruments run in an isolated mode, resulting in the users divided into two groups: selftraining and supervised-training. The former is not a safe way for training, whereas the latter is too costly to be affordable for regular people. Nevertheless, even in the second group, only the very professional coaches can play a role of both trainer and therapist. In one word, the traditional fitness instruments cannot be used for the healthcare purpose. In this section, we introduce our initial ubiquitous fitness instrument system, which was exhibited in World IT Show 2010 in Seoul. As overviewed in Fig. 2, the users of this fitness instrument system can enjoy training or racing with other avatars through internet. The vital signs of users can be transmitted to the corresponding servers for expert analysis.


Fig. 2. Illustration of ubiquitous computing and communication of the fitness instrument system.

This experimental system consists of a treadmill, a big screen and a computer that is in charge of ubiquitous communication and virtual-reality-based interface, as shown in Fig. 3. Compared to the traditional fitness instruments, the proposed system has the following advantages. Firstly, since the training procedures can be monitored by professionals, safer trainings or therapies can be conducted. Secondly, virtual reality technique can provide a userfriendly interaction among users and ubiquitous machines. It is envisioned that our initial fitness instrument system will lead to a seamless integration of ubiquitous computing, ubiquitous communication and user-friendly interface.


Fig. 3. Ubiquitous treadmill training system with virtual reality interface.

4. Conclusion

In this paper, the motivations, principles, significance and objectives of ubiquitous healthcare are highlighted. We also introduce our experimental fitness instrument system for U-healthcare, in which trainees/patients can participate in a virtual reality environment, as well as consult remote coaches/therapists. However, there is still a long way to go to develop a quality and practical ubiquitous healthcare system.

References

[1]      URL: http://nano.xerox.com/hypertext/weiser/UbiHome.html.

[2]      M. Weiser, Hot Topics: Ubiquitous Computing, IEEE Computer, October 1993.

[3]     Chronic care in America: a 21st century challenge. 1996, by the Institute for Health & Aging, University of California, for the Robert Wood Johnson Foundation.
URL: http://www.rwjf.org/files/publications/other/ChronicCareinAmerica.pdf.

[4]      N. Saranummi, IT application for pervasive, personal, and personalized health, IEEE Transactions on Information Technology in Biomedicine, 12(1): 1-4, 2008.

[5]     J. Lim, et al., A context-aware fitness guide system for exercise optimization in U-health. IEEE Transactions on Information Technology in Biomedicine, 13(3): 370-379, 2009.

[6]     I. Korhonen, J. Bardram, Introduction to the Special Section on Pervasive Healthcare. IEEE Transactions on Information Technology in Biomedicine, 8(3): 229-234, 2004.

[7]     T. Cooper, ISO/IEEE 11073 Standards for medical devices communication. In: 2nd Joint EMBS-BMES Conference, Houston, 2002.

[8]     M. Martinez-Espronceda, L. Serrano and I. Martinez, Implementing ISO/EEE 11073: Proposal of two different strategic approaches, In: Proceedings of International Conference of IEEE Engineering in Medicine and Biology Society Vancouver, pp. 1805-1808, British Columbia, Canada, 2008.


About the Authors

Daming Shi (M’02-SM’04) received his first PhD degree in mechanical engineering from Harbin Institute of Technology, China, and his second PhD degree in computer science from University of Southampton, United Kingdom, in 1997 and 2002 respectively. He is currently a Reader at Middlesex University, UK and served as an Assistant Professor at Nanyang Technological University, Singapore from 2002 to 2009. Dr Shi is a co-chair of the technical committee on Intelligent Internet System, IEEE Systems, Man and Cybernetics Society. His research areas include machine learning, intelligent ubiquitous computing, image processing and neural networks.


Professor Richard Comley has over 30 years experience in the areas of signal processing and algorithms. He received his PhD in 1978 from City University, London for work on EEG signal processing and is currently the Associate Dean for Research in the School of Engineering and Information Sciences (EIS) at Middlesex University. His research interests include signal processing, image segmentation and complex algorithms.