Dynamic Task Distribution in Mobile Client-Server Cooperation

Dynamic Task Distribution in Mobile Client-Server Cooperation

Piotr Augustyniak (AGH University of Science and Technology, Poland) and Ryszard Tadeusiewicz (AGH University of Science and Technology, Poland)
Copyright: © 2009 |Pages: 37
DOI: 10.4018/978-1-60566-080-6.ch009
OnDemand PDF Download:
No Current Special Offers


This chapter discusses the technical limitations of remote wearable recorders. These are caused mainly by high expectations of mobility and manifest themselves through short autonomy time, low computational power, limited resources, and unacceptable physical size.
Chapter Preview

Technical Limitations Of Remote Wearable Electrocardiographsremote Wearable Electrocardiographs

Telemedicine based on the remote acquisition of various vital signsvital signs (Chiarugi et al., 2002; Nelwan, van Dam, Klootwijk, & Meil, 2002) opens up a wide application area ranging from equipment for clinical use to the home care devices (Gouaux et al., 2002; Maglaveras et al., 2002). Several commercial tele-diagnostic services in the United States and Europe offer the continuous monitoring of cardiac risk people. Such services typically use restricted-access wireless networks of star topology. The interpretive intelligence aimed at the derivation of diagnostic features from recorded time series is implemented either in the recorder or in the supervising server. Both approaches have serious limitations.

The central intelligence model uses the communication channel continuously to report raw signals of high data volume, so it needs the uninterrupted carrier availability, which makes the transmission cost very high. The spread intelligence model assumes that the recording device interprets the signal and issues an alert message in case of abnormalities. Although the spread interpretation intelligence reduces communication costs, the diagnostic quality is affected due to resource limitations typical to a wearable computer. Other alternatives, like a triggered acquisition method typical for the ECG event recorders, suffer from poor reliability since a manually operated device risks missing an event when the patient in pain is unable to start the recording session. Our research aims at combining the advantages of both interpretive intelligence models.

At first glance, the advantages of remote controlled recording devices are twofold:

  • The signal is interpreted online and if necessary transmitted without delay, so that the medical intervention (e.g., rescue action) may start immediately if necessary.

  • The acquisition is controlled by experienced staff with the support of an almost unlimited knowledge base and with reference to previous results.

When considering the additional features of remote programmability, two dimensions should be pointed out: the levels and the aspects of adaptation.

Levels of software adaptation quantitatively describe the interference of the management procedure into the ECG interpretation process. According to the adaptation level, various kinds of programming technology are used to achieve the adaptation aim. The main adaptation levels are software updatesoftware update based on the modification of selected computation coefficients and software upgrades based on the dynamical re-linking of function libraries.

Aspects of software adaptation provide a qualitative description of the changes and the choice of procedures selected for modification in order to achieve overall improvement in the diagnostic quality of a given patient’s status. The management of the software adaptation aspects is complicated by the dependencies between the diagnostic parameters originating from a common branch of the interpretation tree.

In a typical topology of surveillance network (Figure 1), remote wearable recorders are supervised and controlled by a node archiving the captured information. Assuming both device types are equipped with signal interpretation software, the analysis of other constraints leads to the following remarks, which are a background for the proposed adaptive concept:

Figure 1.

Typical topology of surveillance network using wireless digital communication


Complete Chapter List

Search this Book: