Catálogo de publicaciones - libros

This chapter presents introductory remarks on computational intelligence in healthcare practice, and it provides a brief outline for each of the succeeding chapters in the remainder of this book.

This chapter introduces synthetic character technologies, surveys the broad range of health-related applications using synthetic characters, and addresses in detail the development and usage of health-related synthetic character applications.

Dietary menu planning is an important part of personalized lifestyle counseling. The chapter describes the results of an automated menu generator (MenuGene) of the web-based lifestyle counseling system Cordelia that provides personalized advice to prevent cardiovascular diseases. The menu generator uses Genetic Algorithms to prepare weekly menus for web users. The objectives are derived from personal medical data collected via forms, combined with general nutritional guidelines. The weekly menu is modeled as a multi-level structure. Results show that the Genetic Algorithm based method succeeds in planning dietary menus that satisfy strict numerical constraints on every nutritional level (meal, daily basis, weekly basis). The rule-based assessment proved capable of manipulating the mean occurrence of the nutritional components thus providing a method for adjusting the variety and harmony of the menu plans. By splitting the problem into well determined subproblems, weekly menu plans that satisfy nutritional constraints and have well assorted components can be generated with the same method that is used for daily and meal plan generation.

As healthcare costs continue to spiral upward, healthcare institutions are under enormous pressure to create cost efficient systems without risking quality of care. Healthcare IT applications provide considerable promises for achieving this multifaceted goal through managing inofrmation, reducing costs, and facilitating total quality management and continuous quality improvement programs. However, the desired outcome can not be achieved if these applications are not being used.

Since the first experiments on digital medical imaging, Pictures Archiving and Communication Systems (PACS) have been gaining acceptance along healthcare practitioners. PACS based infrastructures are currently being driven by powerful medical applications that rely completely on the seamless access to images' databases and related metadata. New and demanding applications such as study co-registration and content based retrieval are already driving PACS into new prominent roles.

In this chapter we will revise the major key factors that have promoted this technology. We will then present our own solution for a Web-based PACS and the results achieved by its use on a Cardiology Department. We will finally consider future applications that are pushing developmental research in this field.

For over one hundred years the electrocardiogram (ECG) remains an extremely useful clinical tool and continues to play a major role in the evaluation and management of patients with known or suspected cardiac disease. Interpretation of the 12-lead ECG is a simplistic solution to the “inverse electromagnetic problem” for the electrical activity of the heart, which is to extract information about the instantaneous electrical state of the cardiac muscle from measurements of the body surface potentials that are generated from the electrical activity of the heart. Although adequate for patient management in most instances, there are conditions for which the sensitivity of the 12-lead ECG is suboptimal, as for example for the diagnosis of a posterior wall myocardial infarction. To enhance the diagnostic value of the ECG, one would need to address in depth and provide an actual solution to the inverse electromagnetic problem.

The paper presents the scenario of the Biomedical technologies in the frame of the Advanced Human-Machine Interface (HMI), with specific application to the direct Brain-Computer communication. This approach relies on the development of new miniaturized system for the unobtrusive measurement of biological signal using wearable or embedded sensors integrated in Advanced HMI to be used in performing a task. In the BCI application the actual goal is enabling the communication for severely disabled people with a future perspective to increase the possibilities offered by this technology and in rehabilitation and health care. This should be possible thanks to its integration in a more complex system of ambient intelligence allowing the control of primary functions at home or through the differentiation of specific system platform supporting other services.