Preface

Biomedical Engineering is an interdisciplinary and emergent area that combines engineering with life sciences. The idea of this book is to provide the reader with recent advances and applications in Biomedical Engineering in three particular fields of interest: Biomedical Signal Processing and Modelling, Biomaterials and Prosthetic Devices, and Biomedical Image Processing. The book is a collection of self-contained papers describing specific applications and reviews in these fields. Each paper was properly peer-reviewed by experts before final acceptance and inclusion in the book.

Biomedical Signal Processing and Modelling refers to the use of digital signal processing tools and mathematical models for the characterization and representation of biological systems. In many cases the information available from the system is a time-series related to its current state, hence the role of signal processing is to extract features from time-series that are able to quantify and characterize the state of the biological system. The use and implementation of models is of paramount relevance in life sciences and engineering, mainly when considering ethical and economic issues. However, there is a trade-off between model complexity and accuracy in the representation of the reality. Therefore, modelling biological systems is always a challenging task. The first six chapters of the book are dedicated to this exciting field. The study of these chapters can provide the reader with valuable practical examples of the use of signal processing and modelling. The ideas and methods employed can be easily extended to the reader's own research.

Biomaterials are substances that have been engineered to take a form which is used to direct, by control of interactions with components of living systems, the progress therapeutic and diagnostic procedures. In the past decade, there has been a great advance in this area allowing the improvement of medical treatment and diagnosis. Currently, nanostructures can be used as biomaterials capable of targeting specific living tissues, aiding the process of detection and monitoring of non-communicable diseases such as cancer that is one of the leading global killers. It is expected that in a near future biomaterials can be used in clinical routine as therapy to a number of diseases. Chapters from 7 to 13 illustrate the use of biomaterials in distinct contexts. In addition, some of these chapters also discuss implantable prosthetic devices, which can be seen as a type of biomaterial engineered for providing artificial extension of a

#### X Preface

body part. Prosthetic devices can be used for replacing missing body parts, and also to extend the body function.

Biomedical Image Processing concerns the use of image processing techniques for image analysis, compression and transmission. It is by itself an interdisciplinary research field attracting expertise from applied mathematics, computer science, engineering, statistics, physics, biology and medicine. Computer-assisted image analysis has already become part of clinical routine. However, the new development of high technologies and use of distinct types of imaging modalities have produced new challenges to the field. For instance, how to deal with the increasing volume of data without losing significant information that could be used for diagnosis and treatment. Furthermore, techniques of image analysis can be combined in virtual reality environments in a number of situations, e.g., surgery planning and execution, and also in training. The book brings two chapters (14 and 15) dedicated to this area. It is hoped that the information provided in these chapters can motivate the reader to further explore the field of Biomedical Image Processing.

Finally, I would like to thank my colleagues Dr. Adriano Alves Pereira, Dr. Eduardo Lázaro and Dr. Alcimar B. Soares, of the Postgraduate Program on Biomedical Engineering of the Federal University of Uberlândia in Brazil, for helping me with the task of reviewing the chapters of this book. I do hope the material we have organized can contribute to your knowledge and research.

Have a good reading!

**Prof. Dr. Adriano O. Andrade**

Biomedical Engineering Laboratory (BioLab), Faculty of Electrical Engineering, Federal University of Uberlandia, Brazil

X Preface

extend the body function.

body part. Prosthetic devices can be used for replacing missing body parts, and also to

Biomedical Image Processing concerns the use of image processing techniques for image analysis, compression and transmission. It is by itself an interdisciplinary research field attracting expertise from applied mathematics, computer science, engineering, statistics, physics, biology and medicine. Computer-assisted image analysis has already become part of clinical routine. However, the new development of high technologies and use of distinct types of imaging modalities have produced new challenges to the field. For instance, how to deal with the increasing volume of data without losing significant information that could be used for diagnosis and treatment. Furthermore, techniques of image analysis can be combined in virtual reality environments in a number of situations, e.g., surgery planning and execution, and also in training. The book brings two chapters (14 and 15) dedicated to this area. It is hoped that the information provided in these chapters can motivate the reader to

Finally, I would like to thank my colleagues Dr. Adriano Alves Pereira, Dr. Eduardo Lázaro and Dr. Alcimar B. Soares, of the Postgraduate Program on Biomedical Engineering of the Federal University of Uberlândia in Brazil, for helping me with the task of reviewing the chapters of this book. I do hope the material we have organized

Biomedical Engineering Laboratory (BioLab), Faculty of Electrical Engineering,

**Prof. Dr. Adriano O. Andrade**

Federal University of Uberlandia,

Brazil

further explore the field of Biomedical Image Processing.

can contribute to your knowledge and research.

Have a good reading!

**Section 1** 

**Biomedical Signal Processing and Modelling** 

**Biomedical Signal Processing and Modelling** 

**Chapter 1** 

© 2012 Andrade et al., licensee InTech. This is an open access chapter distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

© 2012 Andrade et al., licensee InTech. This is a paper distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

**Human Tremor:** 

http://dx.doi.org/10.5772/54524

**1. Introduction** 

**Origins, Detection and Quantification** 

Sheila Bernardino Fenelon and Valdeci Carlos Dionisio

to as physiological tremor, whereas the latter as pathological tremor.

by pointing out key unanswered questions in tremor research.

**2. Defining the human tremor** 

employed in its quantification and classification are of paramount importance.

Additional information is available at the end of the chapter

Adriano O. Andrade, Adriano Alves Pereira, Maria Fernanda Soares de Almeida, Guilherme Lopes Cavalheiro, Ana Paula Souza Paixão,

The human tremor is one of the most common movement disorders, which is characterized by repetitive and stereotyped movements. The origins of tremor are still not clear, however tremor can be associated with physiological phenomena, such as ageing, and with neurological disorders, for instance, Parkinson's disease. The first type of tremor is referred

The clinical evaluation of tremor can be a valuable tool for the diagnosis of neuromuscular disorders and also for monitoring their progress. However, in a number of circumstances the discrimination between physiological and pathological tremor may not be clinically evident. In this context, the use of sensors for detecting tremor, and the data analysis tools

In this chapter, the origins, detection and quantification of tremor are discussed. The chapter begins with a review concerning the definition and classification of distinct types of tremor. A review of current theories that explain the origins of tremor are presented. The problem of detecting tremor by using electronic devices is addressed, and new advances in the area of tremor detection are introduced. A review and a critical discussion of the most common tools employed for tremor quantification and classification is provided. The chapter finishes

Tremor is the most common movement disorder characterized by repetitive and stereotyped movements [1]. The human tremor is a clinical manifestation characterized by an
