bluuebunny/crossref_metadata_2025 huggingface dataset:
Kansei Experience
Authors: Salem Ben , Nakatsu Ryohei , Rauterberg Matthias
Published: May 2011

We propose that Information and Communication Technology should deliver a new experience to the user. We call this experience Kansei Experience. To deliver it we advocate the reliance on a new computing paradigm called cultural computing. Within this paradigm, we develop the concept of Kansei Media and how it could be implemented via Kansei Mediated Interaction. Kansei Media is about sharing implicit knowledge such as feelings, emotions and moods. We aim for a Kansei Experience, rendered by Kansei Media, which relates to reality, and enhances it to enlighten the user. To do so we investigate the aesthetics of the experience we wish to produce. Finally, to develop the concept of Kansei Mediated Experience we refer two cultures (Western and Eastern) and use famous stories from both as means of delivering guidelines for the implementation of Kansei Experience.
Comparing Learning Methods
Authors: Hidalgo-Herrero Mercedes , Rodríguez Ismael , Rubio Fernando
Published: May 2011

In this article we perform some experiments to study how an automatic system learns a set of rules from its interaction with an artificial environment. In particular, we are interested in comparing these capabilities to the skills shown by humans to learn the same rules in similar conditions. We perform this analysis by conducting two experiments. On the one hand, we observe the evolution of the automatic learning system in terms of its performance along time. At the beginning, the system does not know the rules, but it can observe the positive/negative results of its decisions. As its knowledge about the environment becomes more precise, its performance improves. On the other hand, seventy students faced the same artificial environment in the same conditions, though this time the experiment was presented as a game. The objective of the game consists in gaining points, but the rules of the game are not known a priori. So, there is a clear incentive for finding them out. We use these experiments to compare the learning curves of both humans and automatic systems, and we use this information to analyze the similarities/differences between both learning processes. In particular, we are interested in assessing how close the automatic system is from passing the Turing test.
Knowledge Management Toolkit for SMEs
Authors: Fink Kerstin , Ploder Christian
Published: May 2011

The discipline of knowledge management is no longer emerging in large organizations, but also small and medium-sized enterprises (SMEs) are focusing on finding the right process that will allow them to make advantages of their intellectual capital. Using survey data from 219 small and medium-sized enterprises in Austria and Switzerland, this article illustrates the four key knowledge processes (1) knowledge identification, (2) knowledge acquisition, (3) knowledge distribution, and (4) knowledge preservation for SMEs and also reports the findings of the empirical study designed to allocate cost-efficient software products to each of the four knowledge processes. As a result a knowledge toolkit for SMEs that integrates knowledge processes, methods and software tool for decision support making is given. Finally, the social view of knowledge management to SMEs is discussed, showing that the use of information technology is currently far more important than the integration of a social-cognitive perspective.
A Framework for Managing the Life Cycle of Knowledge in Global Organizations
Authors: Salisbury Mark
Published: May 2011

This chapter describes a framework for managing the life cycle of knowledge in global organizations. The approaches described in this chapter were initially used to successfully build a knowledge dissemination system for the laboratories and facilities that are under the direction of the United States Department of Energy (DOE) (Salisbury & Plass, 2001). The follow-on work to this effort was the development of a collaboration application that fed the dissemination system for the DOE laboratories and facilities. The resulting system managed the life cycle (creation, preservation, dissemination and application) of knowledge for the DOE laboratories and facilities (Salisbury, 2003). While seen as a highly successful system, a significant problem was the difficulty in identifying the right knowledge that needed to get to the right people at the right time. This is also a significant problem for global organizations that need to share their knowledge across international boundaries. What is needed to solve this problem for global organizations is a systemic way that can be applied as an organizational strategy to identify this knowledge, the people that needed it, and the time it should be accessible. This chapter focuses on the use of performance objectives for managing the “right” knowledge in a global organization. In the next section, the background of the projects that inspired the framework is introduced. Next, the framework itself is discussed: the theoretical foundation for the framework, Work Processes, Learning Processes, and Methodologies for managing the life cycle of knowledge in a global organization. (For a full discussion of this approach in book form, see Salisbury, 2009).
Social Network Structures for Explicit, Tacit and Potential Knowledge
Authors: Smedlund Anssi
Published: May 2011

The purpose of this conceptual article is to develop argumentation of the knowledge assets of a firm as consisting of three constructs, to extend the conventional explicit, tacit dichotomy by including potential knowledge. The article highlights the role of knowledge, which has so far not been utilized in value creation. The underlying assumption in the article is that knowledge assets can be thought of as embedded in the relationships between individuals in the firm, rather than possessed by single actors. The concept of potential knowledge is explained with selected social network and knowledge management literature. The findings suggest that the ideal social network structure for explicit knowledge is centralized, for tacit knowledge it is distributed, and for potential knowledge decentralized. Practically, the article provides a framework for understanding the connection between knowledge assets and social network structures, thus helping managers of firms in designing suitable social network structures for different types of knowledge.
A Simulation System for Evaluating Knowledge Management System (KMS) Implementation Strategies in Small to Mid-Size Enterprises (SME)
Authors: Judge Robert
Published: May 2011

Companies create and use information and knowledge every day. The problem all companies have is figuring out how to efficiently discover that knowledge, capture it, share it, and use it to gain competitive advantage in the marketplace. This chapter describes a simulation model designed to provide small to mid-sized enterprises (SME) with a means to understand the impact of barriers and value accelerators on the flow of organizational information. The simulation model reports the throughput of information (number of information packets received per day) and its timeliness (average duration until packet arrival) and provides for sensitivity analysis of the parameters describing a strategy. Comparisons among model instantiations allow an organization to determine the appropriate strategy for current and future KMS efforts.
Cocreating Corporate Knowledge with a Wiki
Authors: Meloche Joseph A. , Hasan Helen , Willis David , Pfaff Charmaine C. , Qi Yan
Published: May 2011

Wikis have a growing reputation on the open Internet for producing evolving stores of shared knowledge. However, such democratic systems are often treated with suspicion within corporations for management, legal, social, and other reasons. This article describes a field study of a corporate Wiki that has been developed to capture, and make available, organisational knowledge in a large manufacturing company as an initiative of their Knowledge Management (KM) program. As this approach to KM is a controversial and rapidly changing phenomenon, a Q Methodology research approach was selected to uncover employees’ subjective attitudes to the Wiki. Activity Theory was used to provide a deeper interpretation of the findings of the Q-study. The results are enabling the firm to more fully exploit the potential of the Wiki as a ubiquitous tool for successful tacit and explicit knowledge management as more employees are encouraged to participate in a process of cocreating the store of corporate knowledge. The article also demonstrates how meaningful and rigorous research on this new democratic direction of corporate KM should continue.
Assessing the Impact of Knowledge Transfer Mechanisms on Supply Chain Performance
Authors: McLaughlin Stephen
Published: May 2011

With the complexity of organizations increasing, it is becoming vitally important that organizations understand how knowledge is created and shared around their core business processes. However, many organizations deploy technology without due consideration for how their employees access, create and share information and knowledge. This chapter explores the subject empirically through the study of how employees work with information and knowledge around a core business function – in this case a supply chain process. In order to do this the organization needs to be viewed for a network perspective as it relates to specific business processes. Viewing the organization in this way enabled the author to see how employee’s preferred knowledge and information transfer mechanisms varied across the core process. In some cases the identified transfer mechanisms where at odds with the prescribed organization wide mechanisms. However, when the organization considered the employee’s preferred transfer mechanisms as part of an overall process improvement, the E2E supply chain performance was seen to improve significantly.
Capturing Tacit Knowledge from Transient Workers
Authors: Hamza Salah Eldin Adam
Published: May 2011

This article studies the way tacit knowledge is dealt with in a high turnover business environment through a qualitative research approach in an engineering organization with respect to organizational culture and values and the effect in competitive stance. The study found peer review process and managerial/supervisory style to be effective in enabling new employees in a short time with knowledge critical for them to do a successful job, core values, and open-door policy to be necessary factors in forming a fertile environment for a quick tacit knowledge harvesting. The study also showed that a good competitive stance and customer satisfaction can be achieved and maintained through implementation of a rigorous peer review process. The study revealed noneffective utilization of knowledge management (KM) technical resources. The study directs future research towards evaluating possible objectives for utilization of KM technological resources, timeline for effective codification of tacit knowledge, and responsibilities for handling resources.
Utilizing the Rasch Model to Develop and Evaluate Items for the Tacit Knowledge Inventory for Superintendents (TKIS)
Authors: Mueller Christian E. , Bradley Kelly D.
Published: May 2011

Tacit knowledge was originally introduced into the professional literature by Michael Polanyi and later made popular by researchers in a variety of domains. Measuring this implicit form of procedural knowledge requires multiple approaches to adequately “capture” what is often known, but not easily articulated. The present study combines use of Sternberg et al.’s framework for capturing domain-specific tacit knowledge with that of Rasch modeling to develop and validate items for use on a newly developed tacit knowledge inventory. Development of the Tacit Knowledge Inventory for Superintendents (TKIS) occurred in three phases, including two phases of piloting and Rasch analysis. For illustrative purposes, presentation of results is limited to the Rasch analyses conducted on interpersonal tacit knowledge items. However, the methodology extends its usefulness to researchers and practitioners to guide the development process of similar assessments.
Exploring Qualitative Differences in Knowledge Sources
Authors: Hallin Carina Antonia , Øgaard Torvald , Marnburg Einar
Published: May 2011

Focusing on knowledge management (KM) and strategic decision making in service businesses through the constructs of strategic capital and knowledge sharing, the study investigates qualitative differences in domain-specific knowledge of frontline employees and executives. The study draws on cognitive theory and investigates the extend to which the knowledge of these subject groups is correct with respect to incorporating intuitive judgments by various employee groups into forecasting and following strategic decision making. The authors carried out this investigation through an exploratory study of the subject groups’ confidence and accuracy (CA) performance in a constructed knowledge-based forecasting setting. The groups’ intuitive judgmental performances were examined when predicting uncertain business and industry-related outcomes. The authors surveyed 39 executives and 38 frontline employees in 12 hotels. The analysis is based on a between-participants design. The results from this setting do not fully confirm findings in earlier CA studies. Their results indicate that there are no significant differences in the accuracy of executives (as experts) and frontline employees (as novices). Although executives demonstrate overconfidence in their judgments and frontline employees demonstrate underconfidence, in line with earlier CA theory of experts and novices, the differences we find are not significant. Similarly, the CA calibration performance difference between the two groups is not significant. They suggest, among other reasons, that our findings differ from earlier CA studies because of organizational politics and culture by power distance, social capital, misuse of knowledge and the size of the business.
Neuronal Substrates for Language Processing and Word Priming
Authors: Li Chunlin , Li Xiujun , Wu Jinglong , Kusahara Hiroshi
Published: May 2011

The authors of this chapter studied behavioral performance and brain activities associated with word priming using a Japanese Word Stem Completion (WSC) task. They compared the results of this task with the results of a Korean character cognitive task. Their results showed facilitatory effects on subject performance. The percentage of correct answers in the non-priming (P/N) word condition was 94%, whereas the priming (P/Y) condition yielded 100% correct answers. The average reaction time during the P/N word condition was 1501 ms, whereas it was 978 ms and 3106 ms for the P/N non-word and word P/Y word conditions, respectively. In the fMRI experiment, the same tasks were performed using a block-design experimental paradigm without any overt response from the MRI scanner. As seen in the fMRI results, the bilateral middle and inferior frontal gyrus were active with a right hemispheric prevalence. In addition, the superior and inferior parietal gyrus and the supplementary motor area were activated. The prefrontal-parietal network observed in this study is consistent with the areas that were activated during an English word stem task. These results suggest that the facilitatory effects observed in the WSC test were successful for implicit memory retrieval.
Kinetic Visual Field with Changing Contrast and Brightness
Authors: Hiraki Hidenori , Takahashi Satoshi , Wu Jinglong
Published: May 2011

Dynamic perimetry is the area in which a subject is able to recognize a moving target by eye. It is used in medical tests to diagnose glaucoma and cataracts. Evaluation of the kinetic visual field involves the use of an isopter. In a previous study, the area of the kinetic visual field was shown to become smaller with decreased target brightness and advancing age (Hashimoto, 2003). Moreover, the fields in the left and right eyes are the same. It is also known that dementia patients experience symptoms that lower their ability to recognize objects under conditions of weak contrast between the target object and the background (Trick, Trick, Morris, & Wolf, 1995). However, the exact relationship between this contrast and their visual fields is unknown. In this study, the areas of kinetic visual field were measured quantitatively on normal people as a fundamental study of the early detection of dementia in patients. These results were reported using an improved Goldmann perimeter, which has an electric slider to operate targets at constant speeds.
The Important Role of Lipids in Cognitive Impairment
Authors: Jia Yu , Chen Zheng , Lu Jiangyang , Tingting Liu , Liang Zhou , Xinying Liu , Miao Sun , Xiao Weizhong , Fan Dongsheng , Dehua Chui
Published: May 2011

The current knowledge base on circulating serum and plasma risk factors of the cognitive decline of degenerative Alzheimer’s Disease is linked to cholesterol homeostasis and lipoprotein disturbances (i.e., total cholesterol, 24S-hydroxy-cholesterol, lipoprotein(a), or apolipoprotein E. Lipoprotein lipase (LPL) is also expressed in the brain, with the highest levels found in the pyramidal cells of the hippocampus, suggesting a possible role for LPL in the regulation of cognitive function. Little is currently known, however, about the specific role of LPL in the brain. The authors of this chapter have generated an LPL-deficient mouse model that was rescued from neonatal lethality by somatic gene transfer. The levels of the presynaptic marker synaptophysin were reduced in the hippocampus while the levels of the post-synaptic marker PSD-95 remained unchanged in the LPL-deficient mice. The decreased frequency of mEPSC in LPL-deficient neurons indicated that the number of presynaptic vesicles was decreased, which was consistent with the decreases observed in the numbers of total vesicles and docking vesicles. These findings indicate that LPL plays an important role in learning and memory function, possibly by influencing presynaptic function.
In Vivo Optical Imaging of Brain and its Application in Alzheimer’s Disease
Authors: Kim Jinho , Jeong Yong
Published: May 2011

Recently, various in vivo optical brain imaging techniques have been developed. Here, the authors introduce some of these systems and their application to in vivo brain imaging in a mouse model of Alzheimer’s disease (AD). Two-photon laser scanning microscopy (TPLSM) is specialized for fluorescence imaging in deep tissue with sub-micron resolution and has scanning capabilities, intrinsic optical signal imaging detects the relative changes in oxy- and deoxy-hemoglobin concentration following sensory stimulation and voltage-sensitive dye imaging can directly image the changes of the membrane potential after neural stimulation.
Development of Neurorehabilitation Techniques Using Transcranial Magnetic Stimulation with Voluntary Muscle Contraction
Authors: Touge Tetsuo , Morita Shin , Yamada Eiji , Kusaka Takashi
Published: May 2011

The objective of this study was to elucidate the mechanism of transcranial magnetic stimulation (TMS) with maximum voluntary muscle contraction (MVC) (used to facilitate motor neuron function), the effects of magnetic stimulation at the foramen magnum level with MVC were tested by recording motor evoked potentials (MEPs) and the maximum muscle force. In addition, changes in regional cerebral blood flow (rCBF) due to TMS to the motor cortex during MVC were assessed using near infrared spectroscopy (NIRS). Three MEPs in the first dorsal interosseus (FDI) muscle elicited by TMS to the motor cortex or foramen magnum stimulation were recorded before and then at 15 minutes intervals for 1 hour after 4 MVCs (while subjects maximally pinched a strain-gauge transducer for 2 seconds). Five healthy volunteers received TMS to the left motor cortex while maximally grasping a hand dynamometer for 2 seconds 3 times at 10-second intervals and then repeated TMS with MVC 4 times within 1 hour. Oxy-hemoglobin (Hb) and deoxy-Hb levels were recorded at 24 scalp sites using NIRS while subjects grasped a hand dynamometer with MVC for 5 seconds before and after TMS with MVC. Foramen magnum stimulation with MVC significantly decreased MEP amplitudes after TMS with MVC for 1 hour. Oxy-Hb concentration of the left M1, subtracting the right M1, tended to increase after TMS with MVC. The present results suggest that TMS during MVC induces increased cortical motor neuron excitability. However, further studies are needed to elucidate the mechanism of how TMS with MVC might modulate cortical neuron excitability.
Development of a Bilateral Assistance and Coordination Rehabilitation Training System
Authors: Guo Shuxiang , Song Zhibin
Published: May 2011

Strokes can lead to lasting neurological impairments. Many researchers are studying this process and have made important discoveries. Researchers are starting to investigate the possibility of neurorehabilitation based on neuroplasticity. On the other hand, robot assisted systems have increasingly been used in rehabilitation. However, studies on bilateral assistance rehabilitation systems have seldom been reported. Industrial robot arms were proposed for rehabilitation in other studies, but the inertia and volume of the system was too large, and the stiffness was hard to change. In this research, the authors proposed a novel bilateral assistance rehabilitation approach to treatment of the upper limbs of stroke patients, and a bilateral coordination rehabilitation approach was also proposed. This system is based on virtual reality, and is composed of two haptic devices (PHANTOM Omni), an advanced inertial sensor (MTx), and a computer. The authors have built some force models, in which one hand can be used to assist the other. Bilateral coordination training can also be performed in rehabilitation. In this system, the virtual reality technique is adopted to provide a virtual force model for rehabilitation training of the upper limbs. Furthermore, it is easy to change the stiffness of the system through changing the parameters of the developed virtual force model. The advantages of high safety, compactness, and bilateral assistance and coordination training make the system suitable for home rehabilitation.
A Method for Eliciting the Support Needs from People with Early-Stage Dementia for Maintaining Social Living
Authors: Yamamoto Hirotoshi , Yokokohji Yasuyoshi , Takechi Hajime
Published: May 2011

In the area of welfare engineering, various technological research and developmental efforts have been made to support people with dementia. However, it is not clear if these efforts are based on the real needs of these people. When providing support to people with dementia, it is essential to know exactly what their needs are. Nevertheless, it is not easy to obtain appropriate answers from these people by simply asking “How can we help you?” In addition, it is unlikely that answers from those people will cover all of their support needs. In this chapter, a new method based on the “Person-Centered Care” concept is proposed for eliciting the support needs from, and determining their priorities for people with early-stage dementia who are eager to maintain their social living despite coping with various difficulties. First, all of the actual and potential tasks of social living in their daily life are determined. Support needs are then extracted systematically from those tasks by paying attention to what factors are bothering these people or are confusing to them rather than directly asking the individuals what type of support they want or need. Finally, the support needs are prioritized by taking the degree of the individuals’ confusion and task frequency into consideration. When interviewing people with dementia, special care must be taken to ensure that the individuals who have memory impairment are not overburdened . In the proposed method, visual materials such as cards and boards with illustrations are utilized so that people with dementia can answer questions more easily. Some interviews were conducted based on the proposed method to confirm that support needs can be determined systematically from people with early-stage dementia.
The Effectiveness of Health Informatics
Authors: Paolucci Francesco , Ergas Henry , Hannan Terry , Aarts Jos
Published: May 2011

Health care is complex and there are few sectors that can compare to it in complexity and in the need for almost instantaneous information management and access to knowledge resources during clinical decision-making. There is substantial evidence available of the actual, and potential, benefits of e-health tools that use computerized clinical decision support systems (CDSS) as a means for improving health care delivery. CDSS and associated technologies will not only lead to an improvement in health care but will also change the nature of what we call electronic health records (EHR) The technologies that “define” the EHR will change the nature of how we deliver care in the future. Significant challenges relating to the evaluation of these health information management systems relate to demonstrating their ongoing cost-benefit, cost-effectiveness, and effects on the quality of care and patient outcomes. However, health information technology is still mainly about the effectiveness of processes and process outcomes, and the technology is still not mature, which may lead to unintended consequences, but it remains promising and unavoidable in the long run.
Quality Issues in Personalized E-Health, Mobile Health and E-Health Grids
Authors: Kastania Anastasia N. , Kossida Sophia
Published: May 2011

The electronic healthcare in the modern society has the possibility of converting the practice of delivery of health care. Currently, chaos of information is characterizing the public health care, which leads to inferior decision-making, increasing expenses and even loss of lives. Technological progress in the sensors, integrated circuits, and the wireless communications have allowed designing low cost, microscopic, light, and smart sensors. These smart sensors are able to feel, transport one or more vital signals, and they can be incorporated in wireless personal or body networks for remote health monitoring. Sensor networks promise to drive innovation in health care allowing cheap, continuous, mobile and personalized health management of electronic health records with the Internet. The e-health applications imply an exciting set of requirements for Grid middleware and provide a rigorous testing ground for Grid. In the chapter, the authors present an overview of the current technological achievements in the electronic healthcare world combined with an outline of the quality dimensions in healthcare.
E-Medical Education
Authors: Doyle D. John
Published: May 2011

The World Wide Web has made available a large variety of medical information and education resources only dreamed of two decades ago. This review discusses a number of Web-based e-Medical education concepts and resources likely to be of interest to the medical education community as well as a number of other groups. The resources described focus especially on those that are free and those that have an interactive component. The importance of interactivity and its role in the “constructivist” approach to education is emphasized. Problem-based learning in medical education is also discussed. In addition, the importance of “Web 2.0” and related developments is discussed, along with an overview of Web-based medical simulation software that can complement medical education programs. The importance of podcasts and videocasts as an educational resource are also emphasized. Other concepts such as mashups and the semantic Web are briefly described. Intellectual property issues are also discussed, such as Creative Commons license arrangements, as well as the concept of “information philanthropy”. Finally, the importance of peer-review and technology evaluation for online educational materials is discussed.
Improving Clinical Practice through Mobile Medical Informatics
Authors: Gasmelseid Tagelsir Mohamed
Published: May 2011

This chapter introduces the use of mobile medical informatics as a means for improving clinical practice in Sudan. It argues that mobile medical informatics, combined with new techniques for discovering patterns in complex clinical situations, offers a potentially more substantive approach to understanding the nature of information systems in a variety of contexts. Furthermore, the author hopes that understanding the underlying assumptions and theoretical constructs through the use of the Chaos Theory will not only inform researchers of a better design for studying information systems, but also assist in the understanding of intricate relationships between different factors.
Computer-Aided Diagnosis of Cardiac Arrhythmias
Authors: Tsipouras Markos G. , Fotiadis Dimitrios I. , Michalis Lambros K.
Published: May 2011

In this chapter, the field of computer-aided diagnosis of cardiacdiac arrhythmias is reviewed, methodologies are presented, and current trends are discussed. Cardiac arrhythmia is one of the leading causes of death in many countries worldwide. According to the World Health Organization, cardiovascular diseases are the cause of death of millions of people around the globe each year. The large variety and multifaceted nature of cardiac arrhythmias, combined with a wide range of treatments and outcomes, and complex relationships with other diseases, have made diagnosis and optimal treatment of cardiovascular diseases difficult for all but experienced cardiologists. Computer-aided diagnosis of medical deceases is one of the most important research fields in biomedical engineering. Several computer-aided approaches have been presented for automated detection and/or classification of cardiac arrhythmias. In what follows, we present methods reported in the literature in the last two decades that address: (i) the type of the diagnosis, that is, the expected result, (ii) the medical point of view, that is, the medical information and knowledge that is employed in order to reach the diagnosis, and (iii) the computer science point of view, that is, the data analysis techniques that are employed in order to reach the diagnosis.
Automatic Analysis of Microscopic Images in Hematological Cytology Applications
Authors: Díaz Gloria , Manzanera Antoine
Published: May 2011

Visual examination of blood and bone marrow smears is an important tool for diagnosis, prevention and treatment of clinical patients. The interest of computer aided decision has been identified in many medical applications: automatic methods are being explored to detect, classify and measure objects in hematological cytology. This chapter presents a comprehensive review of the state of the art and currently available literature and techniques related to automated analysis of blood smears. The most relevant image processing and machine learning techniques used to develop a fully automated blood smear analysis system which can help to reduce time spent for slide examination are presented. Advances in each component of this system are described in acquisition, segmentation and detection of cell components, feature extraction and selection approaches for describing the objects, and schemes for cell classification.
Computational Methods in Biomedical Imaging
Authors: Piana Michele
Published: May 2011

Biomedical imaging represents a practical and conceptual revolution in the applied sciences of the last thirty years. Two basic ingredients permitted such a breakthrough: the technological development of hardware for the collection of detailed information on the organ under investigation in a less and less invasive fashion; the formulation and application of sophisticated mathematical tools for signal processing within a methodological setting of truly interdisciplinary flavor. A typical acquisition procedure in biomedical imaging requires the probing of the biological tissue by means of some emitted, reflected or transmitted radiation. Then a mathematical model describing the image formation process is introduced and computational methods for the numerical solution of the model equations are formulated. Finally, methods based on or inspired by Artificial Intelligence (AI) frameworks like machine learning are applied to the reconstructed images in order to extract clinically helpful information. Important issues in this research activity are the intrinsic numerical instability of the reconstruction problem, the convergence properties and the computational complexity of the image processing algorithms. Such issues will be discussed in the following with the help of several examples of notable significance in the biomedical practice.
Module Finding Approaches for Protein Interaction Networks
Authors: Aittokallio Tero
Published: May 2011

This chapter provides an overview of the computational approaches developed for exploring the modular organization of protein interaction networks. A special emphasis is placed on the module finding tools implemented in three freely available software packages, VisANT, Cytoscape and MATISSE, as well as on their biomedical applications. The selected methods are presented in the broader context of module discovery options, ranging from approaches that rely merely on topological properties of the underlying network to those that take into account also other complementary data sources, such as the mRNA levels of the proteins. The author will also highlight some current limitations in the measured network data that should be understood when developing and applying module finding methodology, and discuss some key future trends and promising research directions with potential implications for clinical research.
Techniques for Decomposition of EMG Signals
Authors: Wadhwani Arun Kumar , Wadhwani Sulochana
Published: May 2011

The information extracted from the EMG recordings is of great clinical importance and is used for the diagnosis and treatment of neuromuscular disorders and to study muscle fatigue and neuromuscular control mechanism. Thus there is a necessity of efficient and effective techniques, which can clearly separate individual MUAPs from the complex EMG without loss of diagnostic information. This chapter deals with the techniques of decomposition based on statistical pattern recognition, cross-correlation, Kohonen self-organizing map and wavelet transform.
A Biomimetic Adaptive Algorithm and Micropower Circuit Architecture for Implantable Neural Decoders
Authors: Rapoport Benjamin I. , Sarpeshkar Rahul
Published: May 2011

Algorithmically and energetically efficient computational architectures that operate in real time are essential for clinically useful neural prosthetic devices. Such architectures decode raw neural data to obtain direct motor control signals for external devices. They can also perform data compression and vastly reduce the bandwidth and consequently power expended in wireless transmission of raw data from implantable brain–machine interfaces. We describe a biomimetic algorithm and micropower analog circuit architecture for decoding neural cell ensemble signals. The decoding algorithm implements a continuous-time artificial neural network, using a bank of adaptive linear filters with kernels that emulate synaptic dynamics. The filters transform neural signal inputs into control-parameter outputs, and can be tuned automatically in an on-line learning process. We demonstrate that the algorithm is suitable for decoding both local field potentials and mean spike rates. We also provide experimental validation of our system, decoding discrete reaching decisions from neuronal activity in the macaque parietal cortex, and decoding continuous head direction trajectories from cell ensemble activity in the rat thalamus. We further describe a method of mapping the algorithm to a highly parallel circuit architecture capable of continuous learning and real-time operation. Circuit simulations of a subthreshold analog CMOS instantiation of the architecture reveal that its performance is comparable to the predicted performance of our decoding algorithm for a system decoding three control parameters from 100 neural input channels at microwatt levels of power consumption. While the algorithm and decoding architecture are suitable for analog or digital implementation, we indicate how a micropower analog system trades some algorithmic programmability for reductions in power and area consumption that could facilitate implantation of a neural decoder within the brain. We also indicate how our system can compress neural data more than 100,000-fold, greatly reducing the power needed for wireless telemetry of neural data.
Avatars and Diagnosis
Authors: McDonald Claudia L.
Published: May 2011

Medical education faces a host of obstacles in coming decades requiring that it rethink the way it delivers medical curricula, especially with regard to critical thinking and differential diagnostics. Traditional didactic curricula must be coupled with emerging technologies that provide experiential learning without risk to patients while not eroding the clinical effectiveness of advanced medical learners. Virtual-world technologies have advanced to a level where they must be considered as a method for delivering medical curricula effectively and safely; moreover, research must establish that such systems are reliable and valid means for delivering medical curricula; otherwise, they are of no use to the medical community, regardless of their technical sophistication. Pulse!! The Virtual Clinical Learning Lab is a project designed to explore these issues by developing a reliable and valid learning platform for delivering medical curricula in virtual space, space usually reserved for entertainment videogames.
Telemedicine and Biotelemetry for E-Health Systems
Authors: Übeyli Elif Derya
Published: May 2011

This chapter develops an integrated view of telemedicine and biotelemetry applications. The objective of the chapter is coherent with the objective of the book, which includes techniques in the biomedical knowledge management. Telemedicine is the use of modern telecommunications and information technologies for the provision of clinical care to individuals at a distance and the transmission of information to provide that care. The medical systems infrastructure underpinning this form of medicine, consisting of the equipment and processes used to acquire and present clinical information and to store and retrieve data are explained in detail. An investigation of telemedicine applications in various fields is presented and the likely enormous impact of telemedicine systems on the future of medicine is discussed. For example, bioelectric and physiological variables could be measured by biotelemetry systems. Developing a biotelemetry system and the principal operation of such a system are presented, and its components and the telemetry types are explained. The author suggests that the content of the chapter will assist the medical sector and the general reader in gaining a better understanding of the techniques in the telemedicine and biotelemetry applications.
Tele-Audiology in the United States
Authors: Ribera John
Published: May 2011

The incorporation of telehealth into the daily clinical practice of audiologists in the United States is in its early stages of development. Some initial research has been conducted in order to validate the use of telehealth technologies in providing hearing and balance evaluation and management services (Krumm, Huffman, Dick, & Klich, 2008; Krumm, Ribera, & Klich, 2007;Krumm, Ribera, & Schmiedge, 2005; Lancaster, Krumm, & Ribera, 2008). More research is needed. This chapter suggests possible applications using existing technology and explores the possibility of virtual audiology clinics nation-wide and internationally.
Wearable Kinesthetic System for Joint Knee Flexion-Extension Monitoring In Gait Analysis
Authors: Tesconi Mario , Scilingo Enzo Pasquale , Barba Pierluigi , De Rossi Danilo
Published: May 2011

Posture and motion of body segments are the result of a mutual interaction of several physiological systems such as nervous, muscle-skeletal, and sensorial. Patients who suffer from neuromuscular diseases have great difficulties in moving and walking, therefore motion or gait analysis are widely considered matter of investigation by the clinicians for diagnostic purposes. By means of specific performance tests, it could be possible to identify the severity of a neuromuscular pathology and outline possible rehabilitation planes. The main challenge is to quantify a motion anomaly, rather than to identify it during the test. At first, visual inspection of a video showing motion or walking activity is the simplest mode of examining movement ability in the clinical environment. It allows us to collect qualitative and bidimensional data, but it does not provide neither quantitative information about motion performance modalities (for instance about dynamics and muscle activity), nor about its changes. Moreover, the interpretation of recorded motion pattern is demanded to medical personnel who make a diagnosis on the basis of subjective experience and expertise. A considerable improvement in this analysis is given by a technical contribution to quantitatively analyse body posture and gesture. Advanced technologies allow us to investigate on anatomic segments from biomechanics and kinematics point of view, providing a wide set of quantitative variables to be used in multi-factorial motion analysis. A personal computer enables a realtime 3D reconstruction of motion and digitalizes data for storage and off-line elaboration. For this reason, the clinicians have a detailed description of the patient status and they can choose a specific rehabilitation path and verify the subject progress.
Quantitative Analysis of Hysteroscopy Imaging in Gynecological Cancer
Authors: Neofytou Marios , Pattichis Constantinos , Tanos Vasilios , Pattichis Marios , Kyriacou Eftyvoulos
Published: May 2011

The objective of this chapter is to propose a quantitative hysteroscopy imaging analysis system in gynaecological cancer and to provide the current situation about endoscopy imaging. Recently works, involves endoscopy, gastroendoscopy, and colonoscopy imaging with encouraging results. All the methods are using image processing using texture and classification algorithms supporting the physician diagnosis. But none of the studies were involved with the pre-processing module. Also, the above studies are trying to identify tumours in the organs and no of the are investigates the tissue texture. The system supports a standardized image acquisition protocol that eliminates significant statistical feature differences due to viewing variations. In particular, the authors provide a standardized protocol that provides texture features that are statistically invariant to variations to sensor differences (color correction), angle and distance to the tissue. Also, a Computer Aided Diagnostic (CAD) module that supports the classification of normal vs abnormal tissue of early diagnosis in gynaecological cancer of the endometrium is discussed. The authors investigate texture feature variability for the aforementioned targets encountered in clinical endoscopy before and after color correction. For texture feature analysis, three different features sets were considered: (i) Statistical Features, (ii) Spatial Gray Level Dependence Matrices, and (iii) Gray Level Difference Statistics. Two classification algorithms, the Probabilistic Neural Network and the Support Vector Machine, were applied for the early diagnosis of gynaecological cancer of the endometrium based on the above texture features. Results indicate that there is no significant difference in texture features between the panoramic and close up views and between different camera angles. The gamma correction provided an acquired image that was a significantly better approximation to the original tissue image color. Based on the texture features, the classification algorithms results show that the correct classification score, %CC=79 was achieved using the SVM algorithm in the YCrCb color system with the combination of the SF and GLDS texture feature sets. This study provides a standardized quantitative image analysis protocol for endoscopy imaging. Also the proposed CAD system gave very satisfactory and promising results. Concluding, the proposed system can assist the physician in the diagnosis of difficult cases of gynaecological cancer, before the histopathological examination.
Telemedicine Consultations in Daily Clinical Practice
Authors: Vladzymyrskyy Anton V.
Published: May 2011

This chapter introduces usage of telemedicine consultations in daily clinical practice. Author has describe process of teleconsultation, sample schemes of systems, parties of this process and its roles. Also, main steps of clinical teleconsultation (determination of necessity for teleconsultation, preparation of medical information, observance of ethics and law conditions, preparation of conclusion) are shown. Special part is dedicated to efficiency of teleconsultation – author has propose own complex method for estimation of it. Furthermore, the authors hope that understanding of teleconsultations’ process will make it more accessible and easy-to-use for medical practitioners.
Nursing Documentation in a Mature EHR System
Authors: Hammond Kenric W. , Weir Charlene R. , Efthimiadis Efthimis N.
Published: May 2011

Computerized patient care documentation (CPD) is a vital part of a Patient Care Information System (PCIS). Studying CPD in a well-established PCIS is useful because problems of system adoption and startup do not interfere with observations. Factors interfering with optimal nursing use of CPD areparticularly challenging and of great concern, given today’s shortage of nursing manpower. We describe problems and advantages of CPD usage identified by nurses in a series of research interviews. The chief advantages of CPD for nurses found were better accessibility and reliability of patient care documentation. The main disadvantage was an awkward fit between current input technology and nursing workflow. A second disadvantage was difficulty in translating portrayal of the nursing process into readable documentation that is useful to all members of the clinical team. We interpret these findings to show that explicit consideration of nursing workflow constraints and communication processes is necessary for development of effective nursing documentation systems. Some findings point to a PCIS reconfiguration strategy that is feasible in the short term. Other findings suggest the value of considering mobile and team-oriented technologies in future versions of the PCIS.
Applying Social Network Analysis in a Healthcare Setting
Authors: Parise Salvatore
Published: May 2011

The people-to-people relationships where knowledge work actually gets performed in organizations are called social networks, and they may be in complete contradiction to the information flows expected, based on looking at the organizational chart of formal roles or titles. These informal or social networks are playing an increasingly important role in the healthcare industry, as medical and clinical knowledge needs to be shared effectively between people within and among healthcare organizations. Social network analysis (SNA) is a research methodology to analyze networks between people, groups, organizations, and systems within and across organizations (Wasserman & Faust, 1994). The results of the analysis inform the researcher of both the structure of the network, as well as the positions of nodes or people in the network. This article provides a description of how SNA can be applied in a healthcare setting.