Wearable Kinesthetic System for Joint Knee Flexion-Extension Monitoring In Gait Analysis

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.

Ultrasound Guided Noninvasive Measurement of Central Venous Pressure

Central venous pressure (CVP) is a measure of the mean pressure within the thoracic vena cava, which is the largest vein in the body and responsible for returning blood from the systemic circulation to the heart. CVP is a major determinant of the filling pressure and cardiac preload, and like any fluid pump, the heart depends on an adequate preload to function effectively. Low venous return translates into a lower preload and a drop in overall cardiac output, a relationship described by the Frank-Starling Mechanism. CVP is an important physiological parameter, the correct measure of which is a clinically relevant diagnostic tool for heart failure patients. In addition to other vitals such as heart rate and mean arterial pressure, accurate measures of central venous pressure through simple diagnostic instrumentation would provide physicians with a clear picture of cardiac functionality, and allow for more targeted treatment. Recent literature has also shown that measuring CVP can be an important hemodynamic indicator for the early identification and treatment of more widespread conditions, such as sepsis (Rivers, Nguyen, Havstad, & Ressler, 2001). With over five million patients (American Heart Association, http://www.americanheart.org/presenter. jhtml) in the U.S. presenting with heart failure-like symptoms annually, a current challenge for physicians is to obtain a quick and accurate measure of a patient’s central venous pressure in a manner that poses minimum discomfort.

Telemedicine and Information Technology for Disaster Medical Scenarios

Disasters constitute events which are catastrophic in nature. Such events critically threaten the health, safety, and lives of people and their environment (and even aspects of the global environment), and as a result, overwhelm the affected community’s emergency response capacity. Globally, a major disaster occurs almost daily. Consequently, disaster events are virtually an everyday fact of life. Emergency medical services constitute one important aspect of disaster responses. Those populations affected by disasters require a complete range of health services and the appropriate mechanism of delivery. In this respect, increasingly, information technology is playing a greater role. Disaster medicine has become more than merely a mass-casualty, and affected health response; the affected population’s needs are assessed, which range from medical requirements, to rapidly coordinating and providing casualty, routine, and preventive health services. These kinds of assessments are significantly more effective, given the appropriate deployment of current information technology.

Support Vector Machine Classification applied on Weaning Trials Patients

The most common reason for instituting mechanical ventilation is to decrease a patient’s work of breathing. Many attempts have been made to increase the effectiveness on the evaluation of the respiratory pattern by means of respiratory signal analysis. This work suggests a method of studying the lying differences in respiratory pattern variability between patients on weaning trials. The core of the proposed method is the use of support vector machines to classify patients into two groups, taking into account 35 features of each one, previously extracted from the respiratory flow. 146 patients from mechanical ventilation were studied: Group S of 79 patients with Successful trials, and Group F of 67 patients that Failed on the attempt to maintain spontaneous breathing and had to be reconnected. Applying a feature selection procedure based on the use of the support vector machine with leave-one-out cross-validation, it was obtained 86.67% of well classified patients into the Group S and 73.34% into Group F, using only eight of the 35 features. Therefore, support vector machines can be an interesting classification method in the study of the respiratory pattern variability.

Source Localization of Subtopographic Brain Maps for Event Related Potentials (ERP)

Event-related potentials (ERP) are transient brain responses to cognitive stimuli, and they consist of several stationary events whose temporal frequency content can be characterized in terms of oscillations or rhythms. Precise localization of electrical events in the brain, based on the ERP data recorded from the scalp, has been one of the main challenges of functional brain imaging. Several currentDensity estimation techniques for identifying the electrical sources generating the brain potentials are developed for the so-called neuroelectromagnetic inverse problem in the last three decades (Baillet, Mosher, & Leahy, 2001; Koles, 1998; Michela, Murraya, Lantza, Gonzaleza, Spinellib, & Grave de Peraltaa, 2004; Scherg & von Cramon, 1986).

The Relevance of Computer-Aided-Diagnosis Systems in Microscopy Applications to Medicine and Biology

In this article, we discuss the use of computerbased systems in microscopy, focusing on cytological images. We initially present recent results on image segmentation, and then we argue that it makes sense moving from a structural approach to a semantic interpretation of micrographs. In this respect, we focus on the relevance of using CAD tools to overcome the current limitations of microscopy, investigating several peculiar objectives of such systems. A short review of the literature demonstrates that the development of a flexible CAD applicable to various working scenarios is a future trend in microscopy healthcare systems. To support our position, we briefly describe a tool that analyzes and classifies fluorescence images.

Patients on Weaning Trials Classified with Neural Networks and Features Selection

One of the challenges in intensive care is the process of weaning from mechanical ventilation. We studied the differences in respiratory pattern variability between patients capable of maintaining spontaneous breathing during weaning trials, and patients that fail to maintain spontaneous breathing. In this work, neural networks were applied to study these differences. 64 patients from mechanical ventilation are studied: Group S with 32 patients with Successful trials, and Group F with 32 patients that Failed to maintain spontaneous breathing and were reconnected. A performance of 64.56% of well classified patients was obtained using a neural network trained with the whole set of 35 features. After the application of a feature selection procedure (backward selection) 84.25% was obtained using only eight of the 35 features.

PACS Contribution to Hospital Strategy via Improved Workflow

This chapter investigates the adequacy of BSC for a holistic evaluation of the workflow impacts of a PACS implementation. It asks whether a theoretical model such as BSC adequately captures the reality of how such technology is used. The approach taken is radical in that it is built on a consideration of the fundamentals of hospital strategy. The BSC is then modified to incorporate qualitative themes rather than performance measures to reflect the fundamentally qualitative nature of the clinical values of hospital strategy. In so doing, this chapter develops a framework that is relevant to a hospital’s not-for-profit and clinical strategies.

Online Nurse Education

In many countries, healthcare professionals are required to participate annually in compulsory continuing medical education (CME). The effort involved in providing wide-scale training led the Italian Ministry of Health to support pilot courses using online distance learning. This article reports the results of a short survey which aimed to gauge the potential of online CME for nurses in Italy. Most of the 152 respondents, all of whom had completed an online course, supported the inclusion of some form of collaborative learning. Three possible market segments for online learning emerged from the study: nurses who prefer to study alone, those who would appreciate collaborative activities well-integrated into course design, and those who would prefer courses that include online collaboration of any kind. The authors conclude that online learning is a suitable mode for enabling participation in CME for accreditation, but caution that further research is required to confirm that the preferences of nurses who have experienced online distance learning are shared by those who have not.