With the recent consumer interest in computer-based activities designed to improve cognitive performance, there is a growing need for scientific assessment algorithms to validate the potential contributions of cognitive exercises. In this paper, we present a novel methodology for incorporating dynamic cognitive assessment algorithms within computer games designed to enhance cognitive performance. We describe how this approach works for variety of computer applications and describe cognitive monitoring results for one of the computer game exercises. The real-time cognitive assessments also provide a control signal for adapting the difficulty of the game exercises and providing tailored help for elders of varying abilities.

Aa new method of measuring blood pressure (BP) is presented. This technique involves automatic analysis of the wideband external pulse (WEP) recorded by a pressure sensor positioned over the brachial artery during standard BP cuff deflation. Three distinct components of this "K" or "WEP" signal can be defined: K1, K2, and K3 [1]. Each component has a different shape and "appearance/disappearance property. K1 is a low frequency inaudible signal present with cuff pressure above systolic. The K2 signal appears at SP and disappears at Dp (K2-algorithm) and can be used to measure BP. Using this property, the "K2-algorithm" has been shown to be more accurate than the auscultatory technique [1]. To implement an automatic measurement using the K2-algorithm, signal processing techniques are applied to K signals.

Contrast-enhanced magnetic resonance imaging (MRI) is useful to study the infiltration of immune cells, in particular macrophages. Contrast agents, for example ultra-small superparamagnetic iron oxide (USPIO) particles, administered intravenously into the blood stream will be engulfed by macrophages circulating in the circulation system. When a transplanted heart rejects, macrophages and other immune cells will infiltrate the rejecting tissue. Imaged by T*2 weighted MRI, USPIO-labeled macrophages will display dark pixel intensities. Detecting the presence of USPIO particles in the images facilitates the study of heart rejection. We cast the problem of detecting the presence of USPIO-labeled myocardium in the framework of spectral graph theory, and treat our decision function as a level set function on the image. The pixels with positive level set values correspond to the presence of immune cells, and negative to the absence. When the image is modeled by a graph, the spectral analysis of the graph Laplacian provides a basis to represent the level set function. We develop from the Cheeger constant of the graph an objective functional of the level set function. The minimization of the objective leads to the optimal level set function. Experimental results suggest the feasibility of our approach in the study of rejecting hearts.

wHospital is the result of an information technology research project, based on the utilization of a web based application for managing the hospital drugs dispensing. Part of wHospital back bone and its key distinguishing characteristic is the adoption of the digital signature system,initially deployed by the Government of Lombardia, a Northern Italy Region, throughout the distribution of smart cards to all the healthcare and hospital staffs. The developed system is a web-based application with a proposed Health Records Digital Signature (HReDS) handshake to comply with the national law and with the Joint Commission International Standards. The prototype application, for a single hospital Operative Unit (OU), has focused on data and process management, related to drug therapy. Following a multi-faceted selection process, the Infective Disease OU of the Hospital in Busto Arsizio, Lombardia, was chosen for the development and prototype implementation. The project lead time, from user requirement analysis to training and deployment was approximately 8 months. This paper highlights the applied project methodology, the system architecture, and the achieved preliminary results.

The interest in wearable health systems (WHS) originates initially from the need to extend health services out of the hospital and monitor patients over extensive periods of time. Intelligent WIS are integrated systems in contact with or near the body able to sense, process and communicate biomedical,biochemical and physical parameters - and even carry out actions if necessary. Research and development (R&D) in WHS is mainly driven by two different, but complementary,approaches. The first one is "application-pull", stemming from an increased user demand for new solutions in healthcare. The second one is "technology-push", in which technological innovations lead to new systems and products for healthcare solutions. In both approaches, inter-disciplinarity is a key issue. Synergies across multiple domains like biomedical technologies,micro- and nano-technologies, materials engineering, and Information and Communication Technologies (ICT), enable new approaches to support personal health and well-being. These include, for example, unobtrusive personal health monitoring and point-of-care biochemical testing for disease prevention and early diagnosis, as well as follow-up of treatments. This article presents the state-of-the-art on wearable health systems, outlines current research achievements and indicates research trends and challenges in line with these two approaches.

We developed wearable EDA sensor gloves using conducting fabric and embedded system. EDA(Electro-dermal Activity) signal is an electric response on the skin of the human body. There are SCL(Skin Conductance Level) and SCR(Skin Conductance Response) in EDA. Mostly, SCL consists of DC elements. On the other hand, SCR consists of AC elements. We use the relationship between the drowsiness condition and EDA signal We made EDA sensors using conducting fabric instead of Agcl electrode for a more suitable wearable device. And we used an embedded system for EDA signal acquisition and processing instead of a personal computer, which is connected to the EDA sensor gloves through conducting fabric lines. Also, the embedded system is linked to a Notebook PC that shows the results of EDA signal processing analysis and gives proper feedback to the user. This system, for example, can be used in detecting and preventing drowsiness driving accidents for automobile drivers.

This paper attempts to develop a better understanding of the high pulse repetition frequency (HPRF)mode used in ultrasound systems with pulsed wave Doppler capability. It provides both intuition and mathematical analysis to help answer the fundamental question of whether the HPRF mode is feasible at any given depth using a visualization tool called Baker diagrams. The tool provides a better understanding of many of the limitations associated with the HPRF Doppler mode.

Vergence eye movements were recorded from three different populations: healthy young (ages 18-35 years), adaptive presbyopic and non-adaptive presbyopic(the presbyopic groups aged above 45 years) to determine how the variability of the eye movements made by the populations differs. The variability was determined using Shannon Entropy calculations of Wavelet transform coefficients, to yield a non-linear analysis of the vergence movement variability. The data were then fed through a k-means clustering algorithm to classify each subject, with no a priori knowledge of true subject classification. The results indicate a highly significant difference in the total entropy values between the three groups, indicating a difference in the level of information content, and thus hypothetically the oculomotor adaptability, between the three groups.Further, the frequency distribution of the entropy varied across groups.

The centralized and information management are in common use technique of modern management. The management of the medical equipment emphasized in the purchase and the maintenance management in early days,and cost down now is import factor for medical equipment management because the health insurance system causes the hospital budget reduced, so in the cost down strategy is to reduce the amount of money and promoting the efficient of use . Another important subject in medical equipment management is patient safety, so how to ensuring the quality of medical equipment is also having to notice. In the paper, we will provide an architecture for assistant the nursing department to develop a information system on the centralized and information management of valuable medical equipment. Through the system operation we hope can promote the effect and the quality of the medical equipment usage. This system implement up to now has more than half a year, and could acquired some concrete result: the utilization rate promotes doubly, the rate of breaking downs, the borrowed time cuts 75%, the cost downs for equipment purchase and satisfaction increases for user. In this paper, in addition to explaining the above-mentioned result,also discusses the design principle and structure on the whole system. We hope the protocol could be used as for clinical unit to control their valuable equipments and match the authority expectation.

The Polynomial Curve Fitting Method (PCFM) is used firstly on Electrical Impedance Tomography (EIT) to find out the polynomial function of boundary potential distribution according to the measured data in this work. The potential values calculated from the polynomial function can be regarded as measured data. So enough data can be provided to satisfy the requirements of various algorithms. The potential distribution within the domain is obtained approximately according to the equipotential property. Without adding the electrode number and changing data collection strategy, more data can be obtained and regarded as measured data by using the PCFM. With these enough data, the quality of reconstructed image is improved obviously.

Photoplethysmography has been recently studied asa non-invasive indicator of circulatory and respiratory function. In this study, photoplethysmographic (PPG) data were recorded from patients under the influence of anesthesia, but not intubated. Both time and frequency domain features were extracted from the PPG and used as inputs to a neural network classifier. This classifier considers inter-subject variability so that it generalizes well to a large population. This classifier provided 86.1%accuracy to classify segments as being times of 'obstructed' vs.'normal' airways status.

Catecholaminergic polymorphic ventricular tachycardia (CPVT) is a heritable arrhythmia unmasked by exertion or stress, characterized by triggered activity and sudden cardiac death in affected patients. In this study we used a mathematical model to simulate two mutations linked toCPVT, in cardiac calsequestrin (CSQN2) and the ryanodine receptor (RyR2). The aim of the present study is to characterize the mutations responsible for CPVT and establish the mechanistic basis for spontaneous Ca2+ release events that lead to delayed afterdepolarizations (DADs) and triggered arrhythmias. Simulated calcium transients in the mutant CSQN2 model recapitulated the smaller amplitude and time to peak, as well as accelerated recovery from inactivation seen in experiments. When simulated CSQN2-mutant myocytes were paced in current-clamp mode, DADs were observed, suggesting that accelerated recovery of RyR2 induced by impaired luminal Ca2(+) sensing can lead to the triggered activity observed in the mutant CSQN2. Simulations of mutant RyR2 suggest that the hyperactive, "leaky" receptors characteristic of reduced FKBP12.6 function may be centrally involved in triggering DADs. These results provide plausible mechanisms by which defects in RyR2 gating may lead to the cellular triggers of CPVT, with implications for the development of targeted therapies.

The purpose of this project was to determine if the properties of doublet force twitches change with recruitment level. Isometric, human tibialis anterior force twitches were measured in response to singlet and doublet stimulation at several recruitment levels for eight healthy subjects. All doublets showed nonlinear force summation. When normalized to singlet responses at the equivalent recruitment level, doublet peak force, torque-time integral, half pulse width and half decay time changed with recruitment while start time and contraction time did not. Although the number of subjects was small, the results suggest that caution must be exercised when extending doublet properties at full recruitment to partial recruitment conditions.

Neurorobotic control of prosthetic devices may bea viable therapeutic intervention that provides spinal cord injury patients with the ability to use the neuronal activity of populations of single neurons to control an external device (i.e.cursor on a computer screen or robotic arm). However, we are limited by our understanding of how spinal cord injury alters the ability of these neurons to convey information about the intention to move. Therefore, there is a need to develop animal models that 1) describe how population of single neurons encode information about different behavioral tasks (skilled vs.unskilled), 2) determine how this encoding is modulated by spinal cord injury and 3) perform neurorobotic control after spinal cord injury. To address the first question, we developed a rat model of spinal cord transection to evaluate the effects of the injury on the neuronal activity related to hindlimb activity. The model consists of training the rat to press a pedal with its hindlimbs. This paper describes the method that defines both the magnitude and latency of a neuron's activity in terms of its Peri-Event Histogram relative to the animal's movements during the task. The method provides a means by which changes in neural activation can be correlated with changes in behavior.