COMPUTERIZED RADIAL ARTERY PULSE SIGNAL CLASSIFICATION FOR LUNG CANCER DETECTION

Pulse diagnosis, the main diagnosis method in traditional Chinese medicine, is a non-invasive and convenient way to check the health status. Doctors usually use three fingers to feel three positions; Cun, Guan, and Chi of the wrist pulse, to diagnose the body’s healthy status. However, it takes many years to master the pulse diagnosis. This paper aims at finding the best position for acquiring wrist-pulse-signal for lung cancer diagnosis. In our paper, the wrist-pulse-signals of Cun, Guan, and Chi are acquired by three optic fiber pressure sensors of the same type. Twelve features are extracted from the signals of these three positions, respectively. Eight classifiers are applied to detect the effectiveness of the signal acquired from each position by classifying the pulse signals of healthy individuals and lung cancer patients. The results achieved by the proposed features show that the signal acquired at Cun is more effective for lung cancer diagnosis than the signals acquired at Guan and Chi

SMART EQUIPMENT DESIGN CHALLENGES FOR REAL TIME FEEDBACK SUPPORT IN SPORT

Smart equipment can support feedback in motor learning process. Smart equipment with integrated sensors can be used as a standalone system or complemented with body-attached wearable sensors. Our work focuses on real-time biofeedback system design, particularly on the application of a specific sensor selection. The main goal of our research is to prepare the technical conditions to prove efficiency and benefits of the real-time biofeedback when used in selected motion-learning processes. The most used wireless technologies that are used or are expected to be used in real-time biofeedback systems are listed. The tests performed on two prototypes, smart golf club and smart ski, show an appropriate sensor selection and feasibility of implementation of the real-time biofeedback concept in golf and skiing practice. We are confident that the concept can be expanded for use in other sports and rehabilitation. It has been learned that at this time none of the existing wireless technologies can satisfy all possible demands of different real-time biofeedback applications in sport

Boekbespreking

Bas van Bavel  Manors and Markets. Economy and Society in the Low Countries, 500-1600  Oxford (Oxford University Press) 2010, 492 pp. Bas van Bavel  Manors and Markets. Economy and Society in the Low Countries, 500-1600  Oxford (Oxford University Press) 2010, 492 pp.&nbsp

COMPUTERIZED RADIAL ARTERY PULSE SIGNAL CLASSIFICATION FOR LUNG CANCER DETECTION

Pulse diagnosis, the main diagnosis method in traditional Chinese medicine, is a non-invasive and convenient way to check the health status. Doctors usually use three fingers to feel three positions; Cun, Guan, and Chi of the wrist pulse, to diagnose the body’s healthy status. However, it takes many years to master the pulse diagnosis. This paper aims at finding the best position for acquiring wrist-pulse-signal for lung cancer diagnosis. In our paper, the wrist-pulse-signals of Cun, Guan, and Chi are acquired by three optic fiber pressure sensors of the same type. Twelve features are extracted from the signals of these three positions, respectively. Eight classifiers are applied to detect the effectiveness of the signal acquired from each position by classifying the pulse signals of healthy individuals and lung cancer patients. The results achieved by the proposed features show that the signal acquired at Cun is more effective for lung cancer diagnosis than the signals acquired at Guan and Chi

Sport Biomechanics Applications Using Inertial, Force, and EMG Sensors: A Literature Overview

In the last few decades, a number of technological developments have advanced the spread of wearable sensors for the assessment of human motion. These sensors have been also developed to assess athletes’ performance, providing useful guidelines for coaching, as well as for injury prevention. The data from these sensors provides key performance outcomes as well as more detailed kinematic, kinetic, and electromyographic data that provides insight into how the performance was obtained. From this perspective, inertial sensors, force sensors, and electromyography appear to be the most appropriate wearable sensors to use. Several studies were conducted to verify the feasibility of using wearable sensors for sport applications by using both commercially available and customized sensors. The present study seeks to provide an overview of sport biomechanics applications found from recent literature using wearable sensors, highlighting some information related to the used sensors and analysis methods. From the literature review results, it appears that inertial sensors are the most widespread sensors for assessing athletes’ performance; however, there still exist applications for force sensors and electromyography in this context. The main sport assessed in the studies was running, even though the range of sports examined was quite high. The provided overview can be useful for researchers, athletes, and coaches to understand the technologies currently available for sport performance assessment

New benchmarking methodology and programming model for big data processing

Big data processing is becoming a reality in numerous real-world applications. With the emergence of new data intensive technologies and increasing amounts of data, new computing concepts are needed. The integration of big data producing technologies, such as wireless sensor networks, Internet of Things, and cloud computing, into cyber-physical systems is reducing the available time to find the appropriate solutions. This paper presents one possible solution for the coming exascale big data processing: a data flow computing concept. The performance of data flow systems that are processing big data should not be measured with the measures defined for the prevailing control flow systems. A new benchmarking methodology is proposed, which integrates the performance issues of speed, area, and power needed to execute the task. The computer ranking would look different if the new benchmarking methodologies were used; data flow systems would outperform control flow systems. This statement is backed by the recent results gained from implementations of specialized algorithms and applications in data flow systems. They show considerable factors of speedup, space savings, and power reductions regarding the implementations of the same in control flow computers. In our view, the next step of data flow computing development should be a move from specialized to more general algorithms and applications.Peer ReviewedPostprint (published version

Analysing mouse skin cell behaviour under a non-thermal kHz plasma jet

Plasma jets are extensively used in biomedical applications, particularly for exploring cell viability behaviour. However, many experimental parameters influence the results, including jet characteristics, secondary liquid chemistry and protocols used, slowing research progress. A specific interest of the presented research was skin cell behaviour under a non-thermal kHz plasma jet—a so-called cold plasma jet—as a topical skin treatment. Our research was focused on in vitro mouse skin cell direct plasma treatment with argon as an operating gas. The research was complemented with detailed gas-phase diagnostics and liquid-phase chemical analysis of the plasma and plasma-treated medium, respectively. The obtained results showed that direct plasma jet treatment was very destructive, leading to low cell viability. Even with short treatment times (from 35 s to 60 s), apoptosis was observed for most L929 murine fibroblasts under approximately the same conditions. This behaviour was attributed to plasma species generated from direct treatment and the types of cell lines used. Importantly, the research exposed important points that should be taken under consideration for all further research in this field: the urgent need to upgrade and standardise existing plasma treatment protocols of cell lines; to monitor gas and liquid chemistries and to standardise plasma discharge parameters

Towards best practices in research Role of academic core facilities

Peer reviewe

The decline in stomach cancer mortality: exploration of future trends in seven European countries

Mortality from stomach cancer has fallen steadily during the past decades. The aim of this paper is to assess the implication of a possible continuation of the decline in stomach cancer mortality until the year 2030. Annual rates of decline in stomach cancer mortality from 1980 to 2005 were determined for the Netherlands, United Kingdom, France, and four Nordic countries on the basis of regression analysis. Mortality rates were extrapolated until 2030, assuming the same rate of decline as in the past, using three possible scenarios. The absolute numbers of deaths were projected taking into account data on the ageing of national populations. Stomach cancer mortality rates declined between 1980 and 2005 at about the same rate (3.6–4.9% per year) for both men and women in all countries. The rate of decline did not level off in recent years, and it was not smaller in countries with lower overall mortality rates in 1980. If this decline were to continue into the future, stomach cancer mortality rates would decline with about 66% between 2005 and 2030 in most populations, while the absolute number of stomach cancer deaths would diminish by about 50%. Thus, in view of the strong, stable and consistent mortality declines in recent decades, and despite population ageing, stomach cancer is likely to become far less important as a cause of death in Europe in the future