Multi agent system for estimation of cardiovascular parameters

Many cardiovascular diseases can be avoided by continuous monitoring cardiovascular parameters. Heart rate, electrocardiogram, blood pressure and pulse wave velocity are the most important and popular cardiovascular parameters. These parameters can be measured by different sensors that have been developed and improved to achieve reliable, accurate and continuous measurements. A part of the processing of theses sensors data, to get the related information, is parameters estimation. This paper presents a new concept to estimate cardiovascular parameters via using a new multi-agent system; that combines two independent methods; first method depends on pulse wave velocity (PWV), while second method depends on heart rate and artery resistance. The outcome of this multi-agent system is a continuous and reliable estimation of cardiovascular parameters by using non-invasive, Cuffless cheap sensors. © 2005 IEEE

Design and Development of a Bilateral Therapeutic Hand Device for Stroke Rehabilitation

The major cause of disability is stroke. It is the second highest cause of death after coronary heart disease in Australia. In this paper, a post stroke therapeutic device has been designed and developed for hand motor function rehabilitation that a str

The Ability of Green Tea (Camellia sinensis) Extract in Modulating the Cytogenetic and Haematological Effects of Mitomycin C in Albino Male Mice

The present study aimed to investigate the toxic and mutagenic and anti – mutagenic effects of the aqueous extract (5, 10 and 15 mg/kg) of green tea (Camellia sinensis) in modulating the genotoxic effects of mitomycin C (MMC). Albino male mice (Mus musculs) were employed as a biological system and four parameters were performed in vivo; total leucocyte count, mitotic index, chromosomal aberrations and micronucleus formation. The plant extract was evaluated through three types of treatments. In the first, the extract was given alone orally. While the second and third treatment included two types of interactions with MMC; pre – and post – MMC treatments. All treatments were paralleled by negative and positive controls. In the first treatment, the dose 15 mg/kg of green tea extract enhanced the parameters investigated and a significant increase was observed in total count of leucocyte (8070 cells/cu. mm. blood) as compared to either negative (6900 cells/cu. mm. blood) or positive (5060 cells/cu. mm. blood) controls, Such observation was positively correlated with the mitotic index. In contrast, the spontaneous formation of micronuceli and chromosomal aberrations were decreased in the three investigated doses of the extract. The results showed that the plant extract had no genotoxic or mutgenic effects. In the second and third treatments, green tea extract showed a good performance in protecting the bone marrow cells in mice against genotoxic MMC effect by increasing the total leucocyte count and mitotic index and decreasing the chromosomal aberration and mironuclei when the treatment were before or after the MMC

Vibration of circumferentially stepped-thickness piezoelectric cylindrical shells

In this work, thickness variations are introduced around the circumference of a piezoelectric cylindrical shell. The aim is to investigate the vibration characteristics of the shells and the effect of these step-thickness variations on the mode shape of vibration. These thickness variations require stress distribution analysis as well to avoid failure of the cylindrical shell. To this aim, two configurations of stepped-thickness shells with two and three circumferential thickness variations are investigated using FEA software, ANSYS. The results show that these steps assist in localizing vibration in the thin sections and excite mode shapes having the same circumferential wave number as the number of thickness variations. This can be a suitable approach to control and forcibly excite certain vibration mode shapes, which might be required for some applications

Estimation of Torque Based on EMG using ANFIS

© 2017 The Authors. There are wide verities of possible human movements that involve a range from the gait for the lifting of a load by a factory worker to the performance of a superior athlete. Output of the movement can be described by a large number of kinematic variables like knee joint angle, torque. This paper proposes a system that contains a non-parametric model with EMG signal of two muscles is used as input to estimate torque. The mapping of EMG to any joint dynamics is very subject dependent. It also depends on walking, running, jumping or climbing. Each type of posture consists of combination of isometric, eccentric and concentric type of muscle contraction with different intensity level depending on velocity, angle and lifted weight (muscle activation level). To capture the EMG signal pattern which is complex and so dynamic in time and space, an adaptive feature in computational intelligence is desired which will not only learn but also make decision based on EMG channel signal pattern to estimate torque. The EMG signal has been collected from volunteer who has completed the knee joint extension with maximum voluntary contraction (MVC) at different degree/sec ranging from 5deg/Sec to 360deg/Sec. The volunteer was also asked to perform extension with moderate and low effort against different impedance like 5deg/Sec, 20deg/Sec, and 45deg/Sec. RMS feature along with 2nd order digital filter has been used to smooth the raw EMG signal. The proposed study is intended to explore an ANFIS like Neuro-Fuzzy type knowledge based adaptive network with embedded RBF kernel neuron to estimate torque

Significance of Elastance Variation on Respiratory System Dynamics

ABSTRACT The sensitivity of the respiratory system dynamic response to variations in the wall elastance is investigated. The acoustical approach is used to determine the impedance at the throat using impedance recursion formulas. Both symmetric and asymmetric structures are considered. The response of the lung structure indicates that when the airway wall elastance varies, as the case during an asthma attack, the overall normalized input impedance frequency spectrum could be used to give a reasonable signature for identifying such abnormality

Hypoxia-Modified Cancer Cell Metabolism

While oxygen is critical to the continued existence of complex organisms, extreme levels of oxygen within a system, known as hypoxia (low levels of oxygen) and hyperoxia (excessive levels of oxygen), potentially promote stress within a defined biological environment. The consequences of tissue hypoxia, a result of a defective oxygen supply, vary in response to the gravity, extent and environment of the malfunction. Persistent pathological hypoxia is incompatible with normal biological functions, and as a result, multicellular organisms have been compelled to develop both organism-wide and cellular-level hypoxia solutions. Both direct, including oxidative phosphorylation down-regulation and inhibition of fatty-acid desaturation, and indirect processes, including altered hypoxia-sensitive transcription factor expression, facilitate the metabolic modifications that occur in response to hypoxia. Due to the dysfunctional vasculature associated with large areas of some cancers, sections of these tumors continue to develop in hypoxic environments. Crucial to drug development, a robust understanding of the significance of these metabolism changes will facilitate our understanding of cancer cell survival. This review defines our current knowledge base of several of the hypoxia-instigated modifications in cancer cell metabolism and exemplifies the correlation between metabolic change and its support of the hypoxic-adapted malignancy

Towards the Discrimination of Primary and Secondary Headache: An Intelligent Systems Approach

We consider the use of intelligent systems to address the long-standing medical problem of diagnostic differentiation between harmful (secondary) and benign (primary) headache conditions. In secondary headaches, the condition is caused by an underlying pathology, in contrast to primary headaches where the production of pain represents the sole constituent of the disorder. Conventional diagnostic paradigms carry an unacceptable risk of misdiagnosis, leaving patients open to potentially catastrophic consequences. Intelligent systems approaches, grounded in artificial intelligence, are adopted in this study as a potential means to unite contributions from multiple settings, including medicine, the life sciences, pervasive computation, sensor technologies, and autonomous intelligent agency, in the fight against headache uncertainty. In this paper, we therefore present the first steps in our research towards a data intensive, unified approach to headache dichotomisation. We begin by presenting a background to headache and its classification, followed by analysis of the space of confounding symptoms, in addition to the problem of primary and secondary condition discrimination. Finally, we proceed to report results of a preliminary case study, in which the epileptic seizure is considered as a manifestation of a headache generating neuropathology. It was found that our classification approach, based on supervised machine learning, represents a promising direction, with a best area under curve test outcome of 0.915. We conclude that intelligent systems, in conjunction with biosignals, could be suitable for classification of a more general set of pathologies, while facilitating the medicalisation of arbitrary settings

THREE-DIMENSIONAL HOLOGRAPHIC MICROWAVE IMAGING ARRAY: EXPERIMENTAL INVESTIGATION OF TUMOUR DETECTION IN BREAST PHANTOM

ABSTRACT This paper extends our previously presented twodimensional (2-D) Holographic Microwave Imaging Array (HMIA) system for early breast tumour detection to threedimensional (3-D) imaging, and demonstrates its efficacy using experimental data obtained with a breast phantom. This work describes an experimental setup to collect data to form a 3-D breast image. The obtained experimental result proves that the 3-D HMIA system has potential to become a screening and diagnostic tool that could supplement clinical breast examination through its sensitivity, quantitative record storage, ease-of-use, and inherent low cost