Excellence in Research and Innovation for Humanity

International Science Index

Commenced in January 1999 Frequency: Monthly Edition: International Paper Count: 8

Medical, Health, Biomedical, Bioengineering and Pharmaceutical Engineering

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  • 8
    Calculation of the Forces Acting on the Knee Joint When Rising from Kneeling Positions (Effects of the Leg Alignment and the Arm Assistance on the Knee Joint Forces)
    Knee joint forces are available by in vivo measurement using an instrumented knee prosthesis for small to moderate knee flexion but not for high flexion yet. We created a 2D mathematical model of the lower limb incorporating several new features such as a patello-femoral mechanism, a thigh-calf contact at high knee flexion and co-contracting muscles' force ratio, then used it to determine knee joint forces arising from high knee flexions in four kneeling conditions: rising with legs in parallel, with one foot forward, with or without arm use. With arms used, the maximum values of knee joint force decreased to about 60% of those with arms not used. When rising with one foot forward, if arms are not used, the forward leg sustains a force as large as that sustained when rising with legs parallel.
    Study and Design of Patient Flow at the Medicine Department of a University Hospital

    Most, if not all, public hospitals in Thailand have encountered a common problem regarding the increasing demand for medical services. The increasing number of patients causes so much strain on the hospital-s services, over-crowded, overloaded working hours, staff fatigue, medical error and long waiting time. This research studied the characteristics of operational processes of the medical care services at the medicine department in a large public university hospital. The research focuses on details regarding methods, procedures, processes, resources, and time management in overall processes. The simulation model is used as a tool to analyze the impact of various improvement strategies.

    Neuroblasts Micropatterning on Nanostructural Modified Chitosan Membranes
    The study describes chitosan membrane platform modified with nanostructure pattern which using nanotechnology to fabricate. The cell-substrate interaction between neuro-2a neuroblasts cell lines and chitosan membrane (flat, nanostructure and nanostructure pattern types) was investigated. The adhered morphology of neuro-2a cells depends on the topography of chitosan surface. We have found that neuro-2a showed different morphogenesis when cells adhered on flat and nanostructure chitosan membrane. The cell projected area of neuro-2a on flat chitosan membrane is larger than on nanostructure chitosan membrane. In addition, neuro-2a cells preferred to adhere on flat chitosan surface region than on nanostructure chitosan membrane to immobilize and differentiation. The experiment suggests surface topography can be used as a critical mechanism to isolate group of neuro-2a to a particular rectangle area on chitosan membrane. Our finding will provide a platform to take patch clamp to record electrophysiological behavior about neurons in vitro in the future.
    Use of Item Response Theory in Medical Surgical Nursing Achievement Examination
    Medical Surgical Nursing is one of the major subjects in nursing. This study examined the validity and reliability of the achievement examination utilizing the Classical Test Theory and Item Response Theory. The study answered the following objectives specifically : ( a) To establish the validity and reliability of the achievement examination utilizing Classical Test Theory and Item Response Theory ; ( b ) To determine the dimensionality measure of items and ( c ) to compare the item difficulty and item discrimination of the Medical Surgical Nursing Achievement examination using Classical Test Theory ( CTT ) and Item Response Theory ( IRT ). The developed instrument was administered to fourth year nursing students (N= 136) of a private university in Manila. The findings yielded the following results: The achievement examination is reliable both using CTT and IRT. The findings indicate person and item statistics from two frameworks are quite alike. The achievement examination formed a unidimensional construct.
    Dynamic Features Selection for Heart Disease Classification
    The healthcare environment is generally perceived as being information rich yet knowledge poor. However, there is a lack of effective analysis tools to discover hidden relationships and trends in data. In fact, valuable knowledge can be discovered from application of data mining techniques in healthcare system. In this study, a proficient methodology for the extraction of significant patterns from the Coronary Heart Disease warehouses for heart attack prediction, which unfortunately continues to be a leading cause of mortality in the whole world, has been presented. For this purpose, we propose to enumerate dynamically the optimal subsets of the reduced features of high interest by using rough sets technique associated to dynamic programming. Therefore, we propose to validate the classification using Random Forest (RF) decision tree to identify the risky heart disease cases. This work is based on a large amount of data collected from several clinical institutions based on the medical profile of patient. Moreover, the experts- knowledge in this field has been taken into consideration in order to define the disease, its risk factors, and to establish significant knowledge relationships among the medical factors. A computer-aided system is developed for this purpose based on a population of 525 adults. The performance of the proposed model is analyzed and evaluated based on set of benchmark techniques applied in this classification problem.
    The Effect of Postural Anomalies on SAQ, Muscular Strength and Flexibility Performance of the Semipro Soccer Athletes
    The objective of the study is to investigate the effect of a footballer-s postural on selected physical fitness components. Twenty-one (21) subjects of the university male footballers under the Sport Excellence Center programme were photographed using qualitative analysis. The postural variables were stratified manually into normal and anomalies group and their flexibility, strength and SAQ performance were compared using the Mann-Whitney Test. The AROM assessment and SAQ test reported no significance difference (Z=-.398, p=0.711, p>0.05), similar to the lower body strength was shown with no significance different (Z=-.493, p=0.640, p>0.05). In contrast, only 1 RM strength test for the upper body strength test shown with a significance different (Z=- 2.537, p=0.009, p
    Comparison of Knowledge Regarding Human Papillomavirus (HPV) and Cervical Cancer in Students with or without Sexual Intercourse

    The aim of our study was to compare knowledge of regarding HPV and cervical cancer in female student of 18 to 26 years old, with or without sexual intercourse. We conducted a questionnaire survey of the students (N=568), in Faculty of Natural Sciences, Tirana, Albania. Sexually experienced students were more likely to have heard of risk factors such as multiple sex partners, sexual intercourse before age 18, having contracted any sexually transmitted diseases, having genital warts, smoking cigarettes, use of oral contraceptive, poor diet or nutrition and using tampons. No significant sexually experience differences were observed in knowledge of the way of transmission of the virus associated with cervical cancer knowledge, the virus associated with cervical cancer knowledge, the prevention of cervical cancer knowledge. On the other hand strong significant sexually experience differences were observed in knowledge of the diagnostic way of cervical cancer and what HPV can cause knowledge.

    Active Segment Selection Method in EEG Classification Using Fractal Features

    BCI (Brain Computer Interface) is a communication machine that translates brain massages to computer commands. These machines with the help of computer programs can recognize the tasks that are imagined. Feature extraction is an important stage of the process in EEG classification that can effect in accuracy and the computation time of processing the signals. In this study we process the signal in three steps of active segment selection, fractal feature extraction, and classification. One of the great challenges in BCI applications is to improve classification accuracy and computation time together. In this paper, we have used student’s 2D sample t-statistics on continuous wavelet transforms for active segment selection to reduce the computation time. In the next level, the features are extracted from some famous fractal dimension estimation of the signal. These fractal features are Katz and Higuchi. In the classification stage we used ANFIS (Adaptive Neuro-Fuzzy Inference System) classifier, FKNN (Fuzzy K-Nearest Neighbors), LDA (Linear Discriminate Analysis), and SVM (Support Vector Machines). We resulted that active segment selection method would reduce the computation time and Fractal dimension features with ANFIS analysis on selected active segments is the best among investigated methods in EEG classification.