Abstract: There is no reservation on the outstanding contribution of patient families in restoration of hospitalised patients, hence their consideration as essential component of hospital ward regimen. The psychological and emotional support a patient requires has been found to be solely provided by the patient’s family. However, consideration of their presence as one of the major functional requirements of an inpatient setting design have always been a source of disquiet, especially in developing countries where policies, norms and protocols of healthcare administration have no consideration for the patients’ family. This have been a major challenge to the hospital ward facilities, a concern for the hospital administration and patient management. The study therefore is aimed at obtaining a consensus opinion on the best approach for family integration in the design of an inpatient setting. A one day visioning charrette involving Architects, Nurses, Medical Doctors, Healthcare assistants and representatives from the Patient families was conducted with the aim of arriving at a consensus opinion on practical design approach for sustainable family integration. Patient’s family are found to be decisive character of hospital ward regimen that cannot be undermined. However, several challenges that impede family integration were identified and subsequently a recommendation for an ideal approach. This will serve as a guide to both architects and hospital management in implementing much desired Patient and Family Centred Care.
Abstract: The issues that limit application interoperability is lack of common vocabulary, common structure, application domain knowledge ontology based semantic technology provides solutions that resolves application interoperability issues. Ontology is broadly used in diverse applications such as artificial intelligence, bioinformatics, biomedical, information integration, etc. Ontology can be used to interpret the knowledge of various domains. To reuse, enrich the available ontologies and reduce the duplication of ontologies of the same domain, there is a strong need to integrate the ontologies of the particular domain. The integrated ontology gives complete knowledge about the domain by sharing this comprehensive domain ontology among the groups. As per the literature survey there is no well-defined methodology to represent knowledge of a whole domain. The current research addresses a systematic methodology for knowledge representation using multiple sub-ontologies at different levels that addresses application interoperability and enables semantic information retrieval. The current method represents complete knowledge of a domain by importing concepts from multiple sub ontologies of same and relative domains that reduces ontology duplication, rework, implementation cost through ontology reusability.
Abstract: The rapid aging of the population is a common trend in the world. However, the progress of modern medical technology has increased the average life expectancy. The global population structure has changed dramatically, and the elderly population has risen rapidly. In the face of rapid population growth, it must be noted issues of the aging population must face up to, which are the physiological, psychological, and social problems associated with aging. This study aims to investigate how insurance agents are actively dealing with an aging society, their own aging anxiety, and their exercise habits. Purposive sampling was the sampling method of this study, a total of 204 respondents were surveyed and 204 valid surveys were returned. The returned valid ratio was 100%. Statistical method included descriptive statistics, t-test, and one-way ANOVA. The results of the study found that the insurance agent’s age, seniority, exercise habits to aging anxiety are significantly different.
Abstract: In the wake of recent disasters happening around the world such as earthquake in Italy (January, 2017); hurricanes in the United States (US) (September 2016 and September 2017); and compounding disasters in Haiti (September 2010 and September 2016); to our best knowledge, never has the world seen the need to work on preemptive rather than reactionary measures to salvage this situation than now. Tornadoes are natural hazards that mostly affect mid-western and central states in the US. Tornadoes, like all natural hazards such as hurricanes, earthquakes, floods and others, are very destructive and result in massive destruction to homes, cause billions of dollars in damage and claims many lives. Healthcare facilities in general are vulnerable to disasters, and therefore, the safety of patients, health workers and those who come in to seek shelter should be a priority. The focus of this study is to assess disaster management measures instituted by healthcare facilities. Thus, the sole aim of the study is to examine the vulnerabilities and the design of safe spaces in healthcare facilities in Central US. Objectives that guide the study are to primarily identify the impacts of tornadoes in hospitals and to assess the structural design or specifications of safe spaces. St. John’s Regional Medical Center, now Mercy Hospital in Joplin, is used as a case study. Preliminary results show that the lateral base shear of the proposed design to be 684.24 ton (1508.49kip) for the safe space. Findings from this work will be used to make recommendations about the design of safe spaces for health care facilities in Central US.
Abstract: Many supervised machine learning tasks require
decision making across numerous different classes. Multi-class
classification has several applications, such as face recognition, text
recognition and medical diagnostics. The objective of this article is
to analyze an adapted method of Stacking in multi-class problems,
which combines ensembles within the ensemble itself. For this
purpose, a training similar to Stacking was used, but with three
levels, where the final decision-maker (level 2) performs its training
by combining outputs from the tree-based pair of meta-classifiers
(level 1) from Bayesian families. These are in turn trained by pairs
of base classifiers (level 0) of the same family. This strategy seeks to
promote diversity among the ensembles forming the meta-classifier
level 2. Three performance measures were used: (1) accuracy, (2)
area under the ROC curve, and (3) time for three factors: (a)
datasets, (b) experiments and (c) levels. To compare the factors,
ANOVA three-way test was executed for each performance measure,
considering 5 datasets by 25 experiments by 3 levels. A triple
interaction between factors was observed only in time. The accuracy
and area under the ROC curve presented similar results, showing
a double interaction between level and experiment, as well as for
the dataset factor. It was concluded that level 2 had an average
performance above the other levels and that the proposed method
is especially efficient for multi-class problems when compared to
binary problems.
Abstract: Eco-friendly textiles are gaining importance among the consumers and textile manufacturers in the healthcare sector due to increased environmental pollution which leads to several health and environmental hazards. Hence, the research was designed to cultivate and develop the organic cotton knit, to prepare and characterize the Vetiver oil microcapsules for textile finishing and to access the wash durability of finished knits. The cotton SAHANA variety grown under organic production systems was processed and spun into 30 single yarn dyed with four natural colorants (Arecanut slurry, Eucalyptus leaves, Pomegranate rind and Indigo) and eco dyed yarn was further used for development of single jersy knitted fabric. Vetiveria zizanioides is an aromatic grass which is being traditionally used in medicine and perfumery. Vetiver essential oil was used for preparation of microcapsules by interfacial polymerization technique subjected to Gas Chromatography Mass Spectrometry (GCMS), Fourier Transform Infrared Spectroscopy (FTIR), Thermo Gravimetric Analyzer (TGA) and Scanning Electron Microscope (SEM) for characterization of microcapsules. The knitted fabric was finished with vetiver oil microcapsules by exhaust and pad dry cure methods. The finished organic knit was assessed for laundering on antimicrobial efficiency and aroma intensity. GCMS spectral analysis showed that, diethyl phthalate (28%) was the major compound found in vetiver oil followed by isoaromadendrene epoxide (7.72%), beta-vetivenene (6.92%), solavetivone (5.58%), aromadenderene, azulene and khusimol. Bioassay explained that, the vetiver oil and diluted vetiver oil possessed greater zone of inhibition against S. aureus and E. coli than the coconut oil. FTRI spectra of vetiver oil and microcapsules possessed similar peaks viz., C-H, C=C & C꞊O stretching and additionally oil microcapsules possessed the peak of 3331.24 cm-1 at 91.14 transmittance was attributed to N-H stretches. TGA of oil microcapsules revealed that, there was a minimum weight loss (5.835%) recorded at 467.09°C compared to vetiver oil i.e., -3.026% at the temperature of 396.24°C. The shape of the microcapsules was regular and round, some were spherical in shape and few were rounded by small aggregates. Irrespective of methods of application, organic cotton knits finished with microcapsules by pad dry cure method showed maximum zone of inhibition compared to knits finished by exhaust method against S. aureus and E. coli. The antimicrobial activity of the finished samples was subjected to multiple washing which indicated that knits finished with pad dry cure method showed a zone of inhibition even after 20th wash and better aroma retention compared to knits finished with the exhaust method of application. Further, the group of respondents rated that the 5th washed samples had the greater aroma intensity in both the methods than the other samples. Thus, the vetiver microencapsulated organic cotton knits are free from hazardous chemicals and have multi-functional properties that can be suitable for medical and healthcare textiles.
Abstract: Recently, the utilization of reusable surgical gowns in order to decrease costs, environmental protection and enhance surgeon’s comfort is considered. One of the concerns in applying this kind of medical protective clothing is reduction of their resistance to bacterial penetration especially in wet state, after repeated laundering and sterilizing process. The purpose of this study is to investigate the effect of the laundering and sterilizing process on the reusable surgical gown’s resistance against bacterial wet penetration. To this end, penetration of Staphylococcus aureus bacteria in wet state after 70 washing and sterilizing cycles was evaluated on the two single-layer and three-layer reusable gowns. The outcomes reveal that up to 20 laundering and sterilizing cycles, protective property of samples improves due to fabric shrinkage, after that because of the fabric’s construction opening, the bacterial penetration increase. However, the three-layer gown presents higher protective performance comparing to the single-layer one.
Abstract: The viewpoint towards the use of drugs or vaccines against avian parasitic diseases is one of the most striking challenges in avian medical parasitology. This includes many difficulties associated with drug resistance and in developing prophylactic vaccines. In many instances, the potential success of a vaccination in controlling parasitic diseases in poultry is well-documented. However, some medical, technical and financial limitations are still paramount. On the other hand, chemotherapy is not very well-recommended due to a number of medical limitations. But in the absence of an effective vaccine, drugs are used against parasitic diseases. This paper sheds light on some the advantages and disadvantages of using vaccination and drugs in controlling parasitic diseases in poultry species. The usage of chemotherapeutic drugs is discussed with some examples. Then, more light will be shed on using vaccines as a potentially effective and promising control tool.
Abstract: This paper presents an automatic normal and abnormal heart sound classification model developed based on deep learning algorithm. MITHSDB heart sounds datasets obtained from the 2016 PhysioNet/Computing in Cardiology Challenge database were used in this research with the assumption that the electrocardiograms (ECG) were recorded simultaneously with the heart sounds (phonocardiogram, PCG). The PCG time series are segmented per heart beat, and each sub-segment is converted to form a square intensity matrix, and classified using convolutional neural network (CNN) models. This approach removes the need to provide classification features for the supervised machine learning algorithm. Instead, the features are determined automatically through training, from the time series provided. The result proves that the prediction model is able to provide reasonable and comparable classification accuracy despite simple implementation. This approach can be used for real-time classification of heart sounds in Internet of Medical Things (IoMT), e.g. remote monitoring applications of PCG signal.
Abstract: This study aimed to investigate medical students’ attitudes toward some teachers’ talking features regarding their gender in the Iranian context. To do so, 60 male and 60 female medical students of Urmia University of Medical Sciences (UMSU) participated in the research. A researcher made Likert-type questionnaire which was initially piloted and was used to gather the data. Comparing the four different factors regarding the features of teacher talk, it was revealed that visual and extra-linguistic information factor, Lexical and syntactic familiarity, Speed of speech, and the use of Persian language had the highest to the lowest mean score, respectively. It was also indicated that female students rather than male students were significantly more in favor of speed of speech and lexical and syntactic familiarity.
Abstract: The paper reviews design and implementation of a Calculus Course required for the Biomedical Competency Based Program developed as a joint project between The University of Texas Rio Grande Valley, and the University of Texas’ Institute for Transformational Learning, from the theoretical perspective as presented in scholarly work on active learning, formative assessment, and on-line teaching. Following a four stage curriculum development process (objective, content, delivery, and assessment), and theoretical recommendations that guarantee effectiveness and efficiency of assessment in active learning, we discuss the practical recommendations on how to incorporate a strong formative assessment component to address disciplines’ needs, and students’ major needs. In design and implementation of this project, we used Constructivism and Stage-by-Stage Development of Mental Actions Theory recommendations.
Abstract: The human middle ear (ME) is a delicate and vital organ. It has a complex structure that performs various functions such as receiving sound pressure and producing vibrations of eardrum and propagating it to inner ear. It consists of Tympanic Membrane (TM), three auditory ossicles, various ligament structures and muscles. Incidents such as traumata, infections, ossification of ossicular structures and other pathologies may damage the ME organs. The conditions can be surgically treated by employing prosthesis. However, the suitability of the prosthesis needs to be examined in advance prior to the surgery. Few decades ago, this issue was addressed and analyzed by developing an equivalent representation either in the form of spring mass system, electrical system using R-L-C circuit or developing an approximated CAD model. But, nowadays a three-dimensional ME model can be constructed using micro X-Ray Computed Tomography (μCT) scan data. Moreover, the concern about patient specific integrity pertaining to the disease can be examined well in advance. The current research work emphasizes to develop the ME model from the stacks of μCT images which are used as input file to MIMICS Research 19.0 (Materialise Interactive Medical Image Control System) software. A stack of CT images is converted into geometrical surface model to build accurate morphology of ME. The work is further extended to understand the dynamic behaviour of Harmonic response of the stapes footplate and umbo for different sound pressure levels applied at lateral side of eardrum using finite element approach. The pathological condition Cholesteatoma of ME is investigated to obtain peak to peak displacement of stapes footplate and umbo. Apart from this condition, other pathologies, mainly, changes in the stiffness of stapedial ligament, TM thickness and ossicular chain separation and fixation are also explored. The developed model of ME for pathologies is validated by comparing the results available in the literatures and also with the results of a normal ME to calculate the percentage loss in hearing capability.
Abstract: In an access-control situation, the role of a user determines whether a data request is appropriate. This paper combines vetted web mining and logic modeling to build a lightweight system for determining the role of a health care provider based only on their prior authorized requests. The model identifies provider roles with 100% recall from very little data. This shows the value of vetted web mining in AI systems, and suggests the impact of the ICD classification on medical practice.
Abstract: Additive manufacturing gains the popularity in recent times, due to its capability to create prototype as well functional as end use product directly from CAD data without any specific requirement of tooling. Fused deposition modeling (FDM) is one of the widely used additive manufacturing techniques that are used to create functional end use part of polymer that is comparable with the injection-molded parts. FDM printed part has an application in various fields such as automobile, aerospace, medical, electronic, etc. However, application of FDM part is greatly affected by poor mechanical properties. Proper selection of the process parameter could enhance the mechanical performance of the printed part. In the present study, experimental investigation has been carried out to study the behavior of the mechanical performance of the printed part with respect to process variables. Three process variables viz. raster angle, raster width and layer height have been varied to understand its effect on tensile strength. Further, effect of process variables on fractured surface has been also investigated.
Abstract: The concept of space and function forms the bedrock for spatial configuration in architectural design. Thus, the effectiveness and functionality of an architectural product depends their cordial relationship. This applies to all buildings especially to a hospital ward setting designed to accommodate various complex and diverse functions. Health care facilities design, especially an inpatient setting, is governed by many regulations and technical requirements. It is also affected by many less defined needs, particularly, response to culture and the need to provide for patient families’ presence and participation. The spatial configuration of the hospital ward setting in developing countries has no consideration for the patient’s families despite the significant role they play in promoting recovery. Attempts to integrate facilities for patients’ families have always been challenging, especially in developing countries like Nigeria, where accommodation for inpatients is predominantly in an open ward system. In addition, the situation is compounded by culture, which significantly dictates healthcare practices in Africa. Therefore, achieving such a hospital ward setting that is patient and family-centered requires careful assessment of family care actions and transaction spaces so as to arrive at an evidence based solution. Therefore, the aim of this study is to identify how hospital ward spaces can be reconfigured to provide for sustainable family integration. In achieving this aim, a qualitative approach using the principles of behavioral mapping was employed in male and female medical wards of the Federal Teaching Hospital (FTH) Gombe, Nigeria. The data obtained was analysed using classical and comparative content analysis. Patients’ families have been found to be a critical component of hospital ward design that cannot be undermined. Accordingly, bedsides, open yards, corridors and foyers have been identified as patient families’ transaction spaces that require design attention. Arriving at sustainable family integration can be achieved by revisiting the design requirements of the family transaction spaces based on the findings in order to avoid the rowdiness of the wards and uncoordinated sprawl.
Abstract: In clinical practices, it is common that while facing the unknown progress of their disease, palliative care patients may easily feel anxious and depressed. These types of reactions are a cause of psychosomatic diseases and may also influence treatment results. However, the purpose of palliative care is to provide relief from all kinds of pains. Therefore, how to make patients more comfortable is an issue worth studying. This study adopted the “bio-psycho-social model” proposed by Engel and applied spontaneous breathing training, in the hope of seeing patients’ psychological state changes caused by their physiological state changes, improvements in their anxious conditions, corresponding adjustments of their cognitive functions, and further enhancement of their social functions and the social support system. This study will be a one-year study. Palliative care outpatients will be recruited and assigned to the experimental group or the control group for six outpatient visits (once a month), with 80 patients in each group. The patients of both groups agreed that this study can collect their physiological quantitative data using an HRV device before the first outpatient visit. They also agreed to answer the “Beck Anxiety Inventory (BAI)”, the “Taiwanese version of the WHOQOL-BREF questionnaire” before the first outpatient visit, to fill a self-report questionnaire after each outpatient visit, and to answer the “Beck Anxiety Inventory (BAI)”, the “Taiwanese version of the WHOQOL-BREF questionnaire” after the last outpatient visit. The patients of the experimental group agreed to receive the breathing training under HRV monitoring during the first outpatient visit of this study. Before each of the following three outpatient visits, they were required to fill a self-report questionnaire regarding their breathing practices after going home. After the outpatient visits, they were taught how to practice breathing through an HRV device and asked to practice it after going home. Later, based on the results from the HRV data analyses and the pre-tests and post-tests of the “Beck Anxiety Inventory (BAI)”, the “Taiwanese version of the WHOQOL-BREF questionnaire”, the influence of the breathing training in the bio, psycho, and social aspects were evaluated. The data collected through the self-report questionnaires of the patients of both groups were used to explore the possible interfering factors among the bio, psycho, and social changes. It is expected that this study will support the “bio-psycho-social model” proposed by Engel, meaning that bio, psycho, and social supports are closely related, and that breathing training helps to transform palliative care patients’ psychological feelings of anxiety and depression, to facilitate their positive interactions with others, and to improve the quality medical care for them.
Abstract: Medical images are important to help identifying different diseases, for example, Magnetic resonance imaging (MRI) can be used to investigate the brain, spinal cord, bones, joints, breasts, blood vessels, and heart. Image segmentation, in medical image analysis, is usually the first step to find out some characteristics with similar color, intensity or texture so that the diagnosis could be further carried out based on these features. This paper introduces an improved C-means model to segment the MRI images. The model is based on information entropy to evaluate the segmentation results by achieving global optimization. Several contributions are significant. Firstly, Genetic Algorithm (GA) is used for achieving global optimization in this model where fuzzy C-means clustering algorithm (FCMA) is not capable of doing that. Secondly, the information entropy after segmentation is used for measuring the effectiveness of MRI image processing. Experimental results show the outperformance of the proposed model by comparing with traditional approaches.
Abstract: Traffic accidents are a result of the convergence of hazards, malfunctioning of vehicles and human negligence that have adverse economic and health impacts and effects. Unfortunately, avoiding them completely is very difficult, but with quick response to rescue and first aid, the mortality rate of inflicted persons can be reduced significantly. Smart and innovative technologies can play a pivotal role to respond faster to traffic crash emergencies comparing conventional means of transportation. For instance, Rescue Emergency Drone (RED) can provide faster and real-time crash site risk assessment to emergency medical services, thereby helping them to quickly and accurately assess a situation, dispatch the right equipment and assist bystanders to treat inflicted person properly. To conduct a research in this regard, the case of a traffic roundabout that is prone to frequent traffic accidents on the outskirts of Esbjerg, a town located on western coast of Denmark is hypothetically considered. Along with manual calculations, Emergency Disaster Management Simulation (EDMSIM) has been used to verify the response time of RED from a fire station of the town to the presumed crash site. The results of the study demonstrate the robustness of RED into emergency services to help save lives.
Abstract: The high prevalence of cardiovascular diseases has provoked a raising interest in the development of mathematical models in order to evaluate the cardiovascular function both under physiological and pathological conditions. In this paper, a physical model of the cardiovascular system with intrinsic regulation is presented and implemented by using the object-oriented Modelica simulation software tools. For this task, a multi-compartmental system previously validated with physiological data has been built, based on the interconnection of cardiovascular elements such as resistances, capacitances and pumping among others, by following an electrohydraulic analogy. The results obtained under both physiological and pathological scenarios provide an easy interpretative key to analyze the hemodynamic behavior of the patient. The described approach represents a valuable tool in the teaching of physiology for graduate medical and nursing students among others.
Abstract: One of the key problems facing in the analysis of Computed Tomography (CT) images is the poor contrast of the images. Image enhancement can be used to improve the visual clarity and quality of the images or to provide a better transformation representation for further processing. Contrast enhancement of images is one of the acceptable methods used for image enhancement in various applications in the medical field. This will be helpful to visualize and extract details of brain infarctions, tumors, and cancers from the CT image. This paper presents a comparison study of five contrast enhancement techniques suitable for the contrast enhancement of CT images. The types of techniques include Power Law Transformation, Logarithmic Transformation, Histogram Equalization, Contrast Stretching, and Laplacian Transformation. All these techniques are compared with each other to find out which enhancement provides better contrast of CT image. For the comparison of the techniques, the parameters Peak Signal to Noise Ratio (PSNR) and Mean Square Error (MSE) are used. Logarithmic Transformation provided the clearer and best quality image compared to all other techniques studied and has got the highest value of PSNR. Comparison concludes with better approach for its future research especially for mapping abnormalities from CT images resulting from Brain Injuries.