Electronics and biomedical engineering

Plasmodium falciparum is the cause of tropical malaria or malaria falciparum. The most dangerous
species compared to four other species because it can lead to complications of cerebral malaria. These
parasites invade every erythrocytes regardless of age, so the number of erythrocyte infection (degree of
parasitaemia) is very high and often lead to severe complications include shock, cerebral malaria, acute
renal failure, intravascular hemolysis, and pulmonary edema. Authors interested in conducting research
on image segmentation malaria parasite Plasmodium falciparum with active contour method which
implements a special process that Selective Binary and Gaussian Filtering Regularized Level Set
(SBGFRLS). In SBGFRLS process, first performed the conversion of the level set into binary form, then
used a gaussian filter to regularizing. Selective Binary active contour method and Gaussian Filtering
Regularized Level Set (SBGFRLS) for object segmentation blood cells infected with Plasmodium
falciparum parasites in detecting the edges of objects segmentation can do well on an object blood cells
that have an interior intensity is not homogeneous.
Keywords: plasmodium falciparum, active contour, selective binary and gaussian filtering regularized
level set (SBGFRLS), gaussian filter.

Cycling exercise-based on functional electrical stimulation (FES) for disabled individuals-is achieved by stimulating single muscle group, the quadriceps, with the help of a new assist mechanism represented by a solid disc flywheel equipped with an electrical clutch. Fuzzy logic based closed-loop control method is implemented to obtain a stable cycling cadence by i) controlling the stimulation intensity on the muscle and ii) managing the engagement of the flywheel mechanism. To achieve better results, several crank positionswith different gear ratios between the crank and the flywheel-are tested and analyzed. To obtain the optimal design parameters, a multi-objective genetic algorithm (MOGA) approach is adopted towards maximizing the cycling efficiency and minimizing the cadence error. A comparison with the results reported in the literature reveals the superiority of the proposed design to limit the cadence error to ±5 rpm for 35 rpm desired speed. Moreover, the results demonstrate that the designed control approach with the proposed assist mechanism is robust to changes in muscle force due to muscle fatigue. Additionally, the introduced control approach with the new assist mechanism is promoting bounded tracking of the desired speed and prolonging FES-cycling training by stimulating the quadriceps muscle group only.

Due to the continuous monitoring process of critical patients, Intensive Care Units (ICU) generate large amounts of data, which are difficult for healthcare personnel to analyze manually, especially in overloaded situations such as those present during the COVID-19 pandemic. Therefore, the automatic analysis of these data has many practical applications in patient monitoring, including the optimization of alarm systems for alerting healthcare personnel. In this paper, explainable machine learning techniques are used for this purpose, with a methodology based on age-stratification, boosting classifiers, and Shapley Additive Explanations (SHAP) proposed. The methodology is evaluated using MIMIC-III, an ICU patient research database. The results show that the proposed model can predict mortality within the ICU with AUROC values of 0.961, 0.936, 0.898, and 0.883 for age groups 18–45, 45–65, 65–85 and 85+, respectively. By using SHAP, the features with the highest impact in predicting mortality for different age groups and the threshold from which the value of a clinical feature has a negative impact on the patient’s health can be identified. This allows ICU alarms to be improved by identifying the most important variables to be sensed and the threshold values at which the health personnel must be warned.

This paper discusses the current and future prospects of 3-D printing technology in the field of medical science encompassing biomedical engineering for improved human health care. It presents before the reader, an overview on the evolution of the 3D printing technology and its increased usage in the field of biomedical engineering and pharmaceutics. It is expected that it is going to change the future of manufacturing industries and technology.

— This paper is a design of non-invasive instrument for measuring the glucose level in the body using saliva acetone. In this method, the electric current which is equivalent to the acetone level present in the body is converted into voltage using the sensor. This voltage has a negative correlation with the blood glucose level. Thus, it is converted into glucose level by programming done using ATMEGA328 processor which is displayed in LCD. This is a painless procedure with low energy consumption. It is a handheld device and it is cost effective.

Aim
The aim of this study was to project the quantity of waste to be generated by 1500 patients after renovation of Mulago National Referral Hospital(MNRH).
Methods
I utilised mostly both quantitative and qualitative methods such as observation, interviews with waste handlers and checking of waste inventories.
Results
The study established that MNRH will generate 375 Kg of medical waste per day if its plan of attending to only 1500 admitted patient is implemented after renovation and will be distributed as 42.1% of the waste being infectious (RED). 28.4% being infectious (YELLOW), and 18.1% being non-infectious (BLACK) and the sharps ( BLUE ) being 11.4%.

Conclusion
This study established the current values of waste generated in MNRH and projected the values of the expected quantity of waste to be accumulated when MNRH is made to attend to only 1500 admitted patients.

X-ray is being used widely in medical and in other fields of science, engineering, and technology since its invention in the year 1895. Globally, the growing number of general population and the high prevalence of various critical diseases are augmenting the need for X-ray imaging equipment for an accurate diagnosis. Although X-ray tube technology (Coolidge tube) is about 106 years old, it has been still used widely today for medical diagnostic imaging. Various types of X-ray tubes are classified. The indicative list for the standards pertaining to performance and safety of medical electrical equipment and diagnostic X-ray tube assembly includes the following: IEC 60601-1-2/IS 13450-1-2, IEC 60601-
1-3/IS 13450-1-3, IEC 60601-1-6, IEC 60601-1-8, IEC 60601-1-9, IEC 60601-2-28, IEC 60601-2-54, IEC 60522, IEC 60806, IEC 60336, IEC 61267, IEC 61674, IEC 61676, IEC 60613, IEC 60526, IEC 62304, IEC 62366, ISO 13485, ISO 14000, ISO 14971, and ISO 10993-1. The manufacturing processes of the X-ray tube assembly are listed as follows: (step 1) X-ray tube insert parts processing and cleaning; (step 2) X-ray tube insert parts (anode and cathode) assembly processing; (step 3) glass or metal-ceramic envelope processing; (step 4) degassing of X-ray tube insert; (step 5) seasoning of X-ray tube insert; (step 6) X-ray tube assembly processing; (step 7) final testing of X-ray tube assembly; and (step 8) quality control of X-ray tube assembly. As per the recommendations of Atomic Energy Regulatory Board (AERB), Government of India, the accuracy of the applied X-ray tube potential of the general radiography and fluoroscopy, computed tomography, mammography, and dental X-ray machine should be within +/-5, +/-2, +/-1, and +/-5, respectively, of the corresponding measured values.
Linearity of the X-ray tube current (mA or mAs) loading stations (coefficient of linearity (CoL)) of the general radiography and fluoroscopy, computed tomography, mammography, and dental X-ray machine should be within <0.1, +/-0.1, +/-0.1, and <0.1, respectively. The most common causes for the X-ray tube failures include the following: (i) cathode filament burnout, (ii) target micro-cracking, (iii) tube arcing, (iv) slow leaks in the tube, and (v) bearings of rotating anode. Globally, more than 20,000 patents have been filed so far on the innovations of X-ray tube technology

The work shows an assessment of progress in the implementation of the technologies for
neuroscience and its inclusion in the analysis of the behavior of consumers. In this way, the development of
research project on the application of neuromarketing to product engineering is expected to understand the
contributions to the improvement of processes and quality control, based on a new conceptualization of the
universe related to the anthropic principle. Although the ethical controversies of these technological
applications, call the attention because of its implications about the context of the manipulation of
consciousness in the consumption. Nevertheless, as for the methodology, an analysis of technological
availability was realized. Its tendencies to the methods and not invasive skills; later, a comparative
evaluation informed to check its complexity as an indirect measurement of the cost and decrease of times for
the assessment of products. Consequently, a model presents himself for the treatment of information where
there was aware the need to process data for its later analysis, finally there are placed in perspective the
models of reviews available for the info. As for such information, its monitoring is vital to determine the grade
of a link of the product to evaluate with the emotions of the consumer, which in the context of the marketing
think about how to raise the preference and consumption; additionally, general process mathematical models
appear stochastic implied. In the process of the investigation, technology is developing to combine semantic
analyses of the emotions based on engineering Kansei and the monitoring of biomedical variables
prosecution, it taking the market researchers to an opportunity to innovate in the evaluation of new products
or its re-engineering with its processes.

Analysis of electromyogram (EMG) signal processing and its application to identify human muscle strength of rehabilitation purpose has been successfully carried out in this paper. Single channel EMG signal was obtained from human muscle using non-invasive electrodes and further process by signal acquisition circuit to get a suitable signal to be process. In the first part of signal acquisition, the amplification circuit for the small EMG signal has been design successfully. After amplification stage EMG signal was digitized through analogue and digital converter (ADC) then further process in microcontroller (ATmega328) for getting accurate EMG signal. Finally, the processed EMG signal was classified into 6 different levels in order to display the muscle strength level of the user. This EMG device can be used to help the weak person or an elderly to identity their strength level of muscle for clinical rehabilitation purpose.

Independent Component Analysis (ICA) is a signal-processing method to extract independent sources given only observed data that are mixtures of the unknown sources. Recently, Blind Source Separation (BSS) by ICA has received considerable attention because of its potential signal-processing applications such as speech enhancement systems, image processing, telecommunications, medical signal processing and several data mining issues. This book brings the state-of-the-art of some of the most important current research of ICA related to Audio and Biomedical signal processing applications. The book is partly a textbook and partly a monograph. It is a textbook because it gives a detailed introduction to ICA applications. It is simultaneously a monograph because it presents several new results, concepts and further developments, which are brought together and published in the book.

The incorporation of a neuroprosthetic device into one’s being at the physical, cognitive, and social levels constitutes a form of ‘cyborgization’ that imposes new constraints on one’s existence while simultaneously opening a path to new forms of experience. This text explores the boundaries of this qualitatively novel form of being by formulating an ontology of the neuroprosthesis as an instrument that shapes the way in which its human host experiences and acts within emerging posthumanized digital-physical ecosystems.

The ontology addresses four main roles that a neuroprosthetic device may play in this context. First, a neuroprosthesis may serve as a means of human augmentation by altering the cognitive and physical capacities possessed by its host. Second, it may manipulate the contents of information produced or utilized by its human host. Third, a neuroprosthesis may shape the manner in which its host inhabits a digital-physical body and external environment. And finally, a neuroprosthesis may regulate the autonomous agency possessed and experienced by its host.

The development and use of such an ontology can allow researchers to better understand the psychological, social, and ethical ramifications of such technologies and can enable the architects of neuroprosthetic systems and the digital-physical ecosystems within which their human hosts operate to formulate principles of design and management that minimize the dangers and maximize benefits for the neuroprosthetically augmented inhabitants of such environments.

Retinopathy is a disease showing no physical signs of
occurrence with the major repercussion of loss of vision. The
number of retinopathy cases is increasing with each year, which
requires the evaluation of innumerable database. This has led to
the evolution of various automated evaluation methods to follow
up the retinal diseases. In this paper, a simpler automated
approach is presented to detect diabetic retinopathy taking
exudates into account. The earlier methods used direct
segmentation, which generated mediocre results due to the fact
that the texture of unhealthy areas is dissimilar. Therefore a
different method is developed which uses homogeneity of
healthya reas r ather th an u nhealthy areas. In this method we first
extract the healthy areas such as blood vessels by entropy
thresholding method and optic disc using sobel filter method.
Then the thresholding method is employed to segment the
exudates in diabetic retinopathy images. Various qualities of
retinal images are used and the results clearly show that the
presented method performs better than the previous proposed
methods for segmentation of exudates.

A neonatal intensive care unit (NICU),
also known as intensive care nursery (ICN), an
intensive care unit specializing in the care of ill
or premature new born infants. Power
consumption is one of the major issue facing in
the use of baby care units. Normally baby care
units are powered by electricity. In the case of
remote areas electricity is a main problem for
using baby care units. For solving this problem
we use solar energy to power the entire unit. In
this project, the main aim to design an integrated
incubator and phototherapy unit for effective
neonatal application in LABVIEW. We power
this entire baby care unit using solar energy.
This will help to use these types of incubator in
remote areas with 32 hrs battery backup. A
filament heated by solar panels maintains a
mean room temperature to maintain normal
temperature. A heating device is used to regulate
and maintain the desired temperature ranging
from 34°C to 36.1°C. The inbuilt phototherapy
unit is used for jaundice treatment. To achieve
this purpose, we use two blue light sources
(fluorescent lamps) of wavelength 425 to
500nm.In addition to that, sensor units and alarm
units are included. Sensor unit includes a wet
sensor to sense the wetness and discomfort in
babies and a sound sensor to sense the babies
cry. Alarm units are also incorporated with this
sensors and it produce alarms in case of
abnormalities in pulse rate, SPO2, NiBp, Body
Temp., Glucose Level, in babies. This data’s is
sent to the patient relatives or doctors mobile
though SMS using GSM

Biomedical Waste, (BMW), are those potential hazardous waste materials, consisting of solids, liquids, sharps, and laboratory waste which pose a grave danger to the health of humans as well as other living organisms. And in some cases, it may be lethal too. It is of extreme importance that this waste must be properly managed and disposed off safely so as to prevent outbreak of infections to general public and disturb the health care settings in a society. About 57% of the total waste generated in Maharashtra is biomedical waste. It is essential to understand what biomedical waste is, classify them and to manage them accordingly. In this paper, a concise effort is undertaken so as depict biomedical waste substances generated, their origins and the methods to deal with them effectively.

Keywords— Hazardous, infection, biomedical, management, health

This text presents an introduction to neuroprosthetic devices and systems that explores both the state of the art of sensory, motor, and cognitive neuroprostheses that are currently in use as well as more sophisticated kinds of neuroprosthetic technologies that are being actively pursued or that are expected to be developed in the future. This overview takes us from the contemporary world of neuroprostheses that have been designed primarily for purposes of therapeutic treatment of medical disorders and the restoration of natural human abilities lost due to illness or injury to an emerging future world in which neuroprosthetic devices offer the possibility of augmenting and transforming the capacities of their users in such a way that they can perhaps best be described as ‘posthumanizing’ technologies.

There is enormous evidence that the initiation and growth of atherosclerosis is highly influenced by hemodynamic factors. In this study, hemodynamic factors in the following patient specific 3D carotid artery models were studied: i) normal, ii) stenosis (with plaque near to bifurcation of internal carotid artery (ICA)), and iii) surgical model (plaque with surgically fitted Palmaz–Schatz stent). The 3D model of the carotid artery was formed from CT image of a patient through a commercial software MIMICS. The geometrical measurement taken from the 3D model was used to form its CAD model using CATIA software. The CAD model was meshed in ANSYS ICEM CFD module. The inlet- and outlet- boundary conditions were defined and material properties were given in CFX-Pre module of ANSYS. Then the solver input file was given to CFX solver manager for performing computational fluid dynamics (CFD) on the model. The outputs of the CFD analysis were observed in CFD-Post. The wall shear stress and blood velocity were greater both at near the bifurcation and at bend of the carotid artery model. The abnormal model is characterized by high wall shear stress in the stenosed portion which indicates greater probability of growth of plaque. Disturbed flow patterns and oscillating velocity indicate that the vulnerability of plaque formation is high in such places. The hemodynamic values have come back near to normal values in the carotid model fitted with stent. The observed variations in hemodynamic factors in the carotid artery with plaque surgically fitted with stent were compared to its normal model. This information can be used to predict restenosis in future.

Majority of  engineering  colleges, universities and
the technical institutions are undertaking all initiatives to stay competitive. Efforts are exerted to continuously improve the curriculum in order to provide quality and relevant education for the students in response to global call for outcomes-based education. This paper presents the procedures, techniques, methods,  and advantages of using Altium Designer software in teaching electronic circuits. Altium Designer is a schematic capture, simulation, and PCB design software, dedicated to analyzing electronic circuits which is based on interconnected icons of electronic components. The approach makes it easier for the students to visualize the system they are attempting to design, model, and study. Likewise, it makes debugging and error correction simpler. Moreover, an example has been provided  also  to show how to use  the software for teaching and research in electronic circuits.

A growing number of posthuman neuroprosthetic devices are under development that will provide their users with sensory, motor, and cognitive capacities that radically differ from those of ‘natural’ human beings. Specialized organizations such as military agencies and departments are fashioning plans to proactively deploy such neurotechnologies among their personnel. While the use of such devices has been studied from biomedical and ethical perspectives, substantive analysis has not yet been carried out from the perspective of organizational management. In this text we investigate the implications of integrating such advanced neurotechnologies into the structures, processes, and systems of an organization through the lens of enterprise architecture (EA), a management discipline that is designed to facilitate the incorporation of innovative IT into an organization and which is a favored management approach of the kinds of large, complex, and technology-intensive organizations expected to be ‘early adopters’ of posthuman neuroprosthetics.

We identify and analyze two primary ways in which the practice of enterprise architecture will change within organizations that deploy posthuman neuroprosthetics. First, it is argued that EA will be forced to adapt as the introduction of posthuman neuroprosthetics results in: 1) blurring distinctions between human personnel and electronic information systems; 2) changes in the nature of HCI and interpersonal communication; 3) an extension of the functional scope of an organization’s IT systems into the bodies and minds of its workers; 4) legal and ethical constraints limiting an organization’s ability to impose an EA on implanted neuroprostheses; and 5) changes to the fundamental capacities of a workforce. Second, the deployment of posthuman neuroprosthetics will impact an organization’s ability to address four challenges facing contemporary EA: 1) fragmentation of the field; 2) underutilization of EA products; 3) the requirement for ‘soft’ skills in implementing EAs; and 4) the ongoing need to collect large quantities of real-time organizational data.

We further argue that EA is well-positioned to facilitate the technological aspects of integrating posthuman neuroprosthetics into an organization but ill-suited to address the non-technological aspects of that process. Finally, we suggest that EA should draw on fields such as biomedical engineering, management cybernetics, and organization development in order to more effectively design and maintain architectures that incorporate posthuman neuroprosthetics.

Recent days Computer-aided design and image processing techniques are one of the most emerging useful tools for analysis of models in various medical, industrial and research areas. In medical field for the diagnosis of various diseases in vivo techniques including biochemical test, enzymatic tests are needed for continuous monitoring of patients. These diagnosis procedures are time consuming and inconvenient for patients. Therefore Computer assisted designing and image processing techniques are most promising non invasive tools for faster diagnosis and useful tool for designing of biomedical implants. In this paper portal vein was segmented from patient’s Liver computed tomography (CT) image by dedicated software. A Liver’s CT image of 38 year old Indian male patient’s was collected and by using imaged based software MIMICS (Materialise’s Interactive Medical Image Control System, Belgium) 3D model of HPV (hepatic portal vein) was obtained and Solid Work Professional (Dassault Systems Solid Works Corporation, USA) software was used for designing of normal portal vein’s 3D model and various portal vein diseased models including minor right portal vein thrombosis ( 19-20% reduction in medial region of vein), severe right portal vein thrombosis (20-22% reduction in medial and distal region of vein), minor left portal vein thrombosis (19-20% reduction in medial region of vein, severe right portal vein
thrombosis(20-22% reduction in medial and distal region of vein), left aneurysm (150-200 % increase of medial region).These models can be used for designing for implants and analysis of portal vein’s disorder like portal thrombosis, and portal aneurysm which are main cause of portal hypertension and also useful for surgeon for planning surgery and also helpful for understanding of portal vein hemodynamic (pressure, velocity, wall shear force)

The structure and behavior of a neuroprosthetic device can be analyzed from different perspectives. In this text, we formulate an ontology that can be employed to describe the fundamental characteristics of a neuroprosthesis in its role as a computing device. The ontology draws on existing neuroprosthetic device typologies and ontologies developed for other kinds of devices such as mobile devices and robotic systems. It describes four key aspects that shape the functioning of a neuroprosthesis as computing device: 1) the device’s external context (including the human agents who participate in its development and use, factors impacting the device’s availability, and the device’s relationship to the body of its human host); 2) physical components of the neuroprosthesis (including the device’s basic morphology, input and output mechanisms, and computational substrate); 3) processes utilized by the device (including computational processes and input and output modalities); and 4) the types of information generated or handled by the device (which may include data regarding the device’s status and environment, data regarding the cognitive and biological processes of the device’s human host, and procedural and declarative knowledge). The use of such an ontology allows the functionality of a neuroprosthesis as a computing device to be more easily analyzed or designed and facilitates interoperability between neuroprostheses, their human hosts and users, and external computer systems.

In this text, we develop an ontology that envisions, captures, and describes the full range of ways in which a neuroprosthesis may participate in the sensory, cognitive, and motor processes of its human host. By considering anticipated future developments in neuroprosthetics and adopting a generic biocybernetic approach, the ontology is able to account for therapeutic neuroprostheses already in use as well as future types of neuroprostheses expected to be deployed for purposes of human enhancement.

The ontology encompasses three areas. First, a neuroprosthesis may participate in its host’s processes of sensation by (a) detecting stimuli such as photons, sound waves, or chemicals; (b) fabricating sense data, as in the case of virtual reality systems; (c) storing sense data; (d) transmitting sense data within a neural pathway; (e) enabling its host to experience sense data through a sensory modality such as vision, hearing, taste, smell, touch, balance, heat, or pain; or  (f) creating mappings of sensory routes – e.g., in order to allow sensory substitution. Second, a neuroprosthesis may participate in processes of cognition by (a) creating a basic interface between the device and the host’s conscious awareness or affecting the host’s (b) perception, (c) creativity, (d) memory and identity, or (e) reasoning and decision-making. Third, a neuroprosthesis may participate in processes of motion by (a) detecting motor instructions generated by the host’s brain; (b) fabricating motor instructions, as in the case of a medical device controlled by software algorithms rather than its host’s volitions; (c) storing motor instructions; (d) transmitting motor instructions, as within a neural pathway; (e) effectuating physical action within effectors such as natural biological muscles and glands, synthetic muscles, robotic actuators, video screens, audio speakers, or wireless transmitters; (f) allowing the expression of volitions through motor modalities such as language, paralanguage, and locomotion; or (g) creating mappings of motor routes. The use of such an ontology allows easier, more systematic, and more robust analysis of the biocybernetic role of a neuroprosthesis within its host-device system.

Sickle  cell  disease  (SCD)  is  a  major  gene  disorder  among  the
tribal population of central India. Fetal Haemoglobin (HbF) is the
best-known genetic modulator of sickle cell anaemia, which varies
dramatically  in  concentration  in  the  blood  of  these patients.  The
patients with SCA display a remarkable variability  in the disease
severity. Hence the objective of the present study was to determine
the Fetal Haemoglobin (HbF) level in SCD patients (SS), carriers
(AS) and normal individuals (AA). Studied population shows the
highest HbF level in SS followed by AS individuals and a slightly
higher  HbF  level  in  SS  females  than  in  their  male  counterparts.
Among different age groups the highest HbF% was found in the
age group of 11-20 years. And the mean HbF level appears to be
declining as age advances.

Due to the continuous monitoring process of critical patients, Intensive Care Units (ICU) generate large amounts of data, which are difficult for healthcare personnel to analyze manually, especially in overloaded situations such as those present during the COVID-19 pandemic. Therefore, the automatic analysis of these data has many practical applications in patient monitoring, including the optimization of alarm systems for alerting healthcare personnel. In this paper, explainable machine learning techniques are used for this purpose, with a methodology based on age-stratification, boosting classifiers, and Shapley Additive Explanations (SHAP) proposed. The methodology is evaluated using MIMIC-III, an ICU patient research database. The results show that the proposed model can predict mortality within the ICU with AUROC values of 0.961, 0.936, 0.898, and 0.883 for age groups 18–45, 45–65, 65–85 and 85+, respectively. By using SHAP, the features with the highest impact in predicting mo...

COVID-19 leads to severe respiratory symptoms that are associated with highly intensive care unit (ICU) admissions and deaths. Early diagnosis of coronavirus limits its wide spreading. Real-time reverse transcription-polymerase chain reaction (RT-PCR) is the strategy that has been used by clinicians to discover the presence or absence of this type of virus. This technique has a relatively low positive rate in the early stage of this disease. Therefore, clinicians call for another way to help in the diagnosis of COVID-19. The appearance of X-ray chest images in case of COVID-19 is different from any other type of pneumonic disease. Therefore, this research is devoted to employ artificial intelligence techniques in the early detection of COVID-19 from chest X-ray images. Different hybrid models-each consists of deep features' extraction and classification technique-are implemented to assist clinicians in the detection of COVID-19. Convolutional neural network (CNN) is used to extract the graphical features in the hybrid models' implementations from the chest X-ray images. The classification, to COVID-19 or Non-COVID-19, is achieved using different machine learning algorithms such as CNN, support vector machine (SVM), and random forest (RF) to obtain the best recognition performance. The most significant two extracted features are employed for training and parameters testing. According to the performance results of the designed models, CNN outperforms other classifiers with a testing accuracy of 95.2%.

Meningoencephalocele is a hernial protrusion of part of meninges
and neural elements in a sac. A term male baby having a mass
protruding from the occipital area was born by caesarian section
with 3 kg weight. A cranial defect in the occipital area was seen.
The mass was diagnosed as Meningoencephalocele. This type of
condition occurs with high mortality and morbidity.

We address numerical versus experimental design and testing of miniature implantable antennas for biomedical telemetry in the medical implant communications service band (402–405 MHz). A model of a novel miniature antenna is initially proposed for skin implantation, which includes varying parameters to deal with fabrication-specific details. An iterative design-and-testing methodology is further suggested to determine the parameter values that minimize deviations between numerical and experimental results. To assist in vitro testing, a low-cost technique is proposed for reliably measuring the electric properties of liquids without requiring commercial equipment. Validation is performed within a specific prototype fabrication/testing approach for miniature antennas. To speed up design while providing an antenna for generic skin implantation, investigations are performed inside a canonical skin-tissue model. Resonance, radiation, and safety performance of the proposed antenna is finally evaluated inside an anatomical head model. This study provides valuable insight into the design of implantable antennas, assessing the significance of fabrication-specific details in numerical simulations and uncertainties in experimental testing for miniature structures. The proposed methodology can be applied to optimize antennas for several fabrication/testing approaches and biotelemetry applications.

This paper presents an electrocardiogram acquisition system course design project for an upper year bioinstrumentation course. The objective of this design project is to provide students an opportunity for an integrative learning, enhancing their educational experience. Unlike similar electrocardiogram instrumentation projects, this project is based on a commercially available instrumentation amplifier enabling better systems-level thinking. The project is described along with observations made from our pilot implementation of the project. The initial offering of the project is considered a success with positive feedback from students. Recommendations for improvements are also discussed.

Phyllanthus emblica  posses a vast ethnomedicinal history and
represents a large group of phytochemical reservoir of medicinal
uses. It is one of the ingredients used from time immemorial in
various ancient literatures like in “Ayurveda” and “Charka
Samhitha” as a potential ingredient for various ailments. The fruit
is studied for various phyto chemical constituents  like rich in
quercetin, gallic acid, tannins, flavonoids, pectin and Vitamin C
and also contains various polyphenolic compounds. A wide range
of phytochemical components from this plant have shown proven
results for biological activities like terpenoids,  alkaloids,
flavonoids and tannins. Many pharmacological studies also have
exhibited proven results for antioxidant, anticarcinogenic,
antitumour, antigenotoxic, antiinflamatory activities supporting its
traditional uses. In view of these studies the present work has been
focused on the GC–MS analysis of ethyl acetate extract of the bark
portion of the  P. emblica  which could be a possible source of
extracting the therapeutically useful products.

Cato T. Laurencin (born 1959), a professor and a surgeon, served as the Dean of the University of Connecticut School of Medicine and the Vice President for Health Affairs at the University of Connecticut from 2008 - 2011.  He is currently the Chief Executive Officer of the Connecticut Institute for Clinical and Translational Science, the Director of the Institute for Regenerative Engineering, and the Director of the Raymond and Beverly Sackler Center for Biomedical, Biological, Physical, and Engineering Sciences at the University of Connecticut.

He is one of only 3 practicing orthopaedic surgeons in the Institute of Medicine of the National Academies. Laurencin was the first Orthopaedic Surgeon to achieve University Professor level rank in the country. He is the first surgeon in the US to be elected to the Third World Academy of Sciences (of the six US members elected in the last two years, one third are Nobel prize winners). Dr. Laurencin is a member of both the Institutes of Medicine and the National Academies of Engineering.

The articulating surface of standard femoral knee component is as generic shape while every individual patient has a unique shape of knee joint and this is causes some problems. The Conventional femoral knee component gives a satisfactory result in many cases that carry the patient back to active lifestyle and near normal patient and especially for younger patients. Most patients' gaits are altered after a total knee replacement (TKR) due to the change in surface geometry of femoral implant. The main objective of this work is to design custom design implant as smooth-implant interface of femoral component to increase appropriate bone ingrowths and to prevent bone remodeling found in conventional knee implants, also this design maintain the articulating surface of femoral with tibial component and patellar component as natural knee to maintain the patients gait without altered. This custom design of femoral knee implant will provide better results for patients who have more active lifestyle and strenuous activities such as younger patients. The custom design was done by creating 3D models from computerized tomography (CT) scan data through computer segmentation using Materialise MIMICS software. Geomagic studio software was used in this work for smoothing, preparation of the model and convert STL file format to STEP format. The 3D model as STEP format then exported from Geomagic Studio to CAD design software such as solidworks (Solidworks, USA) for design on the femoral components of the implant. From 3D model of the femur, a custom knee implant femoral component was designed. Finite Element Analysis was used to examine and evaluate the stress distribution over the interface between the implant and femur bone. The custom design as smooth surface describe a more even stress distribution in the contact region between femur bone and implant. This stress will reduce the uneven bone remodeling; also reduce the risk of premature loosening of implant.