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American Journal of Biomedical Engineering
Number of Followers: 10

This is an Open Access Journal

Open Access journal
ISSN (Print) 2163-1050 - ISSN (Online) 2163-1077
Published by SAP

[105 journals]

Impact of Sensor Technology Enhancing Corona Disease
- Abstract: Publication year: 2020Source: American Journal of Biomedical Engineering, Volume 10, Number 1Md. Rahimullah Miah, AAM Shazzadur Rahman, Md. Shahariar Khan, Alamgir Adil Samdany, Mohammad Abdul Hannan, Shahriar Hussain Chowdhury, Alexander Kiew SayokAn explorative field observation to determine the impact of sensor networks in different parts of the human body surrounded by body boundary areas. This study was conducted in general, overweight and thin individuals with the positions of global positioning systems and processed frequencies from sensor technology. Everyone uses mobile phones for advanced communication, but none can aware of its security systems due to cutting-edge-technology. The fieldwork details the principles, recognizing the impact of radio frequency with individual’s suffering from corona disease around the world. Quantitative and qualitative related sensor data were obtained from ISNAH experiment while secondary data were collected from diverse sources. The research highlights the impact of sensor networks with variable and processed radio frequencies among individual’s body mass indices facilitating the light and dark environment. The study represents the obese patients suffer from corona disease dies within 7 minutes in dark environment, but 12 minutes in the light condition. These results reflect the importance of human health security that the State provides. A proposed corona control model was developed on the priority of research findings. Lastly, the study recommends future research trajectories of a new collaborative alternative approach to drive the methodological agenda and to make the sound health systems on ways to further incorporate the demanding secured sensor networks for health management.
Analysis and Different Modifications of Empirical Mode Decomposition
Method of Heart Rate Extraction from PPG Signal
- Abstract: Publication year: 2020Source: American Journal of Biomedical Engineering, Volume 10, Number 1A. H. M. Zadidul Karim, Tabassum Hasnat Reshmi, Sabrina Sultana, Md. Rakibul Islam, Shikder Shafiul Bashar, Md. Abdullah Al MahmudIn this paper, a method is shown to estimate the heart rate (HR) from fingertip type devices. Fingertip devices are commonly cheap and easily wearable. As the skin of fingertip is thin, it is easy to extract heart rate from there. A promising feature in today’s world of HR monitoring is Photoplethysmography (PPG). However, during physical exercise HR estimation accuracy is seriously affected by noise and motion artifacts (MA). To estimate HR changes an algorithm is used named ensemble empirical mode decomposition (EEMD) along with spectrum subtraction (SS). EEMD algorithm decomposes a PPG signal and an acceleration signal into several intrinsic mode functions (IMFs) respectively. Due to a common sparsity constraint on spectral coefficients, this method can easily identify the noise related IMFs. After that correlation coefficient (CC) is determined by the spectrum of the acceleration signal and that PPG signal in the band of [0.4 Hz-5Hz]. If CC>0.5, SS is applied to remove the spectrum of the acceleration signal from the spectrum of the PPG signal. Finally, HR related peak is estimated. Here in this paper, some modification techniques are applied to have better-estimated HR peak. There were 12 subjects from where experimental datasets are recorded. The average absolute error, average absolute error percentage, and root mean square (RMS) error of HR was estimated. In this work, the average percentage error is lower when the CC is equal to 0.7.
Investigation of Genome-Wide Association SNPs and Alzheimer's Disease
- Abstract: Publication year: 2020Source: American Journal of Biomedical Engineering, Volume 10, Number 1Mark Nnh Mikhail, Ahmed Y. Sayed, Mai S. Mabrouk, Ayman M. EldeibThe aim of this work is to measure the influence of genome-wide association study single nucleotide polymorphisms (SNPs) in Alzheimer’s disease (AD). Data mining methods were tested. Data used were obtained from ADNI database. Subjects were 214 normal controls (NCs), 364 subjects with mild cognitive impairment (MCI), and 179 subjects with early AD. Linear regression (LR), random forests (RF) and multifactor dimensionality reduction (MDR) models were used. The results demonstrate the effectiveness of using RF and MDR. The MDR model produced the best sensitivity in all comparisons using only 3 SNPs. Regarding specificity, LR resulted in the best specificity in two comparisons (NC vs. MCI and MCI vs. AD), while MDR produced the best specificity in comparison of NC vs. AD. Several significant polymorphisms associated with MCI and AD were identified. RF and MDR are alternatives to existing methods for detecting genetic interactions.
Numerical Simulations of Inspiratory Airflow in Healthy and Asthmatic
Human Airways
- Abstract: Publication year: 2019Source: American Journal of Biomedical Engineering, Volume 9, Number 1Endalew Getnet Tsega, V. K. KatiyarAsthma is a chronic lung disease that inflames and temporary narrows human airways with symptoms of shortness of breath, chest tightness, wheezing, and coughing. It occurs in people of all ages. The increasing atmospheric pollution, the changing lifestyle, increasing industrialization and urbanization have increased the prevalence of asthma several folds globally. In this study, the narrowing effects of asthma on inspiratory airflow dynamics in human upper and lower tracheobronchial airways for rest breathing conditions were investigated using computational fluid dynamics (CFD) techniques. Four airway models (healthy and asthmatic) were constructed for the numerical simulations. The inspiratory airflow velocity, wall pressure and wall shear stress were higher at the asthmatic airways than healthy airways. More significant difference of flow pattern between healthy and asthmatic airways was observed in upper generations than in lower generations. Strong secondary flow was observed in the upper generations for both healthy and asthmatic airways. The airway resistance was extremely higher in lower generation asthmatic airways. This study provides quantitative information on airflow dynamics during asthma attack which can be applied in asthma treatment.
QRS Detection Using Fractional Order Digital Differentiators
- Abstract: Publication year: 2019Source: American Journal of Biomedical Engineering, Volume 9, Number 1B. T. KrishnaDetection of QRS complex is an important step for the analysis of heart rate variability. It has been proved that the algorithms based on the use of differentiation are proven to be efficient and hence can be used for the real-time analysis. At the same time, fractional order digital differentiators are gaining their interest in many areas of research. In this paper, an attempt is made to detect QRS complex by making use of the proposed transfer functions. The results have been proven to be comparable to the conventional techniques.
None Invasive Intraocular Pressure Control Simulation: PF-04475270 Case
Study
- Abstract: Publication year: 2018Source: American Journal of Biomedical Engineering, Volume 8, Number 1Omer HamidPF-04475270 is a hypotensive intraocular pressure (IOP) agent; its linearized 6th and reduced 3rd order Pharmacokinetics/Pharmacodynamics (PKPD) state space models were utilized in the design of model predictive control (MPC) systems. The PF-04475270 PKPD model is taken from the literature. In frequency domain the drug sixth order model is acting as a low pass filter with a cutoff frequency of 0.515 µHz. Kalman filter is used to obtain observer gain of the MPC and also to estimate the simulated noisy IOP. Assumption is made about the availability of: Stimulus responsive drug loaded hydrogel, contact lens IOP sensor and an embedded MPC system. One intentional model parameter doubling showed unbounded intraocular pressure open loop response but behaved well under the proposed linearized MPC; a preliminary test of sensitivity. Four eye drops kept IOP at a desired level for 48 hours. Continuous controlled drug delivery system designed and simulated based on PF-04475270 model has lowered IOP from 100% to 80% of its initial value despite of the added noise to the input and the output.
EEG Classification in Brain Computer Interface (BCI): A Pragmatic
Appraisal
- Abstract: Publication year: 2018Source: American Journal of Biomedical Engineering, Volume 8, Number 1Bamidele Osalusi, Amole Abraham, David AborisadeBrain computer interface (BCI) is one of the technologies growing at an exponential rate with its applications extended to medical and non-medical fields. EEG is widely used in BCI for detection and analysis of abnormalities of the brain. EEG is characterized by inherently high temporal resolution and precision, low spatial resolution and specificity plus contains artifacts and redundant or noise information both from the subject and equipment interferences. Thus, feature extraction is a critical issue in translation algorithm development for BCI. Above all, BCI still faces a lot challenges that results in performance variation across and even within subjects. Thus, this work provides a concise but all encompassing review of methods that have been adopted in the recent time for development of an EEG classification in BCI.
A Systematic Study on Flowability and Compressibility of Symphonia
globulifera Stem Bark Powder for Tablet Dosage Form
- Abstract: Publication year: 2017Source: American Journal of Biomedical Engineering, Volume 7, Number 1Stephen Olaribigbe Majekodunmi, Uwaoma Lucky AligaThe stem bark of Symphonia globulifera is widely used in the treatment of several disorders ranging from parasitic disease, body pain, scabies, spiritual remedies, skin diseases to malaria, diabetes, venereal disease and erective problems in Africa and South America. The objective of the present research was to study the original flowability, compressibility and compactibility of Symphonia glubulifera stem bark and develop its tablet formulations by wet granulation and direct compression technology. The consolidation behaviour of drug and tablet formulations was studied by using Heckel and Leuenberger equations. Symphonia globulifera stem bark powder showed very poor flowability and compactibility. Kawakita analysis revealed improved flowability for formulations prepared by direct compression and wet granulation techniques. The Heckel plot showed that Symphonia globulifera stem bark powder is soft in nature and poor in die filling. Granules showed higher degree of plasticity and fragmentation than powder and direct compression formulations. The compression susceptibility parameter for compact formed by direct compression and wet granulation technique indicated that the maximum crushing strength is reached faster at lower pressures of compression as opposed to Symphonia globulifera stem bark powder. From this study, it is concluded that desired flowability, compressibility and compactibility of Symphonia glubulifera stem bark powder can be obtained by direct compression and wet granulation technique, being higher in the wet granulation.
EKG Signals – De-noising and Features Extraction
- Abstract: Publication year: 2016Source: American Journal of Biomedical Engineering, Volume 6, Number 6Saleh Alomari, Mohammed Shujauddin, Vahid EmamianThe need of effective method to obtain and analyse electrocardiogram (EKG) signal has inspired This research paper to designed an efficient algorithm that can handle any (EKG), remove the most dominant noises associated with it, and extract the important futures. EKG signal is an electrical signal represents the physical human’s heart activity. Nonetheless, this signal is affected by various noise including baseline wondering and power interference. These noises affect the signal to noise ratio (SNR) especially in P and T waves which have less amplitudes than R peaks. Removing these noises result in cleaner signal that can be conveniently processed to extract important features such as heart health condition. EKG features play the main role in diagnosing the heart rate, normality and abnormality of heart activities, and heart diseases. For a healthy person, one heart beat consists of P, QRS Complex, T, and in some signals U waves. In this paper, a robust and numerically sufficient algorithm is developed to de-nosing EKG signal and extract all major features. For de-nosing EKG signal, FIR Equiripple High pass filter is used. FIR Equiripple Low pass filter follows this filter to remove the power interference noises. Haar wavelet transform is used to accurately detect the R peaks. Haar wavelet is found to be better than other common methods that are used to detect R peaks. Haar wavelet shows high accuracy when it is applied on EKG signal to detect R peaks. In fact, it succeeded to detect all R peaks in hundreds of EKG signals (obtained from Physio net website). All other features are detected based on the R peaks by creating a set of windows which their lengths depend on the maximum normal wave durations and locations. These filters and algorithm have been implemented in Matlab. The algorithm has been applied on 108 EKG signals collected from physionet website and could detect all EKG signals’ heart rates successfully despite the fact that some signals were extremely distorted.
Biosensors
- Abstract: Publication year: 2016Source: American Journal of Biomedical Engineering, Volume 6, Number 6Ahmed Kh. SabrIn this paper aims to review how biosensors are made, where they can be used, their advanced and their detection methods. The biosensors are studied and fabricated to detect samples and measure demand values by using online websites that based on grounded theory. The paper reviewing some factors that help us to understand biosensor importance in our daily lives in most fields. Studies and researches are limited to real studies which has been collected from the result of experiment in various laboratories the suggested model is particularly useful for medical detecting to better illustrating and understanding the illness samples by display output of high resolution. In addition, they can be used in water treatment and food testing the paper shows design of biosensors, their application and types. Also; it highlights resolutions and sensitive the value that is detected by biosensors. Moreover, it presents simplicity of using biosensors So, it encourages the researches and inventors to focus on this challenge.