Abdullah Bin Queyam

Work place: Department of Instrumentation and Control Engineering, Dr. B. R. Ambedkar National Institute of Technology, Jalandhar-144011, Punjab, India

E-mail: abdullahbinqueyam@nitj.ac.in


Research Interests: Medical Informatics, Computer systems and computational processes, Computer Graphics and Visualization, Virtual Reality, Medical Image Computing


Abdullah Bin Queyam received his B. Tech degree in Electronics Instrumentation and Control Engineering from Rajasthan Technical University Kota, India. He received his M. Tech degree in Electronics Instrumentation and Control Engineering from Thapar University Patiala, Punjab, India. Currently, he is pursuing Ph. D. from National Institute of Technology Jalandhar, Punjab, India. His areas of interest are Biomedical Instrumentation, Virtual Instrumentation and Medical Signal Processing. He has published several research publications in national and international journals. He is also a student member of IEEE.

Author Articles
Doppler Ultrasound Based Non-Invasive Heart Rate Telemonitoring System for Wellbeing Assessment

By Abdullah Bin Queyam Sharvan Kumar Pahuja Dilbag Singh

DOI: https://doi.org/10.5815/ijisa.2018.12.07, Pub. Date: 8 Dec. 2018

Telemonitoring in the field of healthcare has vastly improved the quality of clinical diagnosis and disease prevention by providing timely medical consultation to people living in rural and remote areas. To monitor the health state of a patient certain vital physiological parameter like electrocardiogram (ECG), respiration rate, blood pressure, oxygen saturation, etc. are acquired and analyzed. Listening to the heart sounds (auscultation) is also a quick method to monitor the health state of the patient’s heart. In this paper, we propose the use of a portable Doppler ultrasound sensor for measuring the heart sounds reliably and to transmit the data for further clinical telemonitoring. We have developed an ultrasound-based hardware prototype which is non-invasive in nature and easy to operate. Its portability, high accuracy, low cost, and wireless nature make this device suitable for home-based self-diagnostic applications. The developed prototype was successfully able to capture both fundamental heart sounds S1 and S2 reliably and transfer the signal wirelessly to the LabVIEW-based monitoring and data logging unit. This unit extracts clinically useful health information like heart rate (HR), R-R interval and heart rate variability (HRV) using signal processing algorithms. Health information is then transmitted via the Internet to a distant hospital for further improved clinical diagnosis and consultancy. The prototype was validated on 40 healthy males in the age group of 25-35 years, and the results show an overall accuracy of 96.74% in HR detection when compared with an ECG sensor, a photoplethysmograph (PPG) sensor, a pulse oximeter device and manual auscultation.

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Simulation and Analysis of Umbilical Blood Flow using Markov-based Mathematical Model

By Abdullah Bin Queyam Sharvan Kumar Pahuja Dilbag Singh

DOI: https://doi.org/10.5815/ijisa.2017.03.06, Pub. Date: 8 Mar. 2017

The intra-uterine development of the fetus depends on various factors, one such critical factor is umbilical blood flow because the quantity of oxygen delivered to the placenta and to the fetus is directly limited by umbilical blood flow rate. Since the measurement of the hemodynamic quantities such as blood pressure and blood flow rate is not possible in utero hence the use of patient-specific mathematical modeling is beneficial for the assessment of feto-maternal well-being. A Markov model based mathematical model of fetal circulation is developed by taking three node concept. The fetus, the umbilical cord, and the placenta represent the 3 nodes of Markov model. A LabVIEW-based virtual instrument is designed to simulate the mathematical model which results in waveform similar to Doppler blood flow velocimetry of umbilical artery. The model is simulated at various degree of conductivity of the umbilical cord to the oxygenated blood. Simulation results show that the umbilical artery blood flow velocity waveform depends on gestation age, fetal heart rate, uterine contraction and placental insufficiency. The Doppler indices calculated from simulation helps in predicting both fetal and maternal abnormalities at various degrees of the conductivity to the blood flow passage. Therefore, integrating patient-specific models along with established medical equipments will be helpful in identifying true intra-uterine growth restricted fetuses from normal fetuses and helps clinicians to take timely interventions.

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