The capacity of electrocardiograms (ECG) recorded in hospital is increasing. Although modern electrocardiographs have digital output, most of ECG's are still recorded on grid papers. Recently, exchanging patients' clinical information between healthcare facilities has become very important. It will be very helpful if paper type of ECG could be converted to digital form. In this study, a morphological method is developed to digitize ECG signal from the paper charts. The results show that the method can erase the background noise and provide the digital ECG signal from ECG paper charts correctly. ECG signal digitization is practically used in ECG data exchanging between healthcare providers. Experimental results on sample ECG paper records are very encouraging and show the promise of efficiency in ECG data storage and retrieval and easy manipulation for clinical uses.

Electrocardiogram (ECG) signal plays a vital role in the primary diagnosis and monitoring of the health of heart. For the features extraction of the ECG signals such as R-peak, QRS complexes, T-waves etc., the significant noises have to be cancelled. The most significant noises corrupted the ECG signal are power line interference (50/60Hz), Electromyographic (EMG) noise due to motion artifacts, muscle contraction, baseline wanders due to respiration and perspiration, and instrumentation noise. Designing digital filters to suppress these noises sits in a quite important position for ECG signal processing and analysis. This paper presents the application of software digital filters in order to effectively eliminate these noises from the ECG signals. Several types of digital filters were designed and implemented along with their strengths and weaknesses. The quantitative properties of implemented digital filters were investigated with the ECG signals from MIT-BIH Arrhythmia Database as the test data. All the work was done with MATLAB ®. The noises were simulated and added to the test data. The performance of digital filters was described by the comparison of power spectra of the filtered noisy signal and the original database ECG recordings and the mean square error.

The system analysis of specific absorption rate (SAR) in human body exposed to a base station antenna by using finite difference time domain techniques was presented in this research works. The objectives of this work are to evaluate the knowledge and awareness about SAR among human body and mobile base station. The paper investigates the electromagnetic wave absorption inside a human body. The human body has been identified using dataset based on 2D object considering different electrical parameters.The SAR convinced inside the human body model exposed to a radiating base station antenna (BSA) has been considered for multiple numbers of carrier frequencies and input power of 20 W/carrier at GSM 900 band.The distance (R) of human body from BSA is varied in the range of 0.1 m to 5.0 m. For the number of carrier frequency equal to one and R = 0.1 m,the concentrated value of whole-body average SAR obtained by FDTD technique is found to be 0.68 W/kg which decreases either with increase of R or decrease of number of carrier frequencies. Safety distance for general public is found to be 1.5 m for number of carrier frequencies equal to one.The performance accuracy of this analysis meets the high level condition by comparing with the relevant system development in recent time.

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Background Transitional economies in Southeast Asia—a distinct group of developing countries—have experienced rapid urbanization in the past several decades due to the economic transition that fundamentally changed the function of their economies, societies and the environment. Myanmar, one of the least developed transitional economies in Southeast Asia, increased urbanization substantially from 25% in 1990 to 31% in 2019. However, major knowledge gaps exist in understanding the changes in urban land use and land cover and environment and their drivers in its cities. Methods We studied Yangon, the largest city in Myanmar, for the urbanization, environmental changes, and the underlying driving forces in a radically transitioned economy in the developing world. Based on satellite imagery and historic land use maps, we quantified the expansion of urban built-up land and constructed the land conversion matrix from 1990 through 2020. We also used three air pollutants to illustrate the changes in environmental conditions. We analyzed the coupled dynamics among urbanization, economic development, and environmental changes. Through conducting a workshop with 20 local experts, we further analyzed the influence of human systems and natural systems on Yangon’s urbanization and sustainability. Results The city of Yangon expanded urban built-up land rapidly from 1990 to 2000, slowed down from 2000 to 2010, but gained momentum again from 2010 to 2020, with most newly added urban built-up land appearing to be converted from farmland and green land in both 1990–2000 and 2010–2020. Furthermore, the air pollutant concentration of CO decreased, but that of NO2 and PM2.5 increased in recent years. A positive correlation exists between population and economic development and the concentration of PM2.5 is highly associated with population, the economy, and the number of vehicles. Finally, the expert panel also identified other potential drivers for urbanization, including the extreme climate event of Cyclone Nargis, capital relocation, and globalization. Conclusions Our research highlights the dramatic expansion of urban land and degradation of urban environment measured by air pollutants and interdependent changes between urbanization, economic development, and environmental changes.