Influence of Artificial Microgravity on Human Arterial Vessels

Akulov, S. A.; Fedotov, A. A.; Макаров, И В; Sidorov, A.; Kosheleva, A.

doi:10.1007/978-3-030-17971-7_99

Cited by 2 publications

(1 citation statement)

References 12 publications

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“…To estimate blood pressure using features taken from electrocardiogram and photoplethysmogram signals, a non-invasive method was created [24,25]. Through machine learning specifically, artificial neural networks, their non-invasive method was meant to estimate blood pressures [26,27,28]. Initially, they conducted their experiment on a real data set of more than 2,000 electrocardiogram, blood pressures, and photoplethysmogram signals from patients of various hospitals within the years 2001 up to 2008.…”

Section: Electrocardiogramsmentioning

confidence: 99%

Development of a Real-Time ECG Signal Transmission Monitoring Algorithm

Don¹

2020

IJETER

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This research will focus on the creation of a simulated real-time ECG signal transmission Algorithm. A MATLAB program would be created to implement the algorithm and monitor the heart rate of the patient. The study focuses on the implementation of Electrocardiograms (ECG) through simulation and would receive the data through a transmitter to a receiver in real-time. The researchers tackled this topic because of its timeliness in present time society wherein most people neglect their physical health. The researchers will solve this problem through a simulation of an ECG signal using the Matrix Laboratory (MATLAB) software. The system will utilize an ECG sampled signal that was converted digitally so that it could be manipulated by MATLAB. An FSK line encoder will be used, and an additive white Gaussian noise will be applied to simulate real-life noise. The expected results will show that the simulation that will be carried out will create an accurate result with a good signal resolution. This study will prove that the MATLAB software is capable of transmitting and receiving ECG signals.

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