scholarly journals ECG signal monitoring based on Covid-19 patients: Overview

2021 ◽  
pp. 45-54
Author(s):  
Amine Saddik *, Rachid Latif and Abdoullah Bella ◽  
Keyword(s):  
Artificial Intelligence ◽  
Image Processing ◽  
Heart Rate ◽  
Respiratory System ◽  
Low Cost ◽  
Ecg Signal ◽  
Heart Rate Monitoring ◽  
Frequent Contact ◽  
Cardiac System ◽  
Signal Monitoring

ECG signal monitoring is a very important step for patients. Especially for those infected by covid-19. This pandemic has shown that the use of artificial intelligence helps to control the propagation of this virus. Particularly the high spread of this virus influences the number of the infected population. As well as the fact that this virus attacks the respiratory system which influences the cardiac system. Therefore, an ECG signal monitoring is mandatory. Our work presents an overview based on various approaches developed for ECG signal monitoring. These techniques are based on non-contact monitoring approaches. These approaches will help to avoid frequent contact with patients and doctors. As well as non-contact ECG signal monitoring is based on low-cost techniques, which reduces the price compared to other sensors. After the revision, we can conclude that the most suitable solution for heart rate monitoring is based on image processing using RGB cameras. These solutions are accurate, low cost, and protect the doctors.

scholarly journals Sensor Based Automatic Neonate Respiration Monitoring System

2019 ◽  
Vol 9 (2) ◽  
pp. 1296-1299
Keyword(s):  
Heart Rate ◽  
Internet Of Things ◽  
Monitoring System ◽  
Respiratory System ◽  
Medical Information ◽  
Low Cost ◽  
Research Work ◽  
Breathing Rate ◽  
Flow Sensors ◽  
Respiration Monitoring

This research work aims to create awareness and monitor the breath rate of a neonate using the air flow sensors and to reduce the number of infants’ death. It is designed based on the Arduino which is open-source electronics platform for hardware and software use. This prototype is developed for reliable and efficient baby monitoring system and play as infant care and monitoring system.A cardio respiratory system is used to monitor the infant’s heart rate, rhythm, breathing rate and other relevant and useful medical information using Electro Cardio Graph (ECG) and other IoT (Internet of Things) devices.This research work proved that the respiration monitoring system for infants can be implemented at low cost and also can prevent the respiration failure deaths.

Low cost heart rate monitoring device using Bluetooth

2014 ◽  
Author(s):  
Ridza Azri Ramlee ◽  
Mohd Azlshah Bin Othman ◽  
Mohammad Ikhwan Bin Abdul Aziz ◽  
Hamzah Asyrani bin Sulaiman
Keyword(s):  
Heart Rate ◽  
Low Cost ◽  
Monitoring Device ◽  
Heart Rate Monitoring

scholarly journals Explainable artificial intelligence for heart rate variability in ECG signal

2020 ◽  
Vol 7 (6) ◽  
pp. 146-154
Author(s):  
Sanjana K. ◽  
Sowmya V. ◽  
Gopalakrishnan E.A. ◽  
Soman K.P.
Keyword(s):  
Artificial Intelligence ◽  
Heart Rate ◽  
Heart Rate Variability ◽  
Ecg Signal ◽  
Explainable Artificial Intelligence

A low cost optical sensor based heart rate monitoring system

2013 ◽  
Author(s):  
Mohammad Nasim Imtiaz Khan ◽  
Dewan Fahim Noor ◽  
Md. Jubaer Hossain Pantho ◽  
Tahmid Syed Abtahi ◽  
Farhana Parveen ◽  
...  
Keyword(s):  
Heart Rate ◽  
Monitoring System ◽  
Optical Sensor ◽  
Low Cost ◽  
Heart Rate Monitoring

A Portable ECG Monitor with Low Power Consumption and Small Size Based on AD8232 Chip

2014 ◽  
Vol 513-517 ◽  
pp. 2884-2887 ◽  
Author(s):  
Tan Cheng Lu ◽  
Peng Liu ◽  
Xiang Gao ◽  
Qi Yong Lu
Keyword(s):  
Heart Rate ◽  
Power Consumption ◽  
Low Power ◽  
Mobile Phone ◽  
Low Cost ◽  
Low Power Consumption ◽  
Ecg Signal ◽  
Fast Recovery ◽  
Analog Front End ◽  
Bluetooth Communication

This paper design a portable ECG monitor based on mobile phone. Using the single-lead heart rate monitor analog front-end of AD8232 chip produced by ADI co. Ltd., the monitor can measure human ECG signal and heart rate with only two electrode pads placed on chest, and display the ECG signal on the mobile phone via Bluetooth communication in real time. It also can simply measure the heart rate by touching the two electrodes of the monitor directly. The system has many functions like ECG signal analysis, heart rate counting, arrhythmia detection, signal playback, leads off detection, fast recovery ECG. The result shows that the portable ECG monitor is low cost, low power consumption, small size and easy to carry, etc.

scholarly journals The use of heart rate monitoring in the estimation of energy expenditure: a validation study using indirect whole-body calorimetry

1989 ◽  
Vol 61 (2) ◽  
pp. 175-186 ◽  
Author(s):  
Sana M. Ceesay ◽  
Andrew M. Prentice ◽  
Kenneth C. Day ◽  
Peter R. Murgatroyd ◽  
Gail R. Goldberg ◽  
...  
Keyword(s):  
Heart Rate ◽  
Energy Expenditure ◽  
Predictive Power ◽  
Low Cost ◽  
Total Energy Expenditure ◽  
Whole Body ◽  
Heart Rate Monitoring ◽  
Calibration Curves ◽  
Individual Calibration ◽  
The Mean

1. A modified heart rate (HR) method for predicting total energy expenditure (TEE) was cross-validated against whole-body calorimetry (CAL). Minute-by-minute HR was converted to energy expenditure (EE) using individual calibration curves when HR exceeded a pre-determined ‘FLEX’ value designed to discriminate periods of activity. (‘FLEX’ HR was defined as the mean of the highest HR during rest and the lowest HR during the lightest imposed exercise.) Sedentary EE (below FLEX) was calculated as the mean EE during lying down, sitting and standing at rest. Sleeping EE was calculated as basal metabolic rate (BMR) predicted from standard equations.2. Calibration curves of oxygen consumption v. HR for different postures at rest and during exercise were obtained for twenty healthy subjects (eleven male, nine female); mean r 0.941 (SD 0.04). The mean FLEX HR for men and women were 86 (sd 10) and 96 (SD 6) beats/min respectively.3. Simultaneous measurements of HR and EE were made during 21 h continuous CAL, which included 4 x 30 min imposed exercise (cycling, rowing, stepping, jogging). HR exceeded FLEX for a mean of 98 (SD 41) min. Mean TEE by CAL (TEE. CAL) was 8063 (sd 1445) kJ.4. The HR method yielded a mean non-significant underestimate in TEE (TEE. HR) of 1.2 (sd 6.2)% (range−11.4 to + 10.6 %). Regression of TEE. HR (y) v. TEE. CAL (X) yielded Y = 0.868 X +927 kJ, r 0.943, se of the estimate 458 kJ, n 20.5. The satisfactory predictive power and low cost of the method makes it suitable for many field and epidemiological applications.

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