This document describes an efficient VLSI architecture for analyzing electrocardiogram (ECG) data to determine the health condition of a baby and mother. The proposed system first stores the mother's normal heart rate digitally. It then takes combined ECG readings of the mother and baby. After filtering, it obtains a digital report and compares the baby's signal to the stored reference to determine if the baby is healthy. Key blocks include memory to store reference signals, an analyzer to extract the baby's signal, and comparison of ECG waves to determine heart rate and health condition. The system aims to automatically monitor health and detect any threats in an accurate and energy efficient way.
Design an impedance plethysmography system for measuring limbMirza Baig
Abstract:
Limb blood as a flow permanent flow per beat and the volume of cardiac output
Safe method
Non-reactive
Advance analog amplifier
Microprocessor controller
Flexible output signal
Abstract: Electrocardiogram is a machine that is used for the detection and the analysis of the peaks of the ECG signal. ECG signal is used for the detection of various diseases related to the heart. The cardiac arrhythmia shows abnormalities of heart that is considered as the major threat to the human. The peaks that are present in the ECG signal are used for detection of the disease. The R peak of the ECG signal is used for the detection of the disease, the arrhythmia is detected as Tachycardia and Bradycardia. This paper presents a study of the ECG signal, peaks and of the various techniques that are used for the detection of disease.
Design an impedance plethysmography system for measuring limbMirza Baig
Abstract:
Limb blood as a flow permanent flow per beat and the volume of cardiac output
Safe method
Non-reactive
Advance analog amplifier
Microprocessor controller
Flexible output signal
Abstract: Electrocardiogram is a machine that is used for the detection and the analysis of the peaks of the ECG signal. ECG signal is used for the detection of various diseases related to the heart. The cardiac arrhythmia shows abnormalities of heart that is considered as the major threat to the human. The peaks that are present in the ECG signal are used for detection of the disease. The R peak of the ECG signal is used for the detection of the disease, the arrhythmia is detected as Tachycardia and Bradycardia. This paper presents a study of the ECG signal, peaks and of the various techniques that are used for the detection of disease.
“ Omnipresent ECG -oversee android watch” is designed to implement the increasing awareness of
alteration in the rhythm of heart beat and coronary heart diseases due to stress and other risk factors. Death
caused by heart diseases are high it can be reduced when a person’s heart beat rate is monitored
continuously for this purpose “Omnipresent ECG -oversee android watch” is used. It can be used by
higher officials/patients to keep track of their heart beat rate by self-opinion or for remote diagnosis of
chronic heart disease patients before sudden flicker. This watch works by ceaseless monitoring over a
person’s heart beat rate if any deflection is found it generates an alert. It is mainly used by people
who are living alone or by those who suffer from any heart disease. It scales the ECG using three lead
electrocardiography and impart three signals to smart watch for processing and for generating alert
it's a graduation project aims to
Diagnose cardiovascular diseases in real-time using machine learning through extracting features from ECG signal with accuracy of 85% to 100%
Health Monitoring KIOSK: An effective system for rural health managementijiert bestjournal
In the rural areas of our country,patients went to the public health centers (PHC) for their treatmen t. PHCs in India are allotted with hardly one doctor. It is really difficult at a single doctor�s end to provi de treatment to huge number of patients approaching a single doc tor. Therefore,in this work it is proposed to deve lop an automated diagnosis system by developing a Health K IOSK. The health KIOSK shall monitor and measure differen t physiological parameters of the body like heart r ate,blood pressure,body- temperature,SpO2. The KIOSK comprises of signal conditioning & data acquisition systems. The parameters recorded by the KIOSK are s tored in a database and can also be provided in pri nted output form. The patient can therefore approach the doctor with a printed data sheet about his/ her physiological parameters and also with a suggestive prescription for necessary consultation. This approach shall save the time of the doctor and the treatment process can be implemented effective ly.
Acquiring Ecg Signals And Analysing For Different Heart AilmentsIJERA Editor
This paper describes and focuses on acquiring and identification of cardiac diseases using ECG waveform in LabVIEW software, which would bridge the gap between engineers and medical physicians. This model work collects the waveform of an affected person. The waveform is analyzed for diseases and then a report is sent to the doctor through mail. Initially the waveforms are collected from the person using EKG sensor with the help of surface electrodes and the hardware controlled by MCU C8051, acquires ECG and also Phonocardiogram (PCG) synchronously and the waveform is sent to the PC installed with LabVIEW software through DAQ-6211. The waveform in digital format is saved and sent to the loops containing conditions for different diseases. If the waveform parameters coincide with any of the looping statements, particular disease is indicated. Simultaneously the patient PCG report is also collected in a separate database containing all information, which will be sent to the doctor through mail.
Classification and Detection of ECG-signals using Artificial Neural NetworksGaurav upadhyay
Electrocardiogram (ECG), a noninvasive technique is used as a primary diagnostic tool for
cardiovascular diseases. A cleaned ECG signal provides necessary information about the
electrophysiology of the heart diseases and ischemic changes that may occur. It provides
valuable information about the functional aspects of the heart and cardiovascular system. The
objective of the thesis is to automatic detection of cardiac arrhythmias in ECG signal.
Recently developed digital signal processing and pattern reorganization technique is used in
this thesis for detection of cardiac arrhythmias. The detection of cardiac arrhythmias in the
ECG signal consists of following stages: detection of QRS complex in ECG signal; feature
extraction from detected QRS complexes; classification of beats using extracted feature set
from QRS complexes. In turn automatic classification of heartbeats represents the automatic
detection of cardiac arrhythmias in ECG signal. Hence, in this thesis, we developed the
automatic algorithms for classification of heartbeats to detect cardiac arrhythmias in ECG
signal.QRS complex detection is the first step towards automatic detection of cardiac
arrhythmias in ECG signal. A novel algorithm for accurate detection of QRS complex in ECG
signal peak classification approach is used in ECG signal for determining various diseases . As
known the amplitudes and duration values of P-Q-R-S-T peaks determine the functioning of
heart of human. Therefore duration and amplitude of all peaks are found. R-R and P-R
intervals are calculated. Finally, we have obtained the necessary information for disease
detection .For detection of cardiac arrhythmias; the extracted features in the ECG signal will
be input to the classifier. The extracted features contain morphological l features of each
heartbeat in the ECG signal. This project is implemented by using MATLAB software. An
interface was created to easily select and process the signal. “.dat” format is used the for ECG
signal data. We have detected bradycardia and tachycardia. Massachusetts Institute of
Technology Beth Israel Hospital (MIT-BIH) arrhythmias database has been used for
performance analysis.
“ Omnipresent ECG -oversee android watch” is designed to implement the increasing awareness of
alteration in the rhythm of heart beat and coronary heart diseases due to stress and other risk factors. Death
caused by heart diseases are high it can be reduced when a person’s heart beat rate is monitored
continuously for this purpose “Omnipresent ECG -oversee android watch” is used. It can be used by
higher officials/patients to keep track of their heart beat rate by self-opinion or for remote diagnosis of
chronic heart disease patients before sudden flicker. This watch works by ceaseless monitoring over a
person’s heart beat rate if any deflection is found it generates an alert. It is mainly used by people
who are living alone or by those who suffer from any heart disease. It scales the ECG using three lead
electrocardiography and impart three signals to smart watch for processing and for generating alert
it's a graduation project aims to
Diagnose cardiovascular diseases in real-time using machine learning through extracting features from ECG signal with accuracy of 85% to 100%
Health Monitoring KIOSK: An effective system for rural health managementijiert bestjournal
In the rural areas of our country,patients went to the public health centers (PHC) for their treatmen t. PHCs in India are allotted with hardly one doctor. It is really difficult at a single doctor�s end to provi de treatment to huge number of patients approaching a single doc tor. Therefore,in this work it is proposed to deve lop an automated diagnosis system by developing a Health K IOSK. The health KIOSK shall monitor and measure differen t physiological parameters of the body like heart r ate,blood pressure,body- temperature,SpO2. The KIOSK comprises of signal conditioning & data acquisition systems. The parameters recorded by the KIOSK are s tored in a database and can also be provided in pri nted output form. The patient can therefore approach the doctor with a printed data sheet about his/ her physiological parameters and also with a suggestive prescription for necessary consultation. This approach shall save the time of the doctor and the treatment process can be implemented effective ly.
Acquiring Ecg Signals And Analysing For Different Heart AilmentsIJERA Editor
This paper describes and focuses on acquiring and identification of cardiac diseases using ECG waveform in LabVIEW software, which would bridge the gap between engineers and medical physicians. This model work collects the waveform of an affected person. The waveform is analyzed for diseases and then a report is sent to the doctor through mail. Initially the waveforms are collected from the person using EKG sensor with the help of surface electrodes and the hardware controlled by MCU C8051, acquires ECG and also Phonocardiogram (PCG) synchronously and the waveform is sent to the PC installed with LabVIEW software through DAQ-6211. The waveform in digital format is saved and sent to the loops containing conditions for different diseases. If the waveform parameters coincide with any of the looping statements, particular disease is indicated. Simultaneously the patient PCG report is also collected in a separate database containing all information, which will be sent to the doctor through mail.
Classification and Detection of ECG-signals using Artificial Neural NetworksGaurav upadhyay
Electrocardiogram (ECG), a noninvasive technique is used as a primary diagnostic tool for
cardiovascular diseases. A cleaned ECG signal provides necessary information about the
electrophysiology of the heart diseases and ischemic changes that may occur. It provides
valuable information about the functional aspects of the heart and cardiovascular system. The
objective of the thesis is to automatic detection of cardiac arrhythmias in ECG signal.
Recently developed digital signal processing and pattern reorganization technique is used in
this thesis for detection of cardiac arrhythmias. The detection of cardiac arrhythmias in the
ECG signal consists of following stages: detection of QRS complex in ECG signal; feature
extraction from detected QRS complexes; classification of beats using extracted feature set
from QRS complexes. In turn automatic classification of heartbeats represents the automatic
detection of cardiac arrhythmias in ECG signal. Hence, in this thesis, we developed the
automatic algorithms for classification of heartbeats to detect cardiac arrhythmias in ECG
signal.QRS complex detection is the first step towards automatic detection of cardiac
arrhythmias in ECG signal. A novel algorithm for accurate detection of QRS complex in ECG
signal peak classification approach is used in ECG signal for determining various diseases . As
known the amplitudes and duration values of P-Q-R-S-T peaks determine the functioning of
heart of human. Therefore duration and amplitude of all peaks are found. R-R and P-R
intervals are calculated. Finally, we have obtained the necessary information for disease
detection .For detection of cardiac arrhythmias; the extracted features in the ECG signal will
be input to the classifier. The extracted features contain morphological l features of each
heartbeat in the ECG signal. This project is implemented by using MATLAB software. An
interface was created to easily select and process the signal. “.dat” format is used the for ECG
signal data. We have detected bradycardia and tachycardia. Massachusetts Institute of
Technology Beth Israel Hospital (MIT-BIH) arrhythmias database has been used for
performance analysis.
The ECG signals captured from the body of the patient using three electrode model is processed and
conditioned by the analog front end device is finally sent to the data acquisition unit. The data acquisition
unit used is the user pc/ laptop with MATLAB. Using very specific image processing techniques the critical
intelligence from the captured image is extracted. From this processed image any sort of abnormal
conditions is determined which is informed to the corresponding doctor via text message. Simultaneously
the processed image is sent to the doctor mail by using specific TCP/IP protocol.
The ECG signals captured from the body of the patient using three electrode model is processed and conditioned by the analog front end device is finally sent to the data acquisition unit. The data acquisition unit used is the user pc/ laptop with MATLAB. Using very specific image processing techniques the critical intelligence from the captured image is extracted. From this processed image any sort of abnormal conditions is determined which is informed to the corresponding doctor via text message. Simultaneously the processed image is sent to the doctor mail by using specific TCP/IP protocol.
Sleep Apnea Identification using HRV Features of ECG Signals IJECEIAES
Sleep apnea is a common sleep disorder that interferes with the breathing of a person. During sleep, people can stop breathing for a moment that causes the body lack of oxygen that lasts for several seconds to minutes even until the range of hours. If it happens for a long period, it can result in more serious diseases, e.g. high blood pressure, heart failure, stroke, diabetes, etc. Sleep apnea can be prevented by identifying the indication of sleep apnea itself from ECG, EEG, or other signals to perform early prevention. The purpose of this study is to build a classification model to identify sleep disorders from the Heart Rate Variability (HRV) features that can be obtained with Electrocardiogram (ECG) signals. In this study, HRV features were processed using several classification methods, i.e. ANN, KNN, N-Bayes and SVM linear Methods. The classification is performed using subjectspecific scheme and subject-independent scheme. The simulation results show that the SVM method achieves higher accuracy other than three other methods in identifying sleep apnea. While, time domain features shows the most dominant performance among the HRV features.
The term Arrhythmia refers to any change from the normal sequence in the electrical impulses. It is also treated as abnormal heart rhythms or irregular heartbeats. The rate of growth of Cardiac Arrhythmia disease is very high & its effects can be observed in any age group in society. Arrhythmia detection can be done in many ways but effective & simple method for detection & diagnosis of Cardiac Arrhythmia is by doing analysis of Electrocardiogram signals from ECG sensors. ECG signal can give us the detail information of heart activities, so we can use ECG signals to detect the rhythm & behaviour of heart beats resulting into detection & diagnosis of Cardiac Arrhythmia. In this paper new & improved methodology for early Detection & Classification of Cardiac Arrhythmia has been proposed. In this paper ECG signals are captured using ECG sensors & this ECG signals are used & processed to get the required data regarding heart beats of the human being & then proposed methodology applies for Detection & Classification of Cardiac Arrhythmia. Detection of Cardiac Arrhythmia using ECG signals allows us for easy & reliable way with low cost solution to diagnose Arrhythmia in its prior early stage.
A Real Time Electrocardiogram (ECG) Device for Cardiac PatientsIJERD Editor
Now-a-days due to rising stress levels, change in lifestyles and a variety of different issues, the number of people suffering from heart related diseases is increasing. This number would significantly rise in the next few years. As the technology enhanced, a significant paradigm shift has been observed in the biomedical industry. To tackle the heart related issues, technology can be introduced in one’s life. This paper proposes a wireless, wearable ECG device capable of processing the patient’s ECG in a real time environment. It is capable of comparing the ECG with threshold parameters, and if ECG of the patient is not in the range of the threshold values, the device notifies the cardiac patient’s mobile phone by sending a Multimedia Messaging Service (MMS) of the changed ECG and, in turn the patient’s mobile phone sends this changed ECG image to the mobile phone present at the hospital.
Design and Implementation of wireless heart monitor for expectant mothers in ...IJMER
A low cost Maternal & Fetal Heart Rate (MFHR) monitor is introduced in an attempt to reduce or eliminate hypoxic episodes well before the development of fetal asphyxia. MFHR monitoring is sensitive and detects fetal hypoxia early in the evolution to acidosis. The abdominal electrocardiogram (AECG) is the recording of the cardiac activity of both the mother and the fetus. The main challenge is to extract the fetal ECG, which is strongly distorted by maternal component of dominating energy and artifacts like baseline wander and power-line interference which were effectively preprocessed and filtered by using a Kaiser FIR filter having a SNR ratio of 13.68 , filter order of 298 and a Notch filter (fc = 50 Hz) with a bandwidth of 2 Hz respectively. Our endeavor has been to design this MFHR monitoring device using a smartphone. This system continuously monitors the patient’s AECG data especially in the 3rd trimester. For the ongoing research work the maternal AECG signals were taken from the Physionet non-invasive ECG database. The AECG file is transferred from the PC to a microcontroller ATMEGA32A which is interfaced to a Bluetooth module. Data is then transferred wirelessly via Bluetooth to the phone. The smartphone contains an application that displays data received from the Bluetooth module interfaced with a plotter application. This Bluetooth Plotter application plots the ECG waveforms of the content on the phone. Various inferences were effectively made based upon the ECG graphs produced on the phone, thus giving the doctors an alert about the patient’s and Fetal ECG information. Further research will examine the real time patient’s data from the hospital assigned to us.
Overview of the fundamental roles in Hydropower generation and the components involved in wider Electrical Engineering.
This paper presents the design and construction of hydroelectric dams from the hydrologist’s survey of the valley before construction, all aspects and involved disciplines, fluid dynamics, structural engineering, generation and mains frequency regulation to the very transmission of power through the network in the United Kingdom.
Author: Robbie Edward Sayers
Collaborators and co editors: Charlie Sims and Connor Healey.
(C) 2024 Robbie E. Sayers
About
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
Technical Specifications
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
Key Features
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface
• Compatible with MAFI CCR system
• Copatiable with IDM8000 CCR
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
Application
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
CFD Simulation of By-pass Flow in a HRSG module by R&R Consult.pptxR&R Consult
CFD analysis is incredibly effective at solving mysteries and improving the performance of complex systems!
Here's a great example: At a large natural gas-fired power plant, where they use waste heat to generate steam and energy, they were puzzled that their boiler wasn't producing as much steam as expected.
R&R and Tetra Engineering Group Inc. were asked to solve the issue with reduced steam production.
An inspection had shown that a significant amount of hot flue gas was bypassing the boiler tubes, where the heat was supposed to be transferred.
R&R Consult conducted a CFD analysis, which revealed that 6.3% of the flue gas was bypassing the boiler tubes without transferring heat. The analysis also showed that the flue gas was instead being directed along the sides of the boiler and between the modules that were supposed to capture the heat. This was the cause of the reduced performance.
Based on our results, Tetra Engineering installed covering plates to reduce the bypass flow. This improved the boiler's performance and increased electricity production.
It is always satisfying when we can help solve complex challenges like this. Do your systems also need a check-up or optimization? Give us a call!
Work done in cooperation with James Malloy and David Moelling from Tetra Engineering.
More examples of our work https://www.r-r-consult.dk/en/cases-en/
Student information management system project report ii.pdfKamal Acharya
Our project explains about the student management. This project mainly explains the various actions related to student details. This project shows some ease in adding, editing and deleting the student details. It also provides a less time consuming process for viewing, adding, editing and deleting the marks of the students.
Cosmetic shop management system project report.pdfKamal Acharya
Buying new cosmetic products is difficult. It can even be scary for those who have sensitive skin and are prone to skin trouble. The information needed to alleviate this problem is on the back of each product, but it's thought to interpret those ingredient lists unless you have a background in chemistry.
Instead of buying and hoping for the best, we can use data science to help us predict which products may be good fits for us. It includes various function programs to do the above mentioned tasks.
Data file handling has been effectively used in the program.
The automated cosmetic shop management system should deal with the automation of general workflow and administration process of the shop. The main processes of the system focus on customer's request where the system is able to search the most appropriate products and deliver it to the customers. It should help the employees to quickly identify the list of cosmetic product that have reached the minimum quantity and also keep a track of expired date for each cosmetic product. It should help the employees to find the rack number in which the product is placed.It is also Faster and more efficient way.
Welcome to WIPAC Monthly the magazine brought to you by the LinkedIn Group Water Industry Process Automation & Control.
In this month's edition, along with this month's industry news to celebrate the 13 years since the group was created we have articles including
A case study of the used of Advanced Process Control at the Wastewater Treatment works at Lleida in Spain
A look back on an article on smart wastewater networks in order to see how the industry has measured up in the interim around the adoption of Digital Transformation in the Water Industry.
Water Industry Process Automation and Control Monthly - May 2024.pdf
Efficient VLSI Architecture for Data Analysis of ECG
1. EFFICIENT VLSI ARCHITECTURE FOR
DATA ANALYSIS OF ECG
Presented by
1.CH.REVATHI 16MQ1A0407
2.B.N.SULOCHANA 16MQ1A0404
3.P.N.V.LAKSHMI 16MQ1A0463
4.A.SAI RAMESH 17MQ5A0412
Under Esteemed Guidence
By
Mr.K.SAI SUDHEER,M.Tech.,
Assistant Professor
2. CONTENTS
Abstract
Introduction
Existed system
Dis-advantages of the Existed System
Proposed system
Explanation of each block
Simulation
Advantages
Applications
References
3. ABSTRACT
In this project we will use the efficient VLSI architecture for the data
analysis of ECG.
Here firstly the data will be saved in digital form.
The normal heart rate of the lady is taken and saved in digital form.
when ever we want to know the condition of the baby,again we will note the
heart rate of the mother and baby.
After applying filter, digital report is obtained. In this digital report the health
condition of baby is present.
4. If the obtained digital form of baby from filter is exactly same as the stored
digital form of the reference baby signal .
Then we can say that the baby is in Healthy condition.
So that we can generate the baby's ECG signal in digital form from it.
Hence this architecture will give automatically the health report of baby’s
condition and mother’s condition.
5. INTRODUCTION
Recently, due to the huge and remarkable advancement in biotechnology,
the development of a dedicated hardware system for accurate analysis,
classification and prediction of ECG Signals in real time has become
possible.
The main requirements are low-power consumption and low-energy
operation of hardware so that we can increase the battery life along with
the small area for wear ability.
Many attempts succeeded to implement ECG signal processing and
classification of systems in hardware
6. EXISTED SYSTEM
In existing one's no ECGS systems are used.
If ECG is not used we can not predict the health condition of the
baby ,then there will be loss of mother's and baby's life also.
9. Continution……….
By using ECG the health condition of both baby and mother will be given.
The record of that patient will be saved effectively in memory.
Here first mother ECG signal will be taken.
General baby ECG signal is also stored in digitl form.
Next mother + baby ECG signal will be taken.
At last by analyzing these two baby binary ECG signal is appeared.
Now obtained signal is compared with the baby's digial form.
From this we can say whether the baby is in Healthy condition or not.
13. BINARY SIGNAL
• Binary signal consists of only two possible values.
• These values are represented by the binary digits, or bits, 1 and 0.
• We are converting the analog signal in to binary data, as we are required
binary data for the procedure.
14. MEMORY
• Memory is used to store the bits in cells.
• Here we are storing the binary data of the mother.
• We are using this data to extract the baby signal from mother + baby signal
at the required month.
15. ANALYZER
Analyzer is a tool used to analyze the given input data.
In this Analyer the inputs are Mother+Baby Signal Data and Mother Signal
Data.
The Output of the Analyser is Baby Signal Data Which Comprises of that
Baby's Heart Beat.
16. ECG SIGNAL
An ECG signal will be acquired using a bio-potential amplifier and then
displayed using instrumentation software.
where a gain control will be created to adjust its amplitude.
Finally, the recorded ECG will be analyzed.
Electrocardiography is the process of producing an electrocardiograma
recording – a graph of voltage versus time – of the electrical activity of the
heart[4] using electrodes placed on the skin.
17. These electrodes detect the small electrical changes that are a consequence
of cardiac muscle depolarization followed by repolarization during each
cardiac cycle (heartbeat).
There are three main components to an ECG:
the P wave, which represents the depolarization of the atria.
the QRS complex, which represents the depolarization of the ventricles.
the T wave, which represents the repolarization of the ventricles.
20. Heart Rate of a Pregnant lady
• The normal heart rate of a woman is about 73 to 77 beats per minute (bpm).
It increases to 86 to 90 bpm as the pregnancy progresses.
Explanation:
First trimester
Heart rate changes begin in the first trimester.
During the first trimester, the heart rate increases to 80-84 bpm.
21. Second trimester
By the beginning of the second trimester, the heart is pumping 30 % to 50
% more blood than normal.
The smooth muscle relaxes and the arteries dilate to handle the increase in
circulating blood volume while maintaining normal blood pressure.
However, the heart rate increases to 82-86 bpm.
22. Third trimester
By the end of the third trimester,
the heart is pumping from 40 % to
90 % more blood than before
pregnancy.
The resting heart rate increases to
86-90 bpm.
26. SOFTWARE USED
Xilinx 14.7 ISE software
FPGA family: virtex 6
Windows 10 with 64 bit operating system
27. ADVANTAGES
• Detects very fast.
• Accurate Signals will be obtained.
• We can Reduce the Area of Design by Implementing this in Chip Level.
28. APPLICATIONS
Useful in Emergency conditions.
Health condition will be stored and compared when ever we want.
29. REFERENCES
• N. Bayasi, T. Tekeste, H. Saleh, A. Khandoker, B. Mohammad, and M.
Ismail, “Adaptive technique for P and T wave delineation in
electrocardiogram signals,” in Proc. IEEE 36th Annu. Int. Conf. Eng. Med.
Biol. Soc., Aug. 2014, pp. 90–93.
• P. Tadejko and W. Rakowski, “Mathematical morphology based ECG
feature extraction for the purpose of heartbeat classification,” in Proc. IEEE
6th Int. Conf. Comput. Inf. Syst. Ind. Manage. Appl. (CISIM), Jun. 2007,
pp. 322–327.
• A.L. Goldberger et al., “Physiobank, physiotoolkit, and physionet:
Components of a new research resource for complex physiologic
signals,”Circulation, vol. 101, no. 23, pp. e215–e220, Jun. 2000.