A Novel Approach for Palpitation Using FPGA
Content
IJSRD - International Journal for Scientific Research & Development| Vol. 3, Issue 08, 2015 | ISSN (online): 2321-0613
A Novel Approach for Palpitations using FPGA
K.Soundarya1 N.Suresh2
P.G. Scholar 2Assistant Professor
1,2
Department of Electronics & Communication Engineering
1,2
Prathyusha Institute of Technology and Management
1
Abstract—The human heart is one of the most vital organs
in the entire human body. At present global, heart diseases
become a leading killer for humans. The goal is to reduce
the death toll by providing therapy in advance. The work
purposely deals with the design of FPGA by analyzing
patient‟s ECG and vital parameters as Body Temperature,
Pulse Rate, and Respiratory Rate are parallel monitored with
the help of smart sensors using GSM. These applications
send a SMS to the physician in case of emergency. It also
describes the design of FPGA that combines physiological
parameters by producing output. This work aims to design a
patient monitoring system using FPGA which is found to
minimize the chip area thereby reducing power consumption
and increase efficiency. The output is based on threshold
values by comparison process of mentioned given values
and are monitored parallel by saving the life of heart patient
especially for aged persons.
Key words: ECG, Blood Pressure, Body Temperature,
Respiratory Rate, FPGA, GSM, Threshold values
I. INTRODUCTION
Heart disease is one of the most prevalent and serious health
problems in the world. According to IANS, the disease kills
17.3 million people each year. The numbers are rising. Over
three quarters of CVD, deaths take place in where the people
are in the low and middle income groups. Further, CVD
claims more lives than all forms of cancer. By 2030, it is
expected that 23 million people will die from CVDs
annually. Patient monitoring systems have been designed in
an effort to bring down the mortality rate. A patient
monitoring system monitors the patient‟s physiological
parameters on a continuous basis and alerts the physician
and caretaker via SMS in the event of an abnormality being
detected.
The Patient Monitoring System currently in use has
been designed using a Microcontroller. This system has a
few inherent drawbacks such as system complexity, high
power consumption and a large chip area. This work aims to
improvise the existing system by implementing the patient
monitoring system using FPGA wherein the chip area is
minimized thereby reducing power consumption and
improving efficiency. This methodology deals with
measurement of the physiological parameters such as ECG,
Pulse Rate, Body Temperature and Respiratory Rate on a
continuous basis. An abnormality in any of these parameters
is intimated both to the physician as well as to the care taker
via SMS so as to ensure timely medical aid.
A patient monitoring system can be defined as an
analyzed collective data monitored continuously providing
better healthcare to the patients especially those in a critical
condition. It helps the physician to make informed
decisions, thereby getting timely attention for the patients.
II. RELATED STUDIES
Many works primarily on algorithms and software based
implementation for detection of abnormality heart rates that
have been measured already but we have designed a FPGA
with patient monitoring system to detect any abnormal heart
rate.
The current work is about an alert SMS sent to the
doctor through a microcontroller that has the drawback of
occupying large area and low power consumption [1].An
algorithm is assessed by an Electrocardiogram (ECG) signal
that triggers alarm for different types of arrhythmias but it
has a smaller accuracy of 95% and deficiency in noise
quality [2]. A wavelet based transform is used for measuring
the heart beats by using Pan and Tompkins algorithm in Lab
View. But the process is complex to detect abnormality and
results in smaller accuracy [3]. The presence of Linear
Discriminate Analysis (LDA) is used to detect abnormal
depending on a database classifier that leads to less accuracy
range of 90.38% [4].
The patient monitoring physiological parameters
are sent to a microcontroller in which average databases are
recorded such that it will alert the physician in case of
emergency through Zigbee. But it has the drawback of a
short range and a low data speed [5].The patient is also
monitored through a data mining algorithm which
compresses all the data in multi-channel through different
node processes. However it requires long computation to
solve the processes which results in delay in sending the
data and complexity [6]. The patient‟s vital signs like ECG,
heart rate, breathing rate, temperature, SpO2 are sent to the
doctor‟s phone using an Android. There is an improper
network failure during data transmission [7]. The other
details are also referred from [8]-[12].
This paper describes abnormal heart rate detection
by simultaneously monitoring patient's ECG that includes
other physiological parameters such as pulse rate;
respiratory rate and body temperature. It is based on
threshold based classifier value which is meant to save the
patient‟s life. An alert is sent to the physician when an
abnormal rate is detected through GSM.
III. PROTOTYPE HARDWARE DESCRIPTION
All rights reserved by www.ijsrd.com
524
A Novel Approach for Palpitations using FPGA
(IJSRD/Vol. 3/Issue 08/2015/132)
Fig. 1: Block Diagram of Patient Monitoring System
The proposed patient monitoring system uses Spartan Kit
for the said application. The architecture of the system is
shown in Fig. 1.
The following four analog input parameters are
described as below:
A. Body Temperature
The Thermistor sensor is used to detect the patient‟s body
temperature. The analog signals from patient‟s body are
amplified and converted into digital values which depend on
resistance changes in response to the patient‟s body
temperature. The normal is given as 45ºc.When the value is
above the normal, it sends an „SMS‟ as „T ABNORMAL‟ to
the physician every minute.
B. Electrocardiogram
The ECG of the patient is measured by fixing three
electrodes potential that are placed in patient‟s body i.e. on
right arm, left arm, right or left leg. The normal is given as
90-160 amplitude duration. When the value is above the
normal, it sends an „SMS‟ as „E ABNORMAL‟ to the
physician every minute.
C. Pulse Rate
An infrared sensor is used to detect the pulse rate. When the
patient‟s finger is placed between the IR transmitter and the
IR receiver, blood flow density increases simultaneously
with intensity and received at the IR receiver decreases and
vice versa. The normal is given as 80 beats per minute.
When the value is above the normal, it sends an „SMS‟ as „P
ABNORMAL‟ to the physician every minute.
D. Respiratory Rate
In this paper, two Thermistors are used for the measurement
of respiration. Here, one Thermistor is used for the patient‟s
respiration and the other is for the indication of room
temperature. The comparator compares both values and
gives the difference between them. The normal is given as
22 breaths per minute. When the value is above the normal,
it sends an „SMS‟ as „R ABNORMAL‟ to the physician
every minute.
E. FPGA Implementation
The process in FPGA kit are executed by external analog
inputs of patient‟s ECG, Body temperature, Respiratory rate,
and Pulse rate threshold values as shown in Figure 3. Here,
the values of ECG and Body temperature are amplified in
order to remove the distortion that is converted into digital
through ADC. But the respiratory rate is directly amplified
to FPGA and the output is digitalized. The patient‟s
condition comes to the physician‟s knowledge depending on
the values of the FPGA output. All the above parameters are
monitored continuously, if any of these parameters occur as
abnormal that immediately it sends a „SMS‟ to physician.
These values are displayed in LCD of proposed system and
SMS is send through GSM.
F. GSM
The GSM stands for Group Special Mobile, a group formed
by the Conference of European Posts and Telegraphs
(CEPT) in 1982 to research the merits of a European
standard for mobile telecommunications. One of the key
features of GSM is the Subscriber Identity Module,
commonly known as a SIM card. Here, the SIM is used
containing the patient‟s mobile number. Then the value of
four parameters (Body Temperature, ECG, Pulse Rate and
Respiratory Rate) is automatically updated when abnormal
is detected, it sends a SMS to physician for every one
minute between a short carrier bands as shown in Figure.1.
IV. SOFTWARE IMPLEMENTATION
The inputs that are taken from patient monitoring are
diagnosed by assigning a value to each parameter and then
converted into crisp decision values given to the FPGA kit.
These parameters such as body temperature, ECG, pulse
rate, respiratory rate are monitored continuously. Based on
output commands, a doctor receives an abnormal „SMS‟.
Let us consider the set X as the number of four
parameters = {Body Temperature, ECG, Pulse rate,
Respiratory rate} => {S1, S2, S3, S4} and Y as the patient‟s
condition= {Normal, Abnormal} => {N, AN}.Specification
of the patient‟s condition depends on these four parameters
which are expressed in (1) values as F selected from the set
as:
F= {Low, Normal, High} ……. (1)
For example, <Body temperature, low> means it
indicates that value given in a set P as: P= {<S1, V1>, <S2,
V2,><S3, V3><S4, V4>……<Sn, Vn>} Vn is the threshold
value that is applied to each parameter Sn. Where n=1, 2, 3,
4......
The set of rules are considered as parameters X
captured in a set of tables P, heart disease. The set of Y is
identified through an SMS. The value P is obtained from the
patient‟s condition as P(X, Y). The inference rules are
written as syntax in the form as: IF<Threshold
values> then < Threshold values > as,
IF (Body temperature is low) AND (Pulse rate is
low) AND (Respiratory Rate is low) AND (ECG is low)
THEN ABNORMAL.
IF (Body temperature is high) AND (Pulse rate is
high) AND (Respiratory Rate is high) AND (ECG is high)
THEN ABNORMAL.
IF (Body temperature is normal) AND (Pulse rate
is normal) AND (Respiratory Rate is normal) AND (ECG is
normal) THEN NORMAL.
The four parameters can be expressed as:
ECG
{
…...(2)
Body Temperature
{
…………….. (3)
Respiratory Rate
{
.................... (4)
Pulse Rate
{
……………….(5)
The above equations (2), (3),(4) and (5) shows the
method of implication based on commands S1, S2, S3, and S4
as low, high and normal. They are interfaced in FPGA and
send an “ABNORMAL” message at each minute with the
monitored values.
All rights reserved by www.ijsrd.com
525
A Novel Approach for Palpitations using FPGA
(IJSRD/Vol. 3/Issue 08/2015/132)
V. EXPERIMENTAL RESULT
The analyzed input parameters obtained from patient‟s body
are processed under FPGA and give output as digitalized
values of LCD are shown in Figure 2.The output of each
parameter is displayed under LCD and when it goes beyond
the normal range values, it sends an „ABNORMAL‟ SMS to
the physician every minute. This is shown in Fig. 2,3 and 4.
Fig. 2. LCD Display
Fig. 3. Prototype Model
Fig. 4: Abnormal Message via GSM
VI. CONCLUSION
The results got from vital parameters of the patient
monitoring system implemented with FPGA are promising
compared to other conventional methods. The parameters
that are measured using FPGA are sent as „SMS‟ to the
physician in the case of emergency. Due to this, patients get
timely help and hence are saved from high risk conditions.
The main advantage of FPGA kit lies in, its flexibility to all
field applications; power consumption and minimal chip
area. The architecture is purely based on commands that are
executed in a programmable chip. In future, the entire
process would be implemented using Bluetooth frequency in
which Spartan kit is used to get effective output using body
worn wearable smart antenna.
REFERENCES
[1] Adisorn Sirikham, “Abnormal Heart Rate Detection
Device warning via Mobile phone Network”, 2010.
[2] Joachim Behar, Julien Oster, Qiao Li, and Gari D.
Clifford, “ECG Signal Quality during Arrhythmia and
Its Application to False Alarm Reduction”, IEEE
Transactions on Biomedical Engineering, vol. 60, no.6,
June 2013, pp.1660-1666.
[3] MehrdadNourani, HlaingMinn, and Lakshman Tamil,
“A Patient-Adaptive Profiling Scheme for ECG Beat
Classification”, IEEE Transactions on Information
Technology in Biomedicine, vol.14, no.5, September
2010, pp.1153-1165.
[4] Taihai
Chen,
Evangelos
B.
Mazomenos,
KoushikMaharatna,
SrinandanDasmahapatra
and
Mahesan Niranjan, “Design of a Low-Power On-Body
ECG Classifier for Remote Cardiovascular Monitoring
Systems”, IEEE Journal on Emerging and Selected
Topics in Circuits and Systems,vol.3, no.1, March
2013, pp. 75-85.
[5] P.Karthik, C.Sureshkumar, P.Arunprasad, S.Pusparaj,
M.Jagadeeshraja, “Embedded Based Real-time Patient
Monitoring System”, International Journal of VLSI
and Embedded Systems, vol. 05, March 2014, pp.773777.
[6] OrenShmiel, TomerShmiel, Yaron Dagan and Mina
Teicher, “Processing of Multi-Channel Recording for
Data Mining Algorithm”, pp.1-11.
[7] PremaSundaram, “Patient Monitoring System Using
Android Technology”, International Journal of
Computer Science and Mobile Computing, vol. 2,
Issue.5, May2013, pp. 191-201.
[8] Swathi Banerjee and Madhuchhanda Mitra,
“Application of Cross Wavelet Transform for ECG
Pattern
Analysis
and
Classification”,
IEEE
Transactions on Instrumentation and Measurement,
vol.63, no.2, February, pp.326-333.
[9] Myung-kyung Suh , Chien-An Chen , Jonathan
Woodbridge, Michael Kai Tu ,Jung In Kim,
AniNahapetian,
Lorraine
S.
Evangelista,
MajidSarrafzadeh, “A Remote Patient Monitoring
System for Congestive Heart Failure”, May2011,pp. 115.
[10] Chin-Teng Lin, Kuan-Cheng Chang, Chun-Ling Lin,
Chia-Cheng Chiang, Shao-Wei Lu, Shih-Sheng Chang,
Bor-Shyh Lin “An Intelligent Telecardiology System
Using a Wearable and Wireless ECG to Detect Atrial
Fibrillation”, IEEE Transactions on Information
Technology in Biomedicine, vol.14, no.3, May 2010,
pp.726-733.
[11] N.Suresh and T.Sasilatha, “FPGA based patient
monitoring system using SOPC”, International Journal
oh Pharma and Bio Sciences, vol. 6, no. 1, Jan 2015,
pp.991-998.
[12] DipaliL.Gaikwad, Prabha Kasliwal, “FPGA Based
Critical Patient Health Monitoring Using Fuzzy Neural
Network”, International Journal of Scientific and
Engineering Research, vol. 4, Issue3, March 2013,
pp.1-5.
All rights reserved by www.ijsrd.com
526
A Novel Approach for Palpitations using FPGA
K.Soundarya1 N.Suresh2
P.G. Scholar 2Assistant Professor
1,2
Department of Electronics & Communication Engineering
1,2
Prathyusha Institute of Technology and Management
1
Abstract—The human heart is one of the most vital organs
in the entire human body. At present global, heart diseases
become a leading killer for humans. The goal is to reduce
the death toll by providing therapy in advance. The work
purposely deals with the design of FPGA by analyzing
patient‟s ECG and vital parameters as Body Temperature,
Pulse Rate, and Respiratory Rate are parallel monitored with
the help of smart sensors using GSM. These applications
send a SMS to the physician in case of emergency. It also
describes the design of FPGA that combines physiological
parameters by producing output. This work aims to design a
patient monitoring system using FPGA which is found to
minimize the chip area thereby reducing power consumption
and increase efficiency. The output is based on threshold
values by comparison process of mentioned given values
and are monitored parallel by saving the life of heart patient
especially for aged persons.
Key words: ECG, Blood Pressure, Body Temperature,
Respiratory Rate, FPGA, GSM, Threshold values
I. INTRODUCTION
Heart disease is one of the most prevalent and serious health
problems in the world. According to IANS, the disease kills
17.3 million people each year. The numbers are rising. Over
three quarters of CVD, deaths take place in where the people
are in the low and middle income groups. Further, CVD
claims more lives than all forms of cancer. By 2030, it is
expected that 23 million people will die from CVDs
annually. Patient monitoring systems have been designed in
an effort to bring down the mortality rate. A patient
monitoring system monitors the patient‟s physiological
parameters on a continuous basis and alerts the physician
and caretaker via SMS in the event of an abnormality being
detected.
The Patient Monitoring System currently in use has
been designed using a Microcontroller. This system has a
few inherent drawbacks such as system complexity, high
power consumption and a large chip area. This work aims to
improvise the existing system by implementing the patient
monitoring system using FPGA wherein the chip area is
minimized thereby reducing power consumption and
improving efficiency. This methodology deals with
measurement of the physiological parameters such as ECG,
Pulse Rate, Body Temperature and Respiratory Rate on a
continuous basis. An abnormality in any of these parameters
is intimated both to the physician as well as to the care taker
via SMS so as to ensure timely medical aid.
A patient monitoring system can be defined as an
analyzed collective data monitored continuously providing
better healthcare to the patients especially those in a critical
condition. It helps the physician to make informed
decisions, thereby getting timely attention for the patients.
II. RELATED STUDIES
Many works primarily on algorithms and software based
implementation for detection of abnormality heart rates that
have been measured already but we have designed a FPGA
with patient monitoring system to detect any abnormal heart
rate.
The current work is about an alert SMS sent to the
doctor through a microcontroller that has the drawback of
occupying large area and low power consumption [1].An
algorithm is assessed by an Electrocardiogram (ECG) signal
that triggers alarm for different types of arrhythmias but it
has a smaller accuracy of 95% and deficiency in noise
quality [2]. A wavelet based transform is used for measuring
the heart beats by using Pan and Tompkins algorithm in Lab
View. But the process is complex to detect abnormality and
results in smaller accuracy [3]. The presence of Linear
Discriminate Analysis (LDA) is used to detect abnormal
depending on a database classifier that leads to less accuracy
range of 90.38% [4].
The patient monitoring physiological parameters
are sent to a microcontroller in which average databases are
recorded such that it will alert the physician in case of
emergency through Zigbee. But it has the drawback of a
short range and a low data speed [5].The patient is also
monitored through a data mining algorithm which
compresses all the data in multi-channel through different
node processes. However it requires long computation to
solve the processes which results in delay in sending the
data and complexity [6]. The patient‟s vital signs like ECG,
heart rate, breathing rate, temperature, SpO2 are sent to the
doctor‟s phone using an Android. There is an improper
network failure during data transmission [7]. The other
details are also referred from [8]-[12].
This paper describes abnormal heart rate detection
by simultaneously monitoring patient's ECG that includes
other physiological parameters such as pulse rate;
respiratory rate and body temperature. It is based on
threshold based classifier value which is meant to save the
patient‟s life. An alert is sent to the physician when an
abnormal rate is detected through GSM.
III. PROTOTYPE HARDWARE DESCRIPTION
All rights reserved by www.ijsrd.com
524
A Novel Approach for Palpitations using FPGA
(IJSRD/Vol. 3/Issue 08/2015/132)
Fig. 1: Block Diagram of Patient Monitoring System
The proposed patient monitoring system uses Spartan Kit
for the said application. The architecture of the system is
shown in Fig. 1.
The following four analog input parameters are
described as below:
A. Body Temperature
The Thermistor sensor is used to detect the patient‟s body
temperature. The analog signals from patient‟s body are
amplified and converted into digital values which depend on
resistance changes in response to the patient‟s body
temperature. The normal is given as 45ºc.When the value is
above the normal, it sends an „SMS‟ as „T ABNORMAL‟ to
the physician every minute.
B. Electrocardiogram
The ECG of the patient is measured by fixing three
electrodes potential that are placed in patient‟s body i.e. on
right arm, left arm, right or left leg. The normal is given as
90-160 amplitude duration. When the value is above the
normal, it sends an „SMS‟ as „E ABNORMAL‟ to the
physician every minute.
C. Pulse Rate
An infrared sensor is used to detect the pulse rate. When the
patient‟s finger is placed between the IR transmitter and the
IR receiver, blood flow density increases simultaneously
with intensity and received at the IR receiver decreases and
vice versa. The normal is given as 80 beats per minute.
When the value is above the normal, it sends an „SMS‟ as „P
ABNORMAL‟ to the physician every minute.
D. Respiratory Rate
In this paper, two Thermistors are used for the measurement
of respiration. Here, one Thermistor is used for the patient‟s
respiration and the other is for the indication of room
temperature. The comparator compares both values and
gives the difference between them. The normal is given as
22 breaths per minute. When the value is above the normal,
it sends an „SMS‟ as „R ABNORMAL‟ to the physician
every minute.
E. FPGA Implementation
The process in FPGA kit are executed by external analog
inputs of patient‟s ECG, Body temperature, Respiratory rate,
and Pulse rate threshold values as shown in Figure 3. Here,
the values of ECG and Body temperature are amplified in
order to remove the distortion that is converted into digital
through ADC. But the respiratory rate is directly amplified
to FPGA and the output is digitalized. The patient‟s
condition comes to the physician‟s knowledge depending on
the values of the FPGA output. All the above parameters are
monitored continuously, if any of these parameters occur as
abnormal that immediately it sends a „SMS‟ to physician.
These values are displayed in LCD of proposed system and
SMS is send through GSM.
F. GSM
The GSM stands for Group Special Mobile, a group formed
by the Conference of European Posts and Telegraphs
(CEPT) in 1982 to research the merits of a European
standard for mobile telecommunications. One of the key
features of GSM is the Subscriber Identity Module,
commonly known as a SIM card. Here, the SIM is used
containing the patient‟s mobile number. Then the value of
four parameters (Body Temperature, ECG, Pulse Rate and
Respiratory Rate) is automatically updated when abnormal
is detected, it sends a SMS to physician for every one
minute between a short carrier bands as shown in Figure.1.
IV. SOFTWARE IMPLEMENTATION
The inputs that are taken from patient monitoring are
diagnosed by assigning a value to each parameter and then
converted into crisp decision values given to the FPGA kit.
These parameters such as body temperature, ECG, pulse
rate, respiratory rate are monitored continuously. Based on
output commands, a doctor receives an abnormal „SMS‟.
Let us consider the set X as the number of four
parameters = {Body Temperature, ECG, Pulse rate,
Respiratory rate} => {S1, S2, S3, S4} and Y as the patient‟s
condition= {Normal, Abnormal} => {N, AN}.Specification
of the patient‟s condition depends on these four parameters
which are expressed in (1) values as F selected from the set
as:
F= {Low, Normal, High} ……. (1)
For example, <Body temperature, low> means it
indicates that value given in a set P as: P= {<S1, V1>, <S2,
V2,><S3, V3><S4, V4>……<Sn, Vn>} Vn is the threshold
value that is applied to each parameter Sn. Where n=1, 2, 3,
4......
The set of rules are considered as parameters X
captured in a set of tables P, heart disease. The set of Y is
identified through an SMS. The value P is obtained from the
patient‟s condition as P(X, Y). The inference rules are
written as syntax in the form as: IF<Threshold
values> then < Threshold values > as,
IF (Body temperature is low) AND (Pulse rate is
low) AND (Respiratory Rate is low) AND (ECG is low)
THEN ABNORMAL.
IF (Body temperature is high) AND (Pulse rate is
high) AND (Respiratory Rate is high) AND (ECG is high)
THEN ABNORMAL.
IF (Body temperature is normal) AND (Pulse rate
is normal) AND (Respiratory Rate is normal) AND (ECG is
normal) THEN NORMAL.
The four parameters can be expressed as:
ECG
{
…...(2)
Body Temperature
{
…………….. (3)
Respiratory Rate
{
.................... (4)
Pulse Rate
{
……………….(5)
The above equations (2), (3),(4) and (5) shows the
method of implication based on commands S1, S2, S3, and S4
as low, high and normal. They are interfaced in FPGA and
send an “ABNORMAL” message at each minute with the
monitored values.
All rights reserved by www.ijsrd.com
525
A Novel Approach for Palpitations using FPGA
(IJSRD/Vol. 3/Issue 08/2015/132)
V. EXPERIMENTAL RESULT
The analyzed input parameters obtained from patient‟s body
are processed under FPGA and give output as digitalized
values of LCD are shown in Figure 2.The output of each
parameter is displayed under LCD and when it goes beyond
the normal range values, it sends an „ABNORMAL‟ SMS to
the physician every minute. This is shown in Fig. 2,3 and 4.
Fig. 2. LCD Display
Fig. 3. Prototype Model
Fig. 4: Abnormal Message via GSM
VI. CONCLUSION
The results got from vital parameters of the patient
monitoring system implemented with FPGA are promising
compared to other conventional methods. The parameters
that are measured using FPGA are sent as „SMS‟ to the
physician in the case of emergency. Due to this, patients get
timely help and hence are saved from high risk conditions.
The main advantage of FPGA kit lies in, its flexibility to all
field applications; power consumption and minimal chip
area. The architecture is purely based on commands that are
executed in a programmable chip. In future, the entire
process would be implemented using Bluetooth frequency in
which Spartan kit is used to get effective output using body
worn wearable smart antenna.
REFERENCES
[1] Adisorn Sirikham, “Abnormal Heart Rate Detection
Device warning via Mobile phone Network”, 2010.
[2] Joachim Behar, Julien Oster, Qiao Li, and Gari D.
Clifford, “ECG Signal Quality during Arrhythmia and
Its Application to False Alarm Reduction”, IEEE
Transactions on Biomedical Engineering, vol. 60, no.6,
June 2013, pp.1660-1666.
[3] MehrdadNourani, HlaingMinn, and Lakshman Tamil,
“A Patient-Adaptive Profiling Scheme for ECG Beat
Classification”, IEEE Transactions on Information
Technology in Biomedicine, vol.14, no.5, September
2010, pp.1153-1165.
[4] Taihai
Chen,
Evangelos
B.
Mazomenos,
KoushikMaharatna,
SrinandanDasmahapatra
and
Mahesan Niranjan, “Design of a Low-Power On-Body
ECG Classifier for Remote Cardiovascular Monitoring
Systems”, IEEE Journal on Emerging and Selected
Topics in Circuits and Systems,vol.3, no.1, March
2013, pp. 75-85.
[5] P.Karthik, C.Sureshkumar, P.Arunprasad, S.Pusparaj,
M.Jagadeeshraja, “Embedded Based Real-time Patient
Monitoring System”, International Journal of VLSI
and Embedded Systems, vol. 05, March 2014, pp.773777.
[6] OrenShmiel, TomerShmiel, Yaron Dagan and Mina
Teicher, “Processing of Multi-Channel Recording for
Data Mining Algorithm”, pp.1-11.
[7] PremaSundaram, “Patient Monitoring System Using
Android Technology”, International Journal of
Computer Science and Mobile Computing, vol. 2,
Issue.5, May2013, pp. 191-201.
[8] Swathi Banerjee and Madhuchhanda Mitra,
“Application of Cross Wavelet Transform for ECG
Pattern
Analysis
and
Classification”,
IEEE
Transactions on Instrumentation and Measurement,
vol.63, no.2, February, pp.326-333.
[9] Myung-kyung Suh , Chien-An Chen , Jonathan
Woodbridge, Michael Kai Tu ,Jung In Kim,
AniNahapetian,
Lorraine
S.
Evangelista,
MajidSarrafzadeh, “A Remote Patient Monitoring
System for Congestive Heart Failure”, May2011,pp. 115.
[10] Chin-Teng Lin, Kuan-Cheng Chang, Chun-Ling Lin,
Chia-Cheng Chiang, Shao-Wei Lu, Shih-Sheng Chang,
Bor-Shyh Lin “An Intelligent Telecardiology System
Using a Wearable and Wireless ECG to Detect Atrial
Fibrillation”, IEEE Transactions on Information
Technology in Biomedicine, vol.14, no.3, May 2010,
pp.726-733.
[11] N.Suresh and T.Sasilatha, “FPGA based patient
monitoring system using SOPC”, International Journal
oh Pharma and Bio Sciences, vol. 6, no. 1, Jan 2015,
pp.991-998.
[12] DipaliL.Gaikwad, Prabha Kasliwal, “FPGA Based
Critical Patient Health Monitoring Using Fuzzy Neural
Network”, International Journal of Scientific and
Engineering Research, vol. 4, Issue3, March 2013,
pp.1-5.
All rights reserved by www.ijsrd.com
526
