SlideShare ist ein Scribd-Unternehmen logo
1 von 8
Downloaden Sie, um offline zu lesen
Health Informatics-An International Journal (HIIJ) Vol.3, No.3,August 2014 
SMART HOSPITAL TECHNOLOGY 
1 M J Jayashree ,2Aju Sam Sunny, 3Anu John, 4Ashley Anna Sunny, 5Sruthi Susan 
Sam. 
Department of Electronics & Communication Engineering,Mar Baselios College of 
Engineering and Technology,Mar IvaniosVidya Nagar, Bethany Hills , Nalanchira 
Thiruvananthapuram -15, Kerala, India 
ABSTRACT 
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. 
KEYWORDS 
DFT, FFT, IFFT, LPF, Arduino 
I. INTRODUCTION 
In Telemedicine communication through audio and video is done to convey or exchange the 
details of a patient with a physician. Using this process the details of a patient can also be 
discussed and analysed. In health information technology Telemedicine plays a major role. 
Telemedicine is basically the combination of medicine & information technology. This involves 
the transmission of medical information electronically. Hence this can be used for conveying the 
condition and status of patient to a doctor if the doctor is not available near the patient. Different 
methods can be applied for this purpose For example: store-and-forward technology, secure 
messaging; e-mailing, 
By monitoring the data received, the doctor is able to understand the patient's condition, to 
diagnose the disease and to take remedial measures. Videoconference is an effective measure in 
this case. 
2. TELE MONITORING 
Tele monitoring is the monitoring patients who are not at the same location as the doctor. For 
example consider a patient with monitoring devices at home. He can easily transmit the results 
of to the doctor through telephone. This assists the patient to perform the initial and basic stage 
of health care by himself. Also this avoids the un necessary travel by the patient. Tele medicine 
is a fast growing field. A new type of Tele monitoring known as primary remote diagnostic 
disease has been introduced in a number of developing countries. In this technique devices are 
used by the doctor for the examination, diagnosis and treatment remotely. This type of treatment 
DOI: 10.5121/hiij.2014.3302 9
Health Informatics-An International Journal (HIIJ) Vol.3, No.3,August 2014 
is mainly used for monitoring the chronic diseases which have been diagnosed already. But this 
new technology can also be applied for monitoring and diagnosing the common diseases such as 
blood pressure, blood glucose, heart rate, weight etc. Frequent monitoring of the patient's 
condition enables the physician to suggest the best and effective course of treatment to the 
patient. 
10 
3. COMPONENTS OF THE SYSTEM 
The system comprises of signal acquisition unit, processing unit and alerting system. The signal 
acquisition unit is the high precision analog front end IC named AD620A from Analog devices. It 
is a low cost, high accuracy instrumentation amplifier that requires only one external resistor to 
set gains from 1 to 1000. The low noise, low input bias current and low power of the AD620 
make it well suited for medical applications such as ECG and non-invasive blood pressure 
monitors. 
For the simulation of the below mentioned image processing algorithm, we use ECG signal 
which is captured from the body in real time. The processing unit is coupled with a PIC micro 
controller which acts as the alerting system. Data processing unit comprises of user PC / Laptop 
loaded with MATLAB. 
4. IMAGE PROCESSING 
The atrial or ventricular regularity or irregularity is a measure of the cardiac rhythm which in turn 
gives an idea about the regularity or irregularity of the heart beat. The consistency of patterns 
between the p waves accesses atrial regularity while the consistency of patterns between R waves 
accesses ventricular regularity. Typical ECG waveform is shown in Fig.No.1 
Fig.No.1: Typical ECG waveform 
Initially eyeballing, the rhythm for regularity was used. Now two more methods are available, 
one is the use of callipers and the other is paper technique. In Callipers two needle points are 
hinged together , one placed at the peak of the P wave or R wave and the other placed at the peak 
of the subsequent P wave or R wave. The needle points are held steadily and the callipers are 
moved down the strip. The needle points of the calliper if fall at the peaks of the subsequent P 
waves shows atrial regularity. If the needle point falls on the peaks other subsequent R waves 
shows ventricular regularity. On the other hand if the needle point do not fall at the peaks of the P 
waves or R waves shows atrial and ventricular irregularities respectively.
Health Informatics-An International Journal (HIIJ) Vol.3, No.3,August 2014 
In paper technique a clean and straight edge of paper is lined up with the peak of the P waves or 
R waves. Three P wave peaks in a row are marked on the edge of the paper and the paper is then 
moved to three subsequent P wave peaks. If the initial marks match with the marks of the 
subsequent P waves that shows atrial regularity and if there is no matching between the marks it 
shows atrial irregularity. Similarly ventricular regularity or irregularity is determined by 
repeating the process with Rwaves. 
11 
5. IMPLEMENTATION ALGORITHM 
Fig.No.2 Block diagram of Algorithm 
Step1: 
Obtain ECG signal from the controller, which is in digital form. The digital values obtained in the 
controller is collected in MATLAB software in real time. 
Step 2: 
Apply smooth filtering process to remove higher frequencies. The most randomly occurring 
signals are eliminated by setting a threshold value. These high frequency signals do not 
contribute any intelligence. It may be due to loose contacts in the electrode or variations in 
impedance matching. 
Step 3: 
To extract vital information from the ecg image apply wavelet decomposition technique.It is done 
by using the function ‘wavedec’. 
Step 4: 
Set a threshold value for identifying the critical condition in heart beat rate using the relation 
(maximum value-mean value) / 2. 
Step 5: 
R peak detection: Done using the function ‘waverec’, inverse of ‘wavedec’, which performs a 
multilevel one dimensional wavelet reconstruction. 
Step6: 
If the adjacent peak distance is greater than a specific value, save the corresponding image to a 
particular location in the computer. 
Step7: 
Calculate heart beat rate.
Health Informatics-An International Journal (HIIJ) Vol.3, No.3,August 2014 
From the final detected peaks any sort of abnormality can be easily detected. In case of 
emergency the PIC controller is triggered and the status of the patient is sent to the doctor as text 
message using a GSM modem as shown in the block diagram given below. 
12 
Fig No 3. Block diagram representation of emergency alerting system 
6. SIMULATION RESULTS 
The setup is as shown in the Fig No.4 
Fig No 4. The system
Health Informatics-A 
An International Journal (HIIJ) Vol.3, No.3,August 2014 
Fig No.6 
6.Screen shot of message on doctor’s handset 
7. EMERGENCY ALERTING 
Fig No 5 Final detected peaks 
LERTING SYSTEM 
The extracted vital intelligence in case of emergency is uploaded to the server. The image which 
is now saved in the server is automatically sent to the mail 
address of the doctors. In case of 
13
Health Informatics-An International Journal (HIIJ) Vol.3, No.3,August 2014 
emergency the trigger is given to PIC controller which will send text message to the doctor 
using GSM modem. From the server the critical ECG image is sent to doctor’s email address. 
For the website creation Microsoft Visual Studio 2010 is the IDE been used .The programming 
language used here is C#. 
14 
Fig No.7.Login page of website 
Fig.No.8.ECG results of various patients.
Health Informatics-An International Journal (HIIJ) Vol.3, No.3,August 2014 
15 
Fig No.9.List of doctors 
Fig.No.10.ECG image of patient displayed
Health Informatics-An International Journal (HIIJ) Vol.3, No.3,August 2014 
16 
8. CONCLUSION 
This system is an initiative of automation in critical health care management. It provides 
continuous monitoring of patient and allows automatic data transfer. The system facilitates 
equitable access to the specialists for all patients regardless of their location. It provides 
opportunities for patients and relatives to contact their specialist. The system can completely 
automate the medical emergency conditions happening in an ICU. 
ACKNOWLEDMENT 
The authors would like to thank their colleagues at Mar Baselios College of Engineering and 
Technology for valuable discussions and feedback, also the reviewers for their 
constructive comments. 
REFERENCES 
[1]Lai Khin Wee, Yeo KeeJiar, EkoSupriyanto “Electrocardiogram Data Capturing System and 
Computerized Digitization using Image Processing Techniques” International Journal of Biology and 
Biomedical Engineering Issue 3, Volume 3, 2009 . 
[2]LjupˇcoHadˇzievski, BoˇskoBojovic´, VladanVukˇcevic´, PetarBeliˇcev, SiniˇsaPavlovic´, 
ZoranaVasiljevic´-Pokrajˇcic´, and MiodragOstojic´’A Novel Mobile Transtelephonic System With 
Synthesized 12-Lead ECG’ IEEE Transaction on Information Technology in Biomedicine, 
Volume 8, 2004 . 
[3]Prof. Dr. Burkhard Stiller ’Mobile Healthcare on Android Devices Communication Systems Group, 
Diploma Thesis, Dept. of Informatics, November 2010 . 
[4]Karen Panetta, Yicong Zhou,SosAgaian,HongweiJia”Non linearunsharp masking for mammogram 
enhancement” , IEEE Transaction on Information Technology in Biomedicine Volume. 15, 
November 2011. 
[5]Al-Naima, F. M., A. H. Ali, and S. S. Mahdi. Data acquisition for myocardial infarction 
classification based on wavelets and Neural Networks. Systems, Signals and Devices, 2008. 
IEEE SSD 2008.5th International Multi-Conference on.IEEE, 2008. 
[6]Chagas, A. V., E. A. B. Da Silva, and J. Nadal. ECG data compression using wavelets. Computers in 
Cardiology 2000.IEEE, 2000.

Weitere ähnliche Inhalte

Was ist angesagt?

Real time heart monitoring system
Real time heart monitoring systemReal time heart monitoring system
Real time heart monitoring systemShashank Kapoor
 
683 690,tesma412,ijeast
683 690,tesma412,ijeast683 690,tesma412,ijeast
683 690,tesma412,ijeastArhamSheikh1
 
The research of_portable_ecg_monitoring_system_with_usb_host_interface
The research of_portable_ecg_monitoring_system_with_usb_host_interfaceThe research of_portable_ecg_monitoring_system_with_usb_host_interface
The research of_portable_ecg_monitoring_system_with_usb_host_interfaceArhamSheikh1
 
Portable ECG Monitoring System using Lilypad And Mobile Platform-PandaBoard
Portable ECG Monitoring System using Lilypad And Mobile Platform-PandaBoardPortable ECG Monitoring System using Lilypad And Mobile Platform-PandaBoard
Portable ECG Monitoring System using Lilypad And Mobile Platform-PandaBoardIJSRD
 
Acquiring Ecg Signals And Analysing For Different Heart Ailments
Acquiring Ecg Signals And Analysing For Different Heart AilmentsAcquiring Ecg Signals And Analysing For Different Heart Ailments
Acquiring Ecg Signals And Analysing For Different Heart AilmentsIJERA Editor
 
Force sensitive resistance based heart beat
Force sensitive resistance based heart beatForce sensitive resistance based heart beat
Force sensitive resistance based heart beatijistjournal
 
The development of a wireless LCP-based intracranial pressure sensor for trau...
The development of a wireless LCP-based intracranial pressure sensor for trau...The development of a wireless LCP-based intracranial pressure sensor for trau...
The development of a wireless LCP-based intracranial pressure sensor for trau...IJECEIAES
 
Internet of Things IoT Based Healthcare Monitoring System using NodeMCU and A...
Internet of Things IoT Based Healthcare Monitoring System using NodeMCU and A...Internet of Things IoT Based Healthcare Monitoring System using NodeMCU and A...
Internet of Things IoT Based Healthcare Monitoring System using NodeMCU and A...ijtsrd
 
Transmission of arm based real time ecg for monitoring remotely located patient
Transmission of arm based real time ecg for monitoring remotely located patientTransmission of arm based real time ecg for monitoring remotely located patient
Transmission of arm based real time ecg for monitoring remotely located patienteSAT Publishing House
 
A simple portable ecg monitor with iot
A simple portable ecg monitor with iotA simple portable ecg monitor with iot
A simple portable ecg monitor with iotArhamSheikh1
 
An Implementation of Embedded System in Patient Monitoring System
An Implementation of Embedded System in Patient Monitoring SystemAn Implementation of Embedded System in Patient Monitoring System
An Implementation of Embedded System in Patient Monitoring Systemijsrd.com
 
IoT Based Patient Monitoring
IoT Based Patient MonitoringIoT Based Patient Monitoring
IoT Based Patient Monitoringijtsrd
 
Remote patient monitoring system
Remote patient monitoring system Remote patient monitoring system
Remote patient monitoring system Rahul Singh
 
A Wireless Methodology of Heart Attack Detection
A Wireless Methodology of Heart Attack DetectionA Wireless Methodology of Heart Attack Detection
A Wireless Methodology of Heart Attack Detectionijsrd.com
 
ECG SIGNAL ACQUISITION, FEATURE EXTRACTION AND HRV ANALYSIS USING BIOMEDICAL ...
ECG SIGNAL ACQUISITION, FEATURE EXTRACTION AND HRV ANALYSIS USING BIOMEDICAL ...ECG SIGNAL ACQUISITION, FEATURE EXTRACTION AND HRV ANALYSIS USING BIOMEDICAL ...
ECG SIGNAL ACQUISITION, FEATURE EXTRACTION AND HRV ANALYSIS USING BIOMEDICAL ...IAEME Publication
 

Was ist angesagt? (19)

Real time heart monitoring system
Real time heart monitoring systemReal time heart monitoring system
Real time heart monitoring system
 
683 690,tesma412,ijeast
683 690,tesma412,ijeast683 690,tesma412,ijeast
683 690,tesma412,ijeast
 
1475 925 x-13-160
1475 925 x-13-1601475 925 x-13-160
1475 925 x-13-160
 
The research of_portable_ecg_monitoring_system_with_usb_host_interface
The research of_portable_ecg_monitoring_system_with_usb_host_interfaceThe research of_portable_ecg_monitoring_system_with_usb_host_interface
The research of_portable_ecg_monitoring_system_with_usb_host_interface
 
Portable ECG Monitoring System using Lilypad And Mobile Platform-PandaBoard
Portable ECG Monitoring System using Lilypad And Mobile Platform-PandaBoardPortable ECG Monitoring System using Lilypad And Mobile Platform-PandaBoard
Portable ECG Monitoring System using Lilypad And Mobile Platform-PandaBoard
 
Acquiring Ecg Signals And Analysing For Different Heart Ailments
Acquiring Ecg Signals And Analysing For Different Heart AilmentsAcquiring Ecg Signals And Analysing For Different Heart Ailments
Acquiring Ecg Signals And Analysing For Different Heart Ailments
 
Eg24842846
Eg24842846Eg24842846
Eg24842846
 
Force sensitive resistance based heart beat
Force sensitive resistance based heart beatForce sensitive resistance based heart beat
Force sensitive resistance based heart beat
 
The development of a wireless LCP-based intracranial pressure sensor for trau...
The development of a wireless LCP-based intracranial pressure sensor for trau...The development of a wireless LCP-based intracranial pressure sensor for trau...
The development of a wireless LCP-based intracranial pressure sensor for trau...
 
Health Monitoring
Health MonitoringHealth Monitoring
Health Monitoring
 
Internet of Things IoT Based Healthcare Monitoring System using NodeMCU and A...
Internet of Things IoT Based Healthcare Monitoring System using NodeMCU and A...Internet of Things IoT Based Healthcare Monitoring System using NodeMCU and A...
Internet of Things IoT Based Healthcare Monitoring System using NodeMCU and A...
 
Transmission of arm based real time ecg for monitoring remotely located patient
Transmission of arm based real time ecg for monitoring remotely located patientTransmission of arm based real time ecg for monitoring remotely located patient
Transmission of arm based real time ecg for monitoring remotely located patient
 
A simple portable ecg monitor with iot
A simple portable ecg monitor with iotA simple portable ecg monitor with iot
A simple portable ecg monitor with iot
 
An Implementation of Embedded System in Patient Monitoring System
An Implementation of Embedded System in Patient Monitoring SystemAn Implementation of Embedded System in Patient Monitoring System
An Implementation of Embedded System in Patient Monitoring System
 
Sensors 21-02777
Sensors 21-02777Sensors 21-02777
Sensors 21-02777
 
IoT Based Patient Monitoring
IoT Based Patient MonitoringIoT Based Patient Monitoring
IoT Based Patient Monitoring
 
Remote patient monitoring system
Remote patient monitoring system Remote patient monitoring system
Remote patient monitoring system
 
A Wireless Methodology of Heart Attack Detection
A Wireless Methodology of Heart Attack DetectionA Wireless Methodology of Heart Attack Detection
A Wireless Methodology of Heart Attack Detection
 
ECG SIGNAL ACQUISITION, FEATURE EXTRACTION AND HRV ANALYSIS USING BIOMEDICAL ...
ECG SIGNAL ACQUISITION, FEATURE EXTRACTION AND HRV ANALYSIS USING BIOMEDICAL ...ECG SIGNAL ACQUISITION, FEATURE EXTRACTION AND HRV ANALYSIS USING BIOMEDICAL ...
ECG SIGNAL ACQUISITION, FEATURE EXTRACTION AND HRV ANALYSIS USING BIOMEDICAL ...
 

Andere mochten auch

Wisdom letter2
Wisdom letter2Wisdom letter2
Wisdom letter2fayaz248
 
Lesson 3 mobility
Lesson 3 mobilityLesson 3 mobility
Lesson 3 mobilitytonyabur
 
Presentazione flexkom personalizzata
Presentazione flexkom personalizzataPresentazione flexkom personalizzata
Presentazione flexkom personalizzataVincenzo Cascio
 
Presentazione libertagiaitalia
Presentazione libertagiaitaliaPresentazione libertagiaitalia
Presentazione libertagiaitaliaVincenzo Cascio
 
Concentrado de arraigo.
Concentrado de arraigo.Concentrado de arraigo.
Concentrado de arraigo.Andres Mendes
 
მოსწავლეთა ნამუშევრები
მოსწავლეთა ნამუშევრებიმოსწავლეთა ნამუშევრები
მოსწავლეთა ნამუშევრებიteagaganidze
 
Aprender a leer y a escribir
Aprender a leer y a escribirAprender a leer y a escribir
Aprender a leer y a escribirMarieta1308
 
Aantallen linkedin november 2012
Aantallen linkedin november 2012Aantallen linkedin november 2012
Aantallen linkedin november 2012Bright Mind Media
 
A FRAMEWORK FOR EXTRACTING AND MODELING HIPAA PRIVACY RULES FOR HEALTHCARE AP...
A FRAMEWORK FOR EXTRACTING AND MODELING HIPAA PRIVACY RULES FOR HEALTHCARE AP...A FRAMEWORK FOR EXTRACTING AND MODELING HIPAA PRIVACY RULES FOR HEALTHCARE AP...
A FRAMEWORK FOR EXTRACTING AND MODELING HIPAA PRIVACY RULES FOR HEALTHCARE AP...hiij
 

Andere mochten auch (19)

Matericlass
MatericlassMatericlass
Matericlass
 
Wisdom letter2
Wisdom letter2Wisdom letter2
Wisdom letter2
 
Lesson 3 mobility
Lesson 3 mobilityLesson 3 mobility
Lesson 3 mobility
 
Presentazione flexkom personalizzata
Presentazione flexkom personalizzataPresentazione flexkom personalizzata
Presentazione flexkom personalizzata
 
Ok 3 rep data2
Ok 3 rep  data2Ok 3 rep  data2
Ok 3 rep data2
 
Ok 8 perkalian
Ok 8 perkalianOk 8 perkalian
Ok 8 perkalian
 
Pertemuan II Function
Pertemuan II FunctionPertemuan II Function
Pertemuan II Function
 
Pointer
PointerPointer
Pointer
 
Presentazione libertagiaitalia
Presentazione libertagiaitaliaPresentazione libertagiaitalia
Presentazione libertagiaitalia
 
Csiro miicrc agile
Csiro miicrc agileCsiro miicrc agile
Csiro miicrc agile
 
Concentrado de arraigo.
Concentrado de arraigo.Concentrado de arraigo.
Concentrado de arraigo.
 
Listrik1
Listrik1Listrik1
Listrik1
 
Pertemuan IV Teori
Pertemuan IV TeoriPertemuan IV Teori
Pertemuan IV Teori
 
Listrik5
Listrik5Listrik5
Listrik5
 
6666666666666
66666666666666666666666666
6666666666666
 
მოსწავლეთა ნამუშევრები
მოსწავლეთა ნამუშევრებიმოსწავლეთა ნამუშევრები
მოსწავლეთა ნამუშევრები
 
Aprender a leer y a escribir
Aprender a leer y a escribirAprender a leer y a escribir
Aprender a leer y a escribir
 
Aantallen linkedin november 2012
Aantallen linkedin november 2012Aantallen linkedin november 2012
Aantallen linkedin november 2012
 
A FRAMEWORK FOR EXTRACTING AND MODELING HIPAA PRIVACY RULES FOR HEALTHCARE AP...
A FRAMEWORK FOR EXTRACTING AND MODELING HIPAA PRIVACY RULES FOR HEALTHCARE AP...A FRAMEWORK FOR EXTRACTING AND MODELING HIPAA PRIVACY RULES FOR HEALTHCARE AP...
A FRAMEWORK FOR EXTRACTING AND MODELING HIPAA PRIVACY RULES FOR HEALTHCARE AP...
 

Ähnlich wie Smart hospital technology

SMART HOSPITAL TECHNOLOGY
SMART HOSPITAL TECHNOLOGYSMART HOSPITAL TECHNOLOGY
SMART HOSPITAL TECHNOLOGYhiij
 
Electrocardiogram signal processing algorithm on microcontroller using wavele...
Electrocardiogram signal processing algorithm on microcontroller using wavele...Electrocardiogram signal processing algorithm on microcontroller using wavele...
Electrocardiogram signal processing algorithm on microcontroller using wavele...IJECEIAES
 
Real Time ECG and Saline Level Monitoring System Using Arduino UNO Processor
Real Time ECG and Saline Level Monitoring System Using Arduino UNO ProcessorReal Time ECG and Saline Level Monitoring System Using Arduino UNO Processor
Real Time ECG and Saline Level Monitoring System Using Arduino UNO ProcessorAssociate Professor in VSB Coimbatore
 
Wireless Medical Surveillance System Using Raspberry Pi and X-Bee By. Nikhil ...
Wireless Medical Surveillance System Using Raspberry Pi and X-Bee By. Nikhil ...Wireless Medical Surveillance System Using Raspberry Pi and X-Bee By. Nikhil ...
Wireless Medical Surveillance System Using Raspberry Pi and X-Bee By. Nikhil ...nikhilpatewar
 
IRJET- Patient’s Health Parameters Monitoring through IoT
IRJET-  	  Patient’s Health Parameters Monitoring through IoTIRJET-  	  Patient’s Health Parameters Monitoring through IoT
IRJET- Patient’s Health Parameters Monitoring through IoTIRJET Journal
 
A Real Time Electrocardiogram (ECG) Device for Cardiac Patients
A Real Time Electrocardiogram (ECG) Device for Cardiac PatientsA Real Time Electrocardiogram (ECG) Device for Cardiac Patients
A Real Time Electrocardiogram (ECG) Device for Cardiac PatientsIJERD Editor
 
IRJET- Design and Implementation of Health Monitoring System
IRJET-  	  Design and Implementation of Health Monitoring SystemIRJET-  	  Design and Implementation of Health Monitoring System
IRJET- Design and Implementation of Health Monitoring SystemIRJET Journal
 
Implementation Of Real Time IoT Based Health monitoring system
Implementation Of Real Time IoT Based Health monitoring systemImplementation Of Real Time IoT Based Health monitoring system
Implementation Of Real Time IoT Based Health monitoring systemkchakrireddy
 
03 cjece-2018-0001
03 cjece-2018-000103 cjece-2018-0001
03 cjece-2018-0001Stefan Oniga
 
Portable Real Time Cardiac Activity Monitoring System
Portable  Real Time Cardiac Activity Monitoring SystemPortable  Real Time Cardiac Activity Monitoring System
Portable Real Time Cardiac Activity Monitoring SystemIRJET Journal
 
IRJET- Review Paper on Patient Health Monitoring System using Can Protocol
IRJET- Review Paper on Patient Health Monitoring System using Can ProtocolIRJET- Review Paper on Patient Health Monitoring System using Can Protocol
IRJET- Review Paper on Patient Health Monitoring System using Can ProtocolIRJET Journal
 
Intelligent Healthcare Monitoring in IoT
Intelligent Healthcare Monitoring in IoTIntelligent Healthcare Monitoring in IoT
Intelligent Healthcare Monitoring in IoTIJAEMSJORNAL
 
Wireless Telemetry System
Wireless Telemetry SystemWireless Telemetry System
Wireless Telemetry Systemijsrd.com
 
IRJET - ECG based Cardiac Arrhythmia Detection using a Deep Neural Network
IRJET - ECG based Cardiac Arrhythmia Detection using a Deep Neural NetworkIRJET - ECG based Cardiac Arrhythmia Detection using a Deep Neural Network
IRJET - ECG based Cardiac Arrhythmia Detection using a Deep Neural NetworkIRJET Journal
 
Welcome to International Journal of Engineering Research and Development (IJERD)
Welcome to International Journal of Engineering Research and Development (IJERD)Welcome to International Journal of Engineering Research and Development (IJERD)
Welcome to International Journal of Engineering Research and Development (IJERD)IJERD Editor
 
Android Based Patient Health Monitoring System
Android Based Patient Health Monitoring SystemAndroid Based Patient Health Monitoring System
Android Based Patient Health Monitoring SystemIRJET Journal
 

Ähnlich wie Smart hospital technology (20)

SMART HOSPITAL TECHNOLOGY
SMART HOSPITAL TECHNOLOGYSMART HOSPITAL TECHNOLOGY
SMART HOSPITAL TECHNOLOGY
 
Electrocardiogram signal processing algorithm on microcontroller using wavele...
Electrocardiogram signal processing algorithm on microcontroller using wavele...Electrocardiogram signal processing algorithm on microcontroller using wavele...
Electrocardiogram signal processing algorithm on microcontroller using wavele...
 
IJET-V3I1P26
IJET-V3I1P26IJET-V3I1P26
IJET-V3I1P26
 
Real Time ECG and Saline Level Monitoring System Using Arduino UNO Processor
Real Time ECG and Saline Level Monitoring System Using Arduino UNO ProcessorReal Time ECG and Saline Level Monitoring System Using Arduino UNO Processor
Real Time ECG and Saline Level Monitoring System Using Arduino UNO Processor
 
Wireless Medical Surveillance System Using Raspberry Pi and X-Bee By. Nikhil ...
Wireless Medical Surveillance System Using Raspberry Pi and X-Bee By. Nikhil ...Wireless Medical Surveillance System Using Raspberry Pi and X-Bee By. Nikhil ...
Wireless Medical Surveillance System Using Raspberry Pi and X-Bee By. Nikhil ...
 
IRJET- Patient’s Health Parameters Monitoring through IoT
IRJET-  	  Patient’s Health Parameters Monitoring through IoTIRJET-  	  Patient’s Health Parameters Monitoring through IoT
IRJET- Patient’s Health Parameters Monitoring through IoT
 
Cj35483486
Cj35483486Cj35483486
Cj35483486
 
A Real Time Electrocardiogram (ECG) Device for Cardiac Patients
A Real Time Electrocardiogram (ECG) Device for Cardiac PatientsA Real Time Electrocardiogram (ECG) Device for Cardiac Patients
A Real Time Electrocardiogram (ECG) Device for Cardiac Patients
 
IRJET- Design and Implementation of Health Monitoring System
IRJET-  	  Design and Implementation of Health Monitoring SystemIRJET-  	  Design and Implementation of Health Monitoring System
IRJET- Design and Implementation of Health Monitoring System
 
Implementation Of Real Time IoT Based Health monitoring system
Implementation Of Real Time IoT Based Health monitoring systemImplementation Of Real Time IoT Based Health monitoring system
Implementation Of Real Time IoT Based Health monitoring system
 
03 cjece-2018-0001
03 cjece-2018-000103 cjece-2018-0001
03 cjece-2018-0001
 
Portable Real Time Cardiac Activity Monitoring System
Portable  Real Time Cardiac Activity Monitoring SystemPortable  Real Time Cardiac Activity Monitoring System
Portable Real Time Cardiac Activity Monitoring System
 
50620130101003
5062013010100350620130101003
50620130101003
 
Multi-Parameter Measurement of ICU Patient Using GSM and Embedded Technology
Multi-Parameter Measurement of ICU Patient Using GSM and Embedded TechnologyMulti-Parameter Measurement of ICU Patient Using GSM and Embedded Technology
Multi-Parameter Measurement of ICU Patient Using GSM and Embedded Technology
 
IRJET- Review Paper on Patient Health Monitoring System using Can Protocol
IRJET- Review Paper on Patient Health Monitoring System using Can ProtocolIRJET- Review Paper on Patient Health Monitoring System using Can Protocol
IRJET- Review Paper on Patient Health Monitoring System using Can Protocol
 
Intelligent Healthcare Monitoring in IoT
Intelligent Healthcare Monitoring in IoTIntelligent Healthcare Monitoring in IoT
Intelligent Healthcare Monitoring in IoT
 
Wireless Telemetry System
Wireless Telemetry SystemWireless Telemetry System
Wireless Telemetry System
 
IRJET - ECG based Cardiac Arrhythmia Detection using a Deep Neural Network
IRJET - ECG based Cardiac Arrhythmia Detection using a Deep Neural NetworkIRJET - ECG based Cardiac Arrhythmia Detection using a Deep Neural Network
IRJET - ECG based Cardiac Arrhythmia Detection using a Deep Neural Network
 
Welcome to International Journal of Engineering Research and Development (IJERD)
Welcome to International Journal of Engineering Research and Development (IJERD)Welcome to International Journal of Engineering Research and Development (IJERD)
Welcome to International Journal of Engineering Research and Development (IJERD)
 
Android Based Patient Health Monitoring System
Android Based Patient Health Monitoring SystemAndroid Based Patient Health Monitoring System
Android Based Patient Health Monitoring System
 

Mehr von hiij

Health Informatics - An International Journal (HIIJ)
Health Informatics - An International Journal (HIIJ)Health Informatics - An International Journal (HIIJ)
Health Informatics - An International Journal (HIIJ)hiij
 
Health Informatics - An International Journal (HIIJ)
Health Informatics - An International Journal (HIIJ)Health Informatics - An International Journal (HIIJ)
Health Informatics - An International Journal (HIIJ)hiij
 
Health Informatics - An International Journal (HIIJ)
Health Informatics - An International Journal (HIIJ)Health Informatics - An International Journal (HIIJ)
Health Informatics - An International Journal (HIIJ)hiij
 
Health Informatics - An International Journal (HIIJ)
Health Informatics - An International Journal (HIIJ)Health Informatics - An International Journal (HIIJ)
Health Informatics - An International Journal (HIIJ)hiij
 
BRIEF COMMENTARY: USING A LOGIC MODEL TO INTEGRATE PUBLIC HEALTH INFORMATICS ...
BRIEF COMMENTARY: USING A LOGIC MODEL TO INTEGRATE PUBLIC HEALTH INFORMATICS ...BRIEF COMMENTARY: USING A LOGIC MODEL TO INTEGRATE PUBLIC HEALTH INFORMATICS ...
BRIEF COMMENTARY: USING A LOGIC MODEL TO INTEGRATE PUBLIC HEALTH INFORMATICS ...hiij
 
Health Informatics - An International Journal (HIIJ)
Health Informatics - An International Journal (HIIJ)Health Informatics - An International Journal (HIIJ)
Health Informatics - An International Journal (HIIJ)hiij
 
AUTOMATIC AND NON-INVASIVE CONTINUOUS GLUCOSE MONITORING IN PAEDIATRIC PATIENTS
AUTOMATIC AND NON-INVASIVE CONTINUOUS GLUCOSE MONITORING IN PAEDIATRIC PATIENTSAUTOMATIC AND NON-INVASIVE CONTINUOUS GLUCOSE MONITORING IN PAEDIATRIC PATIENTS
AUTOMATIC AND NON-INVASIVE CONTINUOUS GLUCOSE MONITORING IN PAEDIATRIC PATIENTShiij
 
INTEGRATING MACHINE LEARNING IN CLINICAL DECISION SUPPORT SYSTEMS
INTEGRATING MACHINE LEARNING IN CLINICAL DECISION SUPPORT SYSTEMSINTEGRATING MACHINE LEARNING IN CLINICAL DECISION SUPPORT SYSTEMS
INTEGRATING MACHINE LEARNING IN CLINICAL DECISION SUPPORT SYSTEMShiij
 
BRIEF COMMENTARY: USING A LOGIC MODEL TO INTEGRATE PUBLIC HEALTH INFORMATICS ...
BRIEF COMMENTARY: USING A LOGIC MODEL TO INTEGRATE PUBLIC HEALTH INFORMATICS ...BRIEF COMMENTARY: USING A LOGIC MODEL TO INTEGRATE PUBLIC HEALTH INFORMATICS ...
BRIEF COMMENTARY: USING A LOGIC MODEL TO INTEGRATE PUBLIC HEALTH INFORMATICS ...hiij
 
INTEGRATING MACHINE LEARNING IN CLINICAL DECISION SUPPORT SYSTEMS
INTEGRATING MACHINE LEARNING IN CLINICAL DECISION SUPPORT SYSTEMSINTEGRATING MACHINE LEARNING IN CLINICAL DECISION SUPPORT SYSTEMS
INTEGRATING MACHINE LEARNING IN CLINICAL DECISION SUPPORT SYSTEMShiij
 
Health Informatics - An International Journal (HIIJ)
Health Informatics - An International Journal (HIIJ)Health Informatics - An International Journal (HIIJ)
Health Informatics - An International Journal (HIIJ)hiij
 
The Proposed Guidelines for Cloud Computing Migration for South African Rural...
The Proposed Guidelines for Cloud Computing Migration for South African Rural...The Proposed Guidelines for Cloud Computing Migration for South African Rural...
The Proposed Guidelines for Cloud Computing Migration for South African Rural...hiij
 
SUPPORTING LARGE-SCALE NUTRITION ANALYSIS BASED ON DIETARY SURVEY DATA
SUPPORTING LARGE-SCALE NUTRITION ANALYSIS BASED ON DIETARY SURVEY DATASUPPORTING LARGE-SCALE NUTRITION ANALYSIS BASED ON DIETARY SURVEY DATA
SUPPORTING LARGE-SCALE NUTRITION ANALYSIS BASED ON DIETARY SURVEY DATAhiij
 
AN EHEALTH ADOPTION FRAMEWORK FOR DEVELOPING COUNTRIES: A SYSTEMATIC REVIEW
AN EHEALTH ADOPTION FRAMEWORK FOR DEVELOPING COUNTRIES: A SYSTEMATIC REVIEWAN EHEALTH ADOPTION FRAMEWORK FOR DEVELOPING COUNTRIES: A SYSTEMATIC REVIEW
AN EHEALTH ADOPTION FRAMEWORK FOR DEVELOPING COUNTRIES: A SYSTEMATIC REVIEWhiij
 
GENDER DISPARITYOF TUBERCULOSISBURDENIN LOW-AND MIDDLE-INCOME COUNTRIES: A SY...
GENDER DISPARITYOF TUBERCULOSISBURDENIN LOW-AND MIDDLE-INCOME COUNTRIES: A SY...GENDER DISPARITYOF TUBERCULOSISBURDENIN LOW-AND MIDDLE-INCOME COUNTRIES: A SY...
GENDER DISPARITYOF TUBERCULOSISBURDENIN LOW-AND MIDDLE-INCOME COUNTRIES: A SY...hiij
 
BRIEF COMMUNICATIONS DATA HYGIENE: IMPORTANT STEP IN DECISIONMAKING WITH IMPL...
BRIEF COMMUNICATIONS DATA HYGIENE: IMPORTANT STEP IN DECISIONMAKING WITH IMPL...BRIEF COMMUNICATIONS DATA HYGIENE: IMPORTANT STEP IN DECISIONMAKING WITH IMPL...
BRIEF COMMUNICATIONS DATA HYGIENE: IMPORTANT STEP IN DECISIONMAKING WITH IMPL...hiij
 
CHINESE PHARMACISTS LAW MODIFICATION, HOW TO PROTECT PATIENTS‘INTERESTS?
CHINESE PHARMACISTS LAW MODIFICATION, HOW TO PROTECT PATIENTS‘INTERESTS?CHINESE PHARMACISTS LAW MODIFICATION, HOW TO PROTECT PATIENTS‘INTERESTS?
CHINESE PHARMACISTS LAW MODIFICATION, HOW TO PROTECT PATIENTS‘INTERESTS?hiij
 
GENDER DISPARITYOF TUBERCULOSISBURDENIN LOW-AND MIDDLE-INCOME COUNTRIES: A SY...
GENDER DISPARITYOF TUBERCULOSISBURDENIN LOW-AND MIDDLE-INCOME COUNTRIES: A SY...GENDER DISPARITYOF TUBERCULOSISBURDENIN LOW-AND MIDDLE-INCOME COUNTRIES: A SY...
GENDER DISPARITYOF TUBERCULOSISBURDENIN LOW-AND MIDDLE-INCOME COUNTRIES: A SY...hiij
 
PERSONALIZED MEDICINE SUPPORT SYSTEM: RESOLVING CONFLICT IN ALLOCATION TO RIS...
PERSONALIZED MEDICINE SUPPORT SYSTEM: RESOLVING CONFLICT IN ALLOCATION TO RIS...PERSONALIZED MEDICINE SUPPORT SYSTEM: RESOLVING CONFLICT IN ALLOCATION TO RIS...
PERSONALIZED MEDICINE SUPPORT SYSTEM: RESOLVING CONFLICT IN ALLOCATION TO RIS...hiij
 
BRIEF COMMUNICATIONS DATA HYGIENE: IMPORTANT STEP IN DECISIONMAKING WITH IMPL...
BRIEF COMMUNICATIONS DATA HYGIENE: IMPORTANT STEP IN DECISIONMAKING WITH IMPL...BRIEF COMMUNICATIONS DATA HYGIENE: IMPORTANT STEP IN DECISIONMAKING WITH IMPL...
BRIEF COMMUNICATIONS DATA HYGIENE: IMPORTANT STEP IN DECISIONMAKING WITH IMPL...hiij
 

Mehr von hiij (20)

Health Informatics - An International Journal (HIIJ)
Health Informatics - An International Journal (HIIJ)Health Informatics - An International Journal (HIIJ)
Health Informatics - An International Journal (HIIJ)
 
Health Informatics - An International Journal (HIIJ)
Health Informatics - An International Journal (HIIJ)Health Informatics - An International Journal (HIIJ)
Health Informatics - An International Journal (HIIJ)
 
Health Informatics - An International Journal (HIIJ)
Health Informatics - An International Journal (HIIJ)Health Informatics - An International Journal (HIIJ)
Health Informatics - An International Journal (HIIJ)
 
Health Informatics - An International Journal (HIIJ)
Health Informatics - An International Journal (HIIJ)Health Informatics - An International Journal (HIIJ)
Health Informatics - An International Journal (HIIJ)
 
BRIEF COMMENTARY: USING A LOGIC MODEL TO INTEGRATE PUBLIC HEALTH INFORMATICS ...
BRIEF COMMENTARY: USING A LOGIC MODEL TO INTEGRATE PUBLIC HEALTH INFORMATICS ...BRIEF COMMENTARY: USING A LOGIC MODEL TO INTEGRATE PUBLIC HEALTH INFORMATICS ...
BRIEF COMMENTARY: USING A LOGIC MODEL TO INTEGRATE PUBLIC HEALTH INFORMATICS ...
 
Health Informatics - An International Journal (HIIJ)
Health Informatics - An International Journal (HIIJ)Health Informatics - An International Journal (HIIJ)
Health Informatics - An International Journal (HIIJ)
 
AUTOMATIC AND NON-INVASIVE CONTINUOUS GLUCOSE MONITORING IN PAEDIATRIC PATIENTS
AUTOMATIC AND NON-INVASIVE CONTINUOUS GLUCOSE MONITORING IN PAEDIATRIC PATIENTSAUTOMATIC AND NON-INVASIVE CONTINUOUS GLUCOSE MONITORING IN PAEDIATRIC PATIENTS
AUTOMATIC AND NON-INVASIVE CONTINUOUS GLUCOSE MONITORING IN PAEDIATRIC PATIENTS
 
INTEGRATING MACHINE LEARNING IN CLINICAL DECISION SUPPORT SYSTEMS
INTEGRATING MACHINE LEARNING IN CLINICAL DECISION SUPPORT SYSTEMSINTEGRATING MACHINE LEARNING IN CLINICAL DECISION SUPPORT SYSTEMS
INTEGRATING MACHINE LEARNING IN CLINICAL DECISION SUPPORT SYSTEMS
 
BRIEF COMMENTARY: USING A LOGIC MODEL TO INTEGRATE PUBLIC HEALTH INFORMATICS ...
BRIEF COMMENTARY: USING A LOGIC MODEL TO INTEGRATE PUBLIC HEALTH INFORMATICS ...BRIEF COMMENTARY: USING A LOGIC MODEL TO INTEGRATE PUBLIC HEALTH INFORMATICS ...
BRIEF COMMENTARY: USING A LOGIC MODEL TO INTEGRATE PUBLIC HEALTH INFORMATICS ...
 
INTEGRATING MACHINE LEARNING IN CLINICAL DECISION SUPPORT SYSTEMS
INTEGRATING MACHINE LEARNING IN CLINICAL DECISION SUPPORT SYSTEMSINTEGRATING MACHINE LEARNING IN CLINICAL DECISION SUPPORT SYSTEMS
INTEGRATING MACHINE LEARNING IN CLINICAL DECISION SUPPORT SYSTEMS
 
Health Informatics - An International Journal (HIIJ)
Health Informatics - An International Journal (HIIJ)Health Informatics - An International Journal (HIIJ)
Health Informatics - An International Journal (HIIJ)
 
The Proposed Guidelines for Cloud Computing Migration for South African Rural...
The Proposed Guidelines for Cloud Computing Migration for South African Rural...The Proposed Guidelines for Cloud Computing Migration for South African Rural...
The Proposed Guidelines for Cloud Computing Migration for South African Rural...
 
SUPPORTING LARGE-SCALE NUTRITION ANALYSIS BASED ON DIETARY SURVEY DATA
SUPPORTING LARGE-SCALE NUTRITION ANALYSIS BASED ON DIETARY SURVEY DATASUPPORTING LARGE-SCALE NUTRITION ANALYSIS BASED ON DIETARY SURVEY DATA
SUPPORTING LARGE-SCALE NUTRITION ANALYSIS BASED ON DIETARY SURVEY DATA
 
AN EHEALTH ADOPTION FRAMEWORK FOR DEVELOPING COUNTRIES: A SYSTEMATIC REVIEW
AN EHEALTH ADOPTION FRAMEWORK FOR DEVELOPING COUNTRIES: A SYSTEMATIC REVIEWAN EHEALTH ADOPTION FRAMEWORK FOR DEVELOPING COUNTRIES: A SYSTEMATIC REVIEW
AN EHEALTH ADOPTION FRAMEWORK FOR DEVELOPING COUNTRIES: A SYSTEMATIC REVIEW
 
GENDER DISPARITYOF TUBERCULOSISBURDENIN LOW-AND MIDDLE-INCOME COUNTRIES: A SY...
GENDER DISPARITYOF TUBERCULOSISBURDENIN LOW-AND MIDDLE-INCOME COUNTRIES: A SY...GENDER DISPARITYOF TUBERCULOSISBURDENIN LOW-AND MIDDLE-INCOME COUNTRIES: A SY...
GENDER DISPARITYOF TUBERCULOSISBURDENIN LOW-AND MIDDLE-INCOME COUNTRIES: A SY...
 
BRIEF COMMUNICATIONS DATA HYGIENE: IMPORTANT STEP IN DECISIONMAKING WITH IMPL...
BRIEF COMMUNICATIONS DATA HYGIENE: IMPORTANT STEP IN DECISIONMAKING WITH IMPL...BRIEF COMMUNICATIONS DATA HYGIENE: IMPORTANT STEP IN DECISIONMAKING WITH IMPL...
BRIEF COMMUNICATIONS DATA HYGIENE: IMPORTANT STEP IN DECISIONMAKING WITH IMPL...
 
CHINESE PHARMACISTS LAW MODIFICATION, HOW TO PROTECT PATIENTS‘INTERESTS?
CHINESE PHARMACISTS LAW MODIFICATION, HOW TO PROTECT PATIENTS‘INTERESTS?CHINESE PHARMACISTS LAW MODIFICATION, HOW TO PROTECT PATIENTS‘INTERESTS?
CHINESE PHARMACISTS LAW MODIFICATION, HOW TO PROTECT PATIENTS‘INTERESTS?
 
GENDER DISPARITYOF TUBERCULOSISBURDENIN LOW-AND MIDDLE-INCOME COUNTRIES: A SY...
GENDER DISPARITYOF TUBERCULOSISBURDENIN LOW-AND MIDDLE-INCOME COUNTRIES: A SY...GENDER DISPARITYOF TUBERCULOSISBURDENIN LOW-AND MIDDLE-INCOME COUNTRIES: A SY...
GENDER DISPARITYOF TUBERCULOSISBURDENIN LOW-AND MIDDLE-INCOME COUNTRIES: A SY...
 
PERSONALIZED MEDICINE SUPPORT SYSTEM: RESOLVING CONFLICT IN ALLOCATION TO RIS...
PERSONALIZED MEDICINE SUPPORT SYSTEM: RESOLVING CONFLICT IN ALLOCATION TO RIS...PERSONALIZED MEDICINE SUPPORT SYSTEM: RESOLVING CONFLICT IN ALLOCATION TO RIS...
PERSONALIZED MEDICINE SUPPORT SYSTEM: RESOLVING CONFLICT IN ALLOCATION TO RIS...
 
BRIEF COMMUNICATIONS DATA HYGIENE: IMPORTANT STEP IN DECISIONMAKING WITH IMPL...
BRIEF COMMUNICATIONS DATA HYGIENE: IMPORTANT STEP IN DECISIONMAKING WITH IMPL...BRIEF COMMUNICATIONS DATA HYGIENE: IMPORTANT STEP IN DECISIONMAKING WITH IMPL...
BRIEF COMMUNICATIONS DATA HYGIENE: IMPORTANT STEP IN DECISIONMAKING WITH IMPL...
 

Kürzlich hochgeladen

Polkadot JAM Slides - Token2049 - By Dr. Gavin Wood
Polkadot JAM Slides - Token2049 - By Dr. Gavin WoodPolkadot JAM Slides - Token2049 - By Dr. Gavin Wood
Polkadot JAM Slides - Token2049 - By Dr. Gavin WoodJuan lago vázquez
 
Automating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps ScriptAutomating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps Scriptwesley chun
 
Powerful Google developer tools for immediate impact! (2023-24 C)
Powerful Google developer tools for immediate impact! (2023-24 C)Powerful Google developer tools for immediate impact! (2023-24 C)
Powerful Google developer tools for immediate impact! (2023-24 C)wesley chun
 
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...DianaGray10
 
Apidays Singapore 2024 - Scalable LLM APIs for AI and Generative AI Applicati...
Apidays Singapore 2024 - Scalable LLM APIs for AI and Generative AI Applicati...Apidays Singapore 2024 - Scalable LLM APIs for AI and Generative AI Applicati...
Apidays Singapore 2024 - Scalable LLM APIs for AI and Generative AI Applicati...apidays
 
EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER
EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWEREMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER
EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWERMadyBayot
 
MS Copilot expands with MS Graph connectors
MS Copilot expands with MS Graph connectorsMS Copilot expands with MS Graph connectors
MS Copilot expands with MS Graph connectorsNanddeep Nachan
 
Apidays New York 2024 - The value of a flexible API Management solution for O...
Apidays New York 2024 - The value of a flexible API Management solution for O...Apidays New York 2024 - The value of a flexible API Management solution for O...
Apidays New York 2024 - The value of a flexible API Management solution for O...apidays
 
Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...
Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...
Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...Zilliz
 
Manulife - Insurer Transformation Award 2024
Manulife - Insurer Transformation Award 2024Manulife - Insurer Transformation Award 2024
Manulife - Insurer Transformation Award 2024The Digital Insurer
 
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers:  A Deep Dive into Serverless Spatial Data and FMECloud Frontiers:  A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FMESafe Software
 
AXA XL - Insurer Innovation Award Americas 2024
AXA XL - Insurer Innovation Award Americas 2024AXA XL - Insurer Innovation Award Americas 2024
AXA XL - Insurer Innovation Award Americas 2024The Digital Insurer
 
Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobe
Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, AdobeApidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobe
Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobeapidays
 
Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...
Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...
Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...apidays
 
TrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments
TrustArc Webinar - Stay Ahead of US State Data Privacy Law DevelopmentsTrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments
TrustArc Webinar - Stay Ahead of US State Data Privacy Law DevelopmentsTrustArc
 
TrustArc Webinar - Unlock the Power of AI-Driven Data Discovery
TrustArc Webinar - Unlock the Power of AI-Driven Data DiscoveryTrustArc Webinar - Unlock the Power of AI-Driven Data Discovery
TrustArc Webinar - Unlock the Power of AI-Driven Data DiscoveryTrustArc
 
ICT role in 21st century education and its challenges
ICT role in 21st century education and its challengesICT role in 21st century education and its challenges
ICT role in 21st century education and its challengesrafiqahmad00786416
 
2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...Martijn de Jong
 
A Year of the Servo Reboot: Where Are We Now?
A Year of the Servo Reboot: Where Are We Now?A Year of the Servo Reboot: Where Are We Now?
A Year of the Servo Reboot: Where Are We Now?Igalia
 
Apidays Singapore 2024 - Modernizing Securities Finance by Madhu Subbu
Apidays Singapore 2024 - Modernizing Securities Finance by Madhu SubbuApidays Singapore 2024 - Modernizing Securities Finance by Madhu Subbu
Apidays Singapore 2024 - Modernizing Securities Finance by Madhu Subbuapidays
 

Kürzlich hochgeladen (20)

Polkadot JAM Slides - Token2049 - By Dr. Gavin Wood
Polkadot JAM Slides - Token2049 - By Dr. Gavin WoodPolkadot JAM Slides - Token2049 - By Dr. Gavin Wood
Polkadot JAM Slides - Token2049 - By Dr. Gavin Wood
 
Automating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps ScriptAutomating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps Script
 
Powerful Google developer tools for immediate impact! (2023-24 C)
Powerful Google developer tools for immediate impact! (2023-24 C)Powerful Google developer tools for immediate impact! (2023-24 C)
Powerful Google developer tools for immediate impact! (2023-24 C)
 
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
 
Apidays Singapore 2024 - Scalable LLM APIs for AI and Generative AI Applicati...
Apidays Singapore 2024 - Scalable LLM APIs for AI and Generative AI Applicati...Apidays Singapore 2024 - Scalable LLM APIs for AI and Generative AI Applicati...
Apidays Singapore 2024 - Scalable LLM APIs for AI and Generative AI Applicati...
 
EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER
EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWEREMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER
EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER
 
MS Copilot expands with MS Graph connectors
MS Copilot expands with MS Graph connectorsMS Copilot expands with MS Graph connectors
MS Copilot expands with MS Graph connectors
 
Apidays New York 2024 - The value of a flexible API Management solution for O...
Apidays New York 2024 - The value of a flexible API Management solution for O...Apidays New York 2024 - The value of a flexible API Management solution for O...
Apidays New York 2024 - The value of a flexible API Management solution for O...
 
Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...
Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...
Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...
 
Manulife - Insurer Transformation Award 2024
Manulife - Insurer Transformation Award 2024Manulife - Insurer Transformation Award 2024
Manulife - Insurer Transformation Award 2024
 
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers:  A Deep Dive into Serverless Spatial Data and FMECloud Frontiers:  A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
 
AXA XL - Insurer Innovation Award Americas 2024
AXA XL - Insurer Innovation Award Americas 2024AXA XL - Insurer Innovation Award Americas 2024
AXA XL - Insurer Innovation Award Americas 2024
 
Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobe
Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, AdobeApidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobe
Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobe
 
Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...
Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...
Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...
 
TrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments
TrustArc Webinar - Stay Ahead of US State Data Privacy Law DevelopmentsTrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments
TrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments
 
TrustArc Webinar - Unlock the Power of AI-Driven Data Discovery
TrustArc Webinar - Unlock the Power of AI-Driven Data DiscoveryTrustArc Webinar - Unlock the Power of AI-Driven Data Discovery
TrustArc Webinar - Unlock the Power of AI-Driven Data Discovery
 
ICT role in 21st century education and its challenges
ICT role in 21st century education and its challengesICT role in 21st century education and its challenges
ICT role in 21st century education and its challenges
 
2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...
 
A Year of the Servo Reboot: Where Are We Now?
A Year of the Servo Reboot: Where Are We Now?A Year of the Servo Reboot: Where Are We Now?
A Year of the Servo Reboot: Where Are We Now?
 
Apidays Singapore 2024 - Modernizing Securities Finance by Madhu Subbu
Apidays Singapore 2024 - Modernizing Securities Finance by Madhu SubbuApidays Singapore 2024 - Modernizing Securities Finance by Madhu Subbu
Apidays Singapore 2024 - Modernizing Securities Finance by Madhu Subbu
 

Smart hospital technology

  • 1. Health Informatics-An International Journal (HIIJ) Vol.3, No.3,August 2014 SMART HOSPITAL TECHNOLOGY 1 M J Jayashree ,2Aju Sam Sunny, 3Anu John, 4Ashley Anna Sunny, 5Sruthi Susan Sam. Department of Electronics & Communication Engineering,Mar Baselios College of Engineering and Technology,Mar IvaniosVidya Nagar, Bethany Hills , Nalanchira Thiruvananthapuram -15, Kerala, India ABSTRACT 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. KEYWORDS DFT, FFT, IFFT, LPF, Arduino I. INTRODUCTION In Telemedicine communication through audio and video is done to convey or exchange the details of a patient with a physician. Using this process the details of a patient can also be discussed and analysed. In health information technology Telemedicine plays a major role. Telemedicine is basically the combination of medicine & information technology. This involves the transmission of medical information electronically. Hence this can be used for conveying the condition and status of patient to a doctor if the doctor is not available near the patient. Different methods can be applied for this purpose For example: store-and-forward technology, secure messaging; e-mailing, By monitoring the data received, the doctor is able to understand the patient's condition, to diagnose the disease and to take remedial measures. Videoconference is an effective measure in this case. 2. TELE MONITORING Tele monitoring is the monitoring patients who are not at the same location as the doctor. For example consider a patient with monitoring devices at home. He can easily transmit the results of to the doctor through telephone. This assists the patient to perform the initial and basic stage of health care by himself. Also this avoids the un necessary travel by the patient. Tele medicine is a fast growing field. A new type of Tele monitoring known as primary remote diagnostic disease has been introduced in a number of developing countries. In this technique devices are used by the doctor for the examination, diagnosis and treatment remotely. This type of treatment DOI: 10.5121/hiij.2014.3302 9
  • 2. Health Informatics-An International Journal (HIIJ) Vol.3, No.3,August 2014 is mainly used for monitoring the chronic diseases which have been diagnosed already. But this new technology can also be applied for monitoring and diagnosing the common diseases such as blood pressure, blood glucose, heart rate, weight etc. Frequent monitoring of the patient's condition enables the physician to suggest the best and effective course of treatment to the patient. 10 3. COMPONENTS OF THE SYSTEM The system comprises of signal acquisition unit, processing unit and alerting system. The signal acquisition unit is the high precision analog front end IC named AD620A from Analog devices. It is a low cost, high accuracy instrumentation amplifier that requires only one external resistor to set gains from 1 to 1000. The low noise, low input bias current and low power of the AD620 make it well suited for medical applications such as ECG and non-invasive blood pressure monitors. For the simulation of the below mentioned image processing algorithm, we use ECG signal which is captured from the body in real time. The processing unit is coupled with a PIC micro controller which acts as the alerting system. Data processing unit comprises of user PC / Laptop loaded with MATLAB. 4. IMAGE PROCESSING The atrial or ventricular regularity or irregularity is a measure of the cardiac rhythm which in turn gives an idea about the regularity or irregularity of the heart beat. The consistency of patterns between the p waves accesses atrial regularity while the consistency of patterns between R waves accesses ventricular regularity. Typical ECG waveform is shown in Fig.No.1 Fig.No.1: Typical ECG waveform Initially eyeballing, the rhythm for regularity was used. Now two more methods are available, one is the use of callipers and the other is paper technique. In Callipers two needle points are hinged together , one placed at the peak of the P wave or R wave and the other placed at the peak of the subsequent P wave or R wave. The needle points are held steadily and the callipers are moved down the strip. The needle points of the calliper if fall at the peaks of the subsequent P waves shows atrial regularity. If the needle point falls on the peaks other subsequent R waves shows ventricular regularity. On the other hand if the needle point do not fall at the peaks of the P waves or R waves shows atrial and ventricular irregularities respectively.
  • 3. Health Informatics-An International Journal (HIIJ) Vol.3, No.3,August 2014 In paper technique a clean and straight edge of paper is lined up with the peak of the P waves or R waves. Three P wave peaks in a row are marked on the edge of the paper and the paper is then moved to three subsequent P wave peaks. If the initial marks match with the marks of the subsequent P waves that shows atrial regularity and if there is no matching between the marks it shows atrial irregularity. Similarly ventricular regularity or irregularity is determined by repeating the process with Rwaves. 11 5. IMPLEMENTATION ALGORITHM Fig.No.2 Block diagram of Algorithm Step1: Obtain ECG signal from the controller, which is in digital form. The digital values obtained in the controller is collected in MATLAB software in real time. Step 2: Apply smooth filtering process to remove higher frequencies. The most randomly occurring signals are eliminated by setting a threshold value. These high frequency signals do not contribute any intelligence. It may be due to loose contacts in the electrode or variations in impedance matching. Step 3: To extract vital information from the ecg image apply wavelet decomposition technique.It is done by using the function ‘wavedec’. Step 4: Set a threshold value for identifying the critical condition in heart beat rate using the relation (maximum value-mean value) / 2. Step 5: R peak detection: Done using the function ‘waverec’, inverse of ‘wavedec’, which performs a multilevel one dimensional wavelet reconstruction. Step6: If the adjacent peak distance is greater than a specific value, save the corresponding image to a particular location in the computer. Step7: Calculate heart beat rate.
  • 4. Health Informatics-An International Journal (HIIJ) Vol.3, No.3,August 2014 From the final detected peaks any sort of abnormality can be easily detected. In case of emergency the PIC controller is triggered and the status of the patient is sent to the doctor as text message using a GSM modem as shown in the block diagram given below. 12 Fig No 3. Block diagram representation of emergency alerting system 6. SIMULATION RESULTS The setup is as shown in the Fig No.4 Fig No 4. The system
  • 5. Health Informatics-A An International Journal (HIIJ) Vol.3, No.3,August 2014 Fig No.6 6.Screen shot of message on doctor’s handset 7. EMERGENCY ALERTING Fig No 5 Final detected peaks LERTING SYSTEM The extracted vital intelligence in case of emergency is uploaded to the server. The image which is now saved in the server is automatically sent to the mail address of the doctors. In case of 13
  • 6. Health Informatics-An International Journal (HIIJ) Vol.3, No.3,August 2014 emergency the trigger is given to PIC controller which will send text message to the doctor using GSM modem. From the server the critical ECG image is sent to doctor’s email address. For the website creation Microsoft Visual Studio 2010 is the IDE been used .The programming language used here is C#. 14 Fig No.7.Login page of website Fig.No.8.ECG results of various patients.
  • 7. Health Informatics-An International Journal (HIIJ) Vol.3, No.3,August 2014 15 Fig No.9.List of doctors Fig.No.10.ECG image of patient displayed
  • 8. Health Informatics-An International Journal (HIIJ) Vol.3, No.3,August 2014 16 8. CONCLUSION This system is an initiative of automation in critical health care management. It provides continuous monitoring of patient and allows automatic data transfer. The system facilitates equitable access to the specialists for all patients regardless of their location. It provides opportunities for patients and relatives to contact their specialist. The system can completely automate the medical emergency conditions happening in an ICU. ACKNOWLEDMENT The authors would like to thank their colleagues at Mar Baselios College of Engineering and Technology for valuable discussions and feedback, also the reviewers for their constructive comments. REFERENCES [1]Lai Khin Wee, Yeo KeeJiar, EkoSupriyanto “Electrocardiogram Data Capturing System and Computerized Digitization using Image Processing Techniques” International Journal of Biology and Biomedical Engineering Issue 3, Volume 3, 2009 . [2]LjupˇcoHadˇzievski, BoˇskoBojovic´, VladanVukˇcevic´, PetarBeliˇcev, SiniˇsaPavlovic´, ZoranaVasiljevic´-Pokrajˇcic´, and MiodragOstojic´’A Novel Mobile Transtelephonic System With Synthesized 12-Lead ECG’ IEEE Transaction on Information Technology in Biomedicine, Volume 8, 2004 . [3]Prof. Dr. Burkhard Stiller ’Mobile Healthcare on Android Devices Communication Systems Group, Diploma Thesis, Dept. of Informatics, November 2010 . [4]Karen Panetta, Yicong Zhou,SosAgaian,HongweiJia”Non linearunsharp masking for mammogram enhancement” , IEEE Transaction on Information Technology in Biomedicine Volume. 15, November 2011. [5]Al-Naima, F. M., A. H. Ali, and S. S. Mahdi. Data acquisition for myocardial infarction classification based on wavelets and Neural Networks. Systems, Signals and Devices, 2008. IEEE SSD 2008.5th International Multi-Conference on.IEEE, 2008. [6]Chagas, A. V., E. A. B. Da Silva, and J. Nadal. ECG data compression using wavelets. Computers in Cardiology 2000.IEEE, 2000.