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 Table of Contents  
ORIGINAL ARTICLE
Year : 2018  |  Volume : 3  |  Issue : 2  |  Page : 54-58

Monitoring of home patient over general packet radio service network


1 Department of Electrical Engineering, University of AL-Mustansiryia, Baghdad, Iraq
2 Department of Electrical Engineering, Al-HikmaUniversity, Baghdad, Iraq
3 Department of Electrical Engineering, University of Nairobi, Nairobi, Kenya

Date of Submission14-Nov-2018
Date of Acceptance16-Nov-2018
Date of Web Publication12-Dec-2018

Correspondence Address:
Dr. Mohanad Abdulhamid
Al-Hikma University, Baghdad
Iraq
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/ijas.ijas_17_18

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  Abstract 


Statement of Problem: Patient monitoring from a hospital has its own limitations. The main one is that there is a shortage in number of intensive care unit(ICU) beds in hospitals and a handful of people to be monitored.
Methodology of Solution: This paper tries to solve the problem of shortage in number of ICU beds by using a home patient monitoring device dependent on general packet radio service (GPRS). The patient monitoring device actualizes the utilization of the GPRS system to send essential signs information to a hospital server. This empowers a patient to be checked in the solace of his or her home. The information is sent utilizing the packet transmission strategy where the signal is separated into packets of information for transmission.
Results: The simulation results demonstrate the impact of the transmission channel on the transmitted signal by presenting an error rate.

Keywords: Bit error rate, general packet radio service network, home patient monitoring


How to cite this article:
Farhan M, Abdulhamid M, Akoth B. Monitoring of home patient over general packet radio service network. Imam J Appl Sci 2018;3:54-8

How to cite this URL:
Farhan M, Abdulhamid M, Akoth B. Monitoring of home patient over general packet radio service network. Imam J Appl Sci [serial online] 2018 [cited 2019 Jan 21];3:54-8. Available from: http://www.e-ijas.org/text.asp?2018/3/2/54/247320




  Introduction Top


Home patient monitoring is essentially the capacity of observing a patient remotely from somebody house. Home patient monitoring dependent on general packet radio service (GPRS) is the execution of restorative patient observing services fused with the communications systems.

GPRS is a packet-based communication service for cell phones that enables information to be sent and got over a cell phone network. It is a packet arranged portable information benefit on the second-generation (2G) and third-generation (3G) cellular communication system's global system for mobile communication. GPRS was initially institutionalized by the European Telecommunication Standards Institute in response to the earlier packet-switched cellular technologies. It is currently kept up by the 3G Partnership Project (3GPP).

In 2G systems, GPRS gives information rates of 56–114 Kbits/second. 2G cellular technology joined with GPRS is portrayed as 2.5G, that is, an innovation between the 2G and 3G of mobile communication.

A microcontroller is characterized as a little PC on a solitary coordinated circuit containing a processor core, memory, and programmable input/output peripherals. They are intended for implanted applications instead of the chip which are utilized in PCs or other universally useful applications.

Microcontrollers are utilized in consequently controlled items and devices, for example, implantable medicinal devices, remote controls, control apparatuses, and other installed frameworks. They are reasonable for enduring battery applications. Some microcontrollers might be utilized as digital signal processors, with higher clock speeds and power utilization.

Patient observing from a healing center has its very own impediments. The principle one is that there is a lack in number of intensive care unit beds in healing facilities and a bunch of individuals to be checked. Therefore, this paper tries to exhibit how tolerant checking dependent on GPRS can be executed to attempt and take care of this issue. Some works on this topic can be found in literatures.[1],[2],[3],[4],[5],[6]


  Design Methodology Top


The model of home patient monitoring dependent on GPRS is appeared in [Figure 1]. This model is simulated utilizing matrix laboratory (MATLAB) Simulink. The suppositions made are that the database is now accessible and that the signal being observed is produced and prepared for transmission.
Figure 1: Model of home patient monitoring based on general packet radio service

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Electrocardiogram signal

The electrocardiogram (ECG) signal is simulated using MATLAB. The ECG signal is obtained as shown in [Figure 2].
Figure 2: Electrocardiogram signal developed from a matrix laboratory code

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Signal processing and transmission

This included the usage of a digital signal processing section together with a communication system with the end goal to empower successful transmission of the ECG signal. The Simulink display utilized for the simulation is appeared in [Figure 3].
Figure 3: Matrix laboratory Simulink model for electrocardiogram signal transmission through general packet radio service

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Signal from workspace

This block is used for implementing a variable from the MATLAB workspace. In this case, the ECG signal is our variable used for the “signal from workspace” block. The ECG variable is a 1 × 600 matrix. [Figure 4] shows the ECG signal to be transmitted through GPRS. The signal's output is in successive sample times. In the case of this experiment, the sample time was set to 1 s.
Figure 4: Electrocardiogram signal from workspace on Simulink

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Image data type conversion

This block is responsible for the conversion and scaling of the input image into a specific output data type. The image, in this case, is converted into a Boolean data type output as shown in [Figure 5].
Figure 5: Image data type conversion

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Frame conversion

This block passes the input through to the output and sets the sampling mode output signal which can be chosen to be either frame based or sample based. In this case, it is chosen that the sampling mode output would be frame based.

Convolutional encoder

This block served the purpose of encoding binary data. A trellis structure is created to perform this function. The trellis structure is set as:

poly2trellis (7 171133)

Convolutional interleaver

Convolutional interleaving refers to a method that is used to rearrange a transmitted data sequence so that it becomes more scattered and rugged to longer sequences of errors. The convolutional interleaver block is used to change the order of the input signal (which is in symbols) using a set of shift registers. This is illustrated using a time scope shown in [Figure 6].
Figure 6: Interleaved signal using the convolutional interleaver block

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Gaussian minimum shift keying modulator

The Gaussian Minimum Shift Keying (GMSK) is a form of modulation that has no phase discontinuities used to provide data transmission with an appropriate efficiency for spectrum usage. [Figure 7] shows GMSK modulation of the ECG signal.
Figure 7: Gaussian minimum shift keying modulation of the electrocardiogram signal

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Multipath Rayleigh fading

Rayleigh fading is a statistical model that is used to evaluate the effect of the propagation environment on a signal such as that used by wireless devices. This is a block that is chosen to work as the channel for data transmission. It is suitable as it can be used to implement the air interface as the channel for communication. The Doppler frequency is set with reference to the sampling period of the signal. The Doppler frequency is set to 0.9 Hz. [Figure 8] shows the multipath Rayleigh fading channel signal.
Figure 8: Multipath Rayleigh fading channel signal

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Gaussian minimum shift keying demodulator

This block is used to demodulate the GMSK modulated signal using the Viterbi algorithm. [Figure 9] shows GMSK demodulated signal.
Figure 9: Gaussian minimum shift keying demodulated signal

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Convolutional deinterleaver

This is the block that restores the interleaved signal using a set of shift registers. This is illustrated in [Figure 10] as seen from the time scope.
Figure 10: Convolutionally deinterleaved signal

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Viterbi decoder

This block is used to decode the convolutionally encoded signal. The trellis code used is as follows:

poly2trellis (7,171133)

The resultant signal from the Viterbi decoder is shown in [Figure 11].
Figure 11: Output of the Viterbi decoder

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Error rate calculator

This block is used to compare the number of bits transmitted to the number of bits that are received on the receiver side.


  Simulation Results Top


The complete model shown in [Figure 3] is simulated using MATLAB Simulink to calculate the error rate by comparing between transmitted and received detected signals. [Figure 12] and [Figure 13] show the transmitted signal in bits and the received detected signal in bits, respectively.
Figure 12: Transmitted signal in bits

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Figure 13: Received detected signal in bits

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It can be concluded from the above two figures that, the two signals are not identical. This is due to the error occurs because of distortion introduced by Rayleigh fading channel. The bit error rate can be calculated as follows:

The simulation was running for 1000 s. The total number of bits that were sent in these 1000 s was a total of 1001. Out of the 1001 bits sent, the digital communication system successfully sent 493 bits. This shows that the bits that were not sent successfully are:

unsuccessfully sent bits due to errors = 1001 - 493 = 508

The bit error rate then can be calculated as:



This shows that approximately 50% of bits were sent successfully through the constructed GPRS communication network.


  Conclusion Top


This paper developed a model of home patient monitoring over GPRS system. MATLAB Simulink was used to study the performance of the model over Rayleigh fading channel. An error was introduced due to the distortion of the channel.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
  References Top

1.
Akoth B. Home Patient Monitoring Based on GPRS. University of Nairobi, Kenya: Graduation Project; 2014.  Back to cited text no. 1
    
2.
Riley WT, Keberlein P, Sorenson G, Mohler S, Tye B, Ramirez AS, et al. Program evaluation of remote heart failure monitoring: Healthcare utilization analysis in a rural regional medical center. Telemed J E Health 2015;21:157-62.  Back to cited text no. 2
    
3.
Pedone C, Rossi FF, Cecere A, Costanzo L, Antonelli Incalzi R. Efficacy of a physician-led multiparametric telemonitoring system in very old adults with heart failure. J Am Geriatr Soc 2015;63:1175-80.  Back to cited text no. 3
    
4.
Frederix I, Van Driessche N, Hansen D, Berger J, Bonne K, Alders T, et al. Increasing the medium-term clinical benefits of hospital-based cardiac rehabilitation by physical activity telemonitoring in coronary artery disease patients. Eur J Prev Cardiol 2015;22:150-8.  Back to cited text no. 4
    
5.
Kraai I, de Vries A, Vermeulen K, van Deursen V, van der Wal M, de Jong R, et al. The value of telemonitoring and ICT-guided disease management in heart failure: Results from the IN TOUCH study. Int J Med Inform 2016;85:53-60.  Back to cited text no. 5
    
6.
Zweth J, Askari M. Devices used for non-invasive tele-homecare for cardiovascular patients. In: Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2018). Vol. 5. Portugal: HEALTHINF; 2018. p. 300-7.  Back to cited text no. 6
    


    Figures

  [Figure 1], [Figure 2], [Figure 3], [Figure 4], [Figure 5], [Figure 6], [Figure 7], [Figure 8], [Figure 9], [Figure 10], [Figure 11], [Figure 12], [Figure 13]



 

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  In this article
Abstract
Introduction
Design Methodology
Simulation Results
Conclusion
References
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