Published on February 17, 2014
Regular Paper Proc. of Int. Conf. on Advances in Power Electronics and Instrumentation Engineering 2013 Application of Power Line Communication in Healthcare for ECG and EEG Monitoring Sridhathan C, Fahmi Samsuri Faculty of Electrical and Electronics Engineering, University Malaysia Pahang, Pekan Campus, Pekan, Malaysia Email: firstname.lastname@example.org, email@example.com Abstract—Tele-healthcare is used to deliver health associated services and information using communications technologies. Advances in communication network technology have the potential applications in healthcare industry. Healthcare industries are focusing on medical care; however urban communities will gain major focus and benefits because of advanced communication network technologies. The rural communities lack communication networks and medical facilities compared to urban communities because they are located at far distance and cost of establishment is more. Both urban and rural areas have Power Lines (PL) which is used to deliver electricity. This paper proposes a method for Telemonitoring of Electrocardiogram (ECG) and Electroencephalogram (EEG) signals using pre-established PL cables for Tele-healthcare application. In our work, ECG is measured by placing the electrodes based on Einthoven’s triangle and EEG signals is measured by placing the electrodes on FP1, FP2 and ear lobe. Measured signals are digitalized and then transmitted over the single phase PL cable using Power Line Modem (PLM) to a common monitoring place. In the receiver, signals are decoded and retrieved back. The ECG with fixed wave pattern was very useful in studying the effect of PL noises when compared with EEG which varies randomly based on the subject activities and does not have a fixed pattern. From the obtained results, it was observed that ECG, EEG signals where affected by the PL noise disturbances. Hence, filtration is required for the received signal to remove the PL noises. The cost of establishing PL communication system for Tele-healthcare application was less. Transmission and reception of ECG, EEG using PL was successful. It can be concluded that in future PL channel will replace all communication technologies and will be used in many medical applications too monitoring patient’s in real time using LAN, Radio Frequency(RF), zigbee, WAN etc[1,2,3]. Healthcare industries are targeting rural and urban areas for providing health and medical care. These latest technologies and infrastructures are available and benefits than urban areas. Moreover, health industries in rural areas cannot get such facilities because the cost for establishing these communication technologies is very high. The rural communities are located at far distance; hence establishment cost for communication networks and medical facilities is more compared to urban communities. Power Line Network (PLN) is available in both urban and rural areas for delivering electricity. Recently Automatic Meter Reading (ARM), home automation and networking, high-speed Internet service, street and stage lighting control, voice and data transmissions uses Power Line Communication (PLC) technology and still many researchers are going on. A smart house management system is a combination of technologies including PLC to enable and effectively monitor the house hold appliances. Controllers are employed to monitor home appliances like washing machine, lighting system, refrigerators, air-conditions according to the owners requirement. It improves the life style and living condition by connecting to the external world for information using the wiring which is used to connect home appliances and deliver electricity. Hence in our research work, the PLC technology using pre-established power cables was applied for telemedicine application. EEG and ECG signals were measured, transmitted and received using low voltage PL inside the building. In the monitoring room near the patient the transmitter unit was placed. In physician room receiver unit was placed and it was connected to the personal computer (PC) in which the medical data’s were displayed. ECG and EEG signal are used for studying the PL noise, interferences and disturbances. Power cables do not have fixed characteristics due to unpredictable load effects, noise, high attenuation and resonance effects. Hence implementing high quality transmission over PL remains a difficult issue. PLC was found to be a cost effective way for transferring the ECG and EEG signals inside a hospital building with considerable data speed, accuracy and less error. When compared to other technologies the establishment cost, visible range problem and power consumption of this prototype was much less. This paper is organized in the following manner. Introduction in Section 1 gives a brief description about the PLC in telemedicine application. Details of Biological Index Terms—Tele-healthcare, PLC, PLM, ECG, EEG. I. INTRODUCTION In hospitals, patients who are in need of medical aids are assisted by medical equipment such as ECG machine, blood pressure apparatus, ventilators and infusion pumps etc. Automated bio-signal monitors are placed in the hospital ward and Intensive Care Unit for monitoring the patient’s physiological parameters. In highly equipped hospitals these devices are interlinked by networking for monitoring and storing medical details if required. Nowadays, healthcare industries are applying communication and networking technologies in Telehealthcare application for delivering health related assistance to the patients. Telemedicine, Tele-surgery, Tele-health are few latest technologies used for assisting, treating and © 2013 ACEEE DOI: 03.LSCS.2013.4.527 41
Regular Paper Proc. of Int. Conf. on Advances in Power Electronics and Instrumentation Engineering 2013 Parameters ECG and EEG signals are given in Section 2 and Section 3 deals with the power line communication. Section 4 presents the hardware description followed by result and discussion in Section 5. TABLE I. SIGNAL VOLTAGE LEVEL AND TIME PERIOD FOR NORMAL ECG WAVEFORM Amplitude Duration Wave 0.25 P-R Delay of AV node to allow filling of Ventricles 0.12 –0.20 1.60 Q-S Depolarization of ventricles 0.35 – 0.44 Q– Depolarization of ventricles 0.4 S-T Beginning of ventricle repolarization 0.05 – 0.15 T – Ventricular repolarization A. Electrocardiogram Human cardiovascular system consists of four chambered heart which circulates blood to entire body through blood vessels named as arteries and veins. Sinoatrial (SA) node is the natural pacemaker of the heart which triggers the action potential and produces nearly 72 pulses per minute. This action potential starts at SA and spreads throughout the atria, atrioventricular node, bundle of His and Purkinje fibres. Contraction of atria produces the ‘P’ wave and ‘QRS’ complex are produced by the contraction of ventricles. Return of ventricles to a rest state will produces the ‘T’ wave. Path of electrical impulses in the heart and the normal sinus rhythm are shown in Figure 1. Amplitude Voltage level and Time Period for Normal ECG waveform is given in Table 1. ECG signal is a recording of the electrical activity of the heart and is used for diagnosing the heart rate, heart rhythm and heart diseases like ischemia (lack of blood flow), arrhythmia (irregular heart beat), bradycardia, tachycardia. The number of cardiac arrest and death rates are increasing due to ageing, work pressure and bad habitat [4, 5]. Time (sec) R – Contraction of ventricles Biomedical signals are divided into two categories namely Endogenous and Exogenous. Signals that are arising or produced inside living creatures by natural physiological processes such as electrocardiogram (ECG), electroencephalogram (EEG), Temperature, blood pressure are termed as endogenous signals. Signals which are applied from external source to measure internal structures and parameters of a human or any living organism is called as exogenous signals. Wave P– Depolarization of atria II. BIOLOGICAL PARAMETERS Signal Voltage (mV) 0.1 - 0.5 P- Depolarization of atria 0.11 its functions completely. Brain is considered as the primary organ which integrates, control and performs the body balancing, processing, thinking, face and place recognition, taste, smell, emotional reactions, hearing, response to reflexes, regulating and producing hormones [6, 7]. Human Brain consists of two hemispheres and four lobes named as frontal, parietal, temporal and occipital. Each lobe is responsible of some operation and functions. In case of frontal lobe it is responsible for speech, emotions and movements. Parietal lobe is associated with recognition of place and face. Occipital lobe deals with the vision and visual processing. Temporal lobe is responsible for memory, auditory and speech. In Figure 2, the function of the lobes is given in shown. Figure 2. Regions in brains with their function Measurement of brain’s electrical activity is termed as Electroencephalography (EEG). Electrodes are placed on the subject’s scalp and signals are recorded at different areas of the brain. By monitoring the EEG signals we can diagnose certain health disorder such as epilepsy, apraxia, sleeping disorders, Parkinson’s disease, shaking palsy and many more. In table 2, the EEG waveform that are produced based on the subject condition is shown. Figure 1. The heart and normal sinus rhythm B. Electroenchepalogram Human brain is the most complicated and interesting part. Many studies and researches have been carried out for several decades but until now it’s very difficult to understand © 2013 ACEEE DOI: 03.LSCS.2013.4.527 42
Regular Paper Proc. of Int. Conf. on Advances in Power Electronics and Instrumentation Engineering 2013 TABLE II. N ORMAL EEG SPECTRUM WITH FREQUENCY BAND AND VOLTAGE Wave Frequency (Hz) Voltage (µV) Delta 0.5 – 4 10 mV Theta 4–8 Alpha 8 – 13 Beta 13 – 30 Generated Pattern Kids – 50 Adult – 10 Kids – 75 Adult – 50 10 – 20 Subject Condition Profound Sleep Light Sleep, Emotional Stress Relax, Closed Eye Activity, Thinking C. Power Line Communication Technology Electric powers that are generated from the sources in the frequency range of 50-60Hz are transmitted to the consumers using the power lines. During 1920, PLC was initiated and used for detecting the faults in the distribution networks. The PLC technologies main advantages is the availability of power outlets in each room of a house, which avoids the additional costs for wiring and proves to be convenient and promising communication via power line. In case of critical situation, a fast data exchange between power plants, distribution network and substations is necessary to avoid the worse effect. Since the PL is already available and connected them it made their work simple. In olden days twisted pairs wire, coaxial cables and optical fiber were used for home automation and networking. Due to developments in the PLC technology nowadays we can send and receive the signals using power lines PLC has advantages like cost effective, extensive coverage and disadvantages such as noise, attenuation and open circuit [8, 9]. Power generated from the power plants will be in megawatts which are sent over high voltage PL to substations. From the substation power will be reduced to kilowatts for industrial applications carried in medium voltage PL. Further Power is reduced to watts and transmitted using Low voltage PL for home and other commercial purpose. Figure 3 shows the power distribution system. For quick communication and telemetry purpose PLC is used. Power-line when used as a channel for high frequency signal transmission, the signal will be affected and interfered by various additive noises, besides multi-path fading. Power Line noises can be viewed as a non-stationary signal with multiple components. Figure 4 represent the PL Channel with additive noises such as narrow band, coloured background, periodic impulse, burst noise, non-periodic impulse and additive white Gaussian noise [10, 11, 12]. Figure 3. Power Distribution System Figure 4. Model of Power Line Channel with additive noises III. HARDWARE DESCRIPTION Figure 5: Block diagram representation of the prototype Figure 5 shows the block diagram representation of the hardware consisting of ECG and EEG measuring unit, transmitter and receiver modules. ECG signals provide the detail information about myocardial electric activity and physiological function of the © 2013 ACEEE DOI: 03.LSCS.2013.4.527 heart. Position of the ECG electrodes is shown in the Figure 6a, RA refers to Right Arm, LA - Left Arm and RL - Right Leg respectively. The two electrodes placed on the RA and LA is used to record the electrical potential difference between two points. The electrode placed on right leg is termed as a refer 43
Regular Paper Proc. of Int. Conf. on Advances in Power Electronics and Instrumentation Engineering 2013 ence electrode or point. ECG electrodes are placed based on the Einthoven triangle on the body surface for measuring the ECG signal noninvasively. The triangle formed by the three electrode position is called Einthoven’s triangle. EEG signals provide the detail information about electric activity and function of the Brain. In the Figure 6b, the position of the electrodes for measuring EEG signal is shown. a) ECG Electrodes Position connecting to personal computer. EPLM uses the single phase low voltage power line (220V) as the channel for communication. Figure 8, shows the details how the EPLM is used for communication. b) EEG Electrode Position Figure 6: Position of the Electrodes for measuring ECG and EEG signals In figure 7, bio-signal acquisition using low noise instrumentation amplifier INA122 is shown. The ECG electrodes from RA, LA and RL are connected to the pins 2, 3 and 4 of INA122. Similarly EEG electrodes are connected to 2, 3 and 4 pins of INA122 from Fp1, Fp2 and earlobes respectively. It has two operational amplifiers (op-amp) for providing excellent performance during data acquisition. INA122 operates in the voltage range from 2.2V to 36V with quiescent current of 60µA. Gain of the amplifier circuit will be depending on the Resistor R1. The gain formula is given by the following equation. R1 value is changed based on the application. (1) Figure 8: EPLM modem pin connections for data communication PL modems transmits the data in digital from inside the building using the live and neutral cables which are used for distributing power. Carrier frequencies will be ranging from 50 to 500 kHz based on the modulation technique such as ASK (amplitude shift keying), PSK (phase shift keying), FSK (frequency shift keying), BPSK (binary phase shift keying) and DSSS (direct-sequence spread spectrum). In spread spectrum technique (SST) the data is transmitted by spreading over the given bandwidth. The advantage of SST is the resistance to Narrowband interference. The Narrowband data is converted into broad band signal which reduces the power level of the signal when compared to the original signal. Narrow and broadband interference are added to the signal during transmissions. PLC uses different frequencies based on the data transmitted over the power lines. Lower baud rate will be used for long distance communication with few hundred bits of data rate. The shorter distances will be covered by high baud rate which operates on millions bits. EPLM used here is based on SST and works at the baud rate of 300 bits per second at 115Khz. In the receiver side EPLM decodes the DSSS signal and send to processing unit which transfers the signal to computer for display and analysis. Figure 9 shows the prototype model used for measuring ECG and EEG signal. Figure 10 shows the embedded power line modem. Figure 7: Bio-signal acquisition using INA122 The measured ECG and EEG signals are fed as input to the Port0 of the AT89C51 microcontroller after converting them to digital signal using ADC0809 converter. These digital data streams are transmitted to the Embedded Power Line Modem ATL90115 (EPLM) using 89C51through the Port3 TXD and RXD pins. EPLM is a power line modem having high noise immunity and which can work in the range of 220–250V. EPLM works on the Direct Sequence Spread Spectrum Technology (DSSS) and transmits the data at the Baud rate of 300 bps. TTL or RS232C level serial interfacing is available for 44 © 2013 ACEEE DOI: 03.LSCS.2013.4.527 Figure 9. Model of prototype for measuring ECG and EEG signal
Regular Paper Proc. of Int. Conf. on Advances in Power Electronics and Instrumentation Engineering 2013 PLC will provide a huge opportunity for monitoring the health of out-patients and in-patients those who are suffering from chronic diseases. The ECG and EEG were transmitted inside the hospital building using single phase low voltage PL using the EPLM. The effect of the power line noises and disturbances was more in the received ECG and EEG signals because of their continuous time varying property. Figure 10. Embedded Power Line Modem IV. RESULT AND DISCUSSION The ECG and EEG signal are transmitted over the single phase power line using embedded power line modem inside the building. ECG signal which has the fixed waveform was very constructive in identifying level of the additive noise which is added in the channel. Figure 11 the signals measured using the proposed system are shown. In Figure 11a, ECG signal measured using the designed prototype is displayed. It can be noticed that ECG signal was affected by little noise level. In Figure 11b, ECG, EEG signal received using the PLC technology is shown. The VB software is used to regenerate the transmitted signals in the PC. In Figure 11c, close shot of the ECG and EEG signals are shown. When we compare the figure 11a and c, we can clearly understand the effect of PL noise on ECG signal. It was found that the P-wave and T-wave are mostly affected by noises when compared to QRS complex of ECG wave. This is because of the high amplitude voltage of QRS complex is less affected by noise. Since the EEG waves don’t have a fixed wave patterns, the effect of PL noises cannot be identified clearly. Data was transferred at a nominal baud rate of 300kbps. EPLM used for the work was able to communicate up to a distance of 300-400m in a single phase power line. It can be concluded that PLC is economical and cost efficient way for communicating inside a hospital building. When compared to other existing techniques, cost of fabrication of prototype is less and does not require any new channel for communication. Physiological parameter ECG and EEG were measured using the measuring unit, transmitted and received using the EPLM. The ECG and EEG waves were affected by the PL noises and other disturbances because of their continuous time varying property. In future, in addition to these ECG and EEG, other physiological parameters will added to the model; noise and errors rate will be reduced and communication distance will also be increased. (a) ECG signal displayed on the prototype (b) ECG and EEG signal received by using PLC (c) Clear view of the received ECG and EEG signals Figure 11. Signals measured using the proposed system REFERENCES SUMMARY AND CONCLUSIONS  Paul Frehill, Desmond Chambers and Cosmin Rotariu, “A Wireless Network Sensor and Server Architecture for Legacy Medical Devices”, IEEE International Conference on Telecommunications, St. Petersburg, 16-19 June 2008, 2008 pp1-4.  Paul Frehill, Desmond Chambers and Cosmin Rotariu, “Using In our work, we applied the PLC technology in Telehealthcare application. PLC was found to be a cost effective way for solving medical data transporting. The conventional or prior methods were not cost effective. Tele-healthcare using © 2013 ACEEE DOI: 03.LSCS.2013.4.527 45
Regular Paper Proc. of Int. Conf. on Advances in Power Electronics and Instrumentation Engineering 2013      Zigbee to Integrate Medical Devices”, Proceedings of the 29th Annual International Conference of the IEEE EMBS, Lyon, France, 23-26August 2007, pp. 6717-6720 R. Sukanesh, S. Palanivel Rajan, S. Vijayprasath, S. Janardhana Prabhu and P. Subathra, “GSM-based ECG Tele-aler t System”, International Journal of Computer Science and Application, ISSN 0974-0767 Issue 2010, pp.112-116. Paul S Addison, “Wavelet transforms and the ECG: a review” Physiological Measurement, Institute of Physics Publishing, 26 (2005), pp. R155–R199 Cai Ken and Liang Xiaoying, “A Zigbee Based Mesh Network for ECG Monitoring System”, in Proc. iCBB, Chengdu, 1820 June 2010, pp. 1-4. Pari Jahankhani, Vassilis Kodogiannis and Kenneth Revett, “EEG Signal Classification Using Wavelet Feature Extraction and Neural Networks” International Symposium on Modern Computing, 2006. JVA ’06. IEEE John Vincent Atanasoff 2006, Sofia, 3-6 Oct. 2006, pp120-124. R. Dilmaghani, M. Ghavami, K. Cumar, A Dualeh, S. Gomes Da Sousa, R. Salleh Mohd, M. Sekanderzada and H. Koke, “Design and Implementation of a Wireless Multi Channel EEG © 2013 ACEEE DOI: 03.LSCS.2013.4.527      46 Recording”, 7th International Symposium on Communication Systems Networks and Digital Signal Processing (CSNDSP), Newcastle upon Tyne, 21-23 July 2010, pp741-746 Muhammad Salman Yousuf and Mustafa El-Shafei, “Power Line Communications: An Overview - Part I”, 4th International Conference on Innovations in Information Technology, 2007, Dubai. 18-20 Nov. 2007, pp.218 – 222 V.C. Gungor and F.C. Lambert, “A survey on communication networks for electric system automation”, Computer Networks 50, 2006, pp.877–897. J. Michael Silva and Bruce Whitney, “Evaluation of the Potential for Power Line Carrier (PLC) to Interfere with Use of the Nationwide Differential GPS Network”, IEEE Transactions on Power Delivery, VOL. 17, NO. 2, April 2002, pp.348-352. Manfred Zimmermann and Klaus Dostert, “Analysis and Modeling of Impulsive Noise in Broad-Band Powerline Communications”, IEEE Transactions on Electromagnetic Compatibility, vol. 44, no. 1, February 2002, pp. 249 – 258. X. Jiang, J. Nguimbis, S. Cheng, H. He, X. Wu, “A novel scheme for low voltage power line communication signal processing” Electrical Power and Energy Systems 25 (2003), pp.269–274.
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