C., Sridhathan and Fahmi, Samsuri (2014) ECG and EEG Monitoring using Power Line Communication. ACEEE International Journal on Communication, 5 (1). pp. 50-59. ISSN 2158-7558. (Published)
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Abstract
Information and Communication technology (ICT) takes the main role in the economic growth of a country and has many applications such as mobile network, healthcare, navigation system, internet, weather forecasting and home automation. Healthcare devices manufacture incorporate ICT components in their product for remote monitoring and delivering health associated services. Due to this additional telemetry features, cost of the devices are more and all hospital or clinic cannot afford to buy them. Hence in our work, Electrocardiogram (ECG) and Electroencephalogram(EEG) monitoring equipment based on power line communication is developed. This is cost effective and economical equipment which uses existing power cables as communication medium. ECG and EEG signals are measured and digitized for transmission. Power Line Modem (PLM) is used for transmitting and receiving the signals over power line cable. Signals are modulated and demodulated using direct-sequence spread spectrum (DSSS) technology. ECG and EEG signals are affected by power line disturbances at the receiver end. ECG’s recurring fixed wave pattern was helpful in studying the noise effect. Noise effect on EEG cannot be determined easily since it does not have fixed wave structures and varies randomly. Finite Impulse Response (FIR) filter with Kaiser Window is designed using MATLAB for filtering noise from ECG signal. When compared with other communication technologies like local area network (LAN), ZigBee, Bluetooth, the establishment cost for healthcare monitor using Power Line Communication (PLC) was less. ECG and EEG signals are successfully transmitted and received using power cables with certain limitations. FIR filter was very effective in ECG noise filtering. It can be concluded that, in future communication using power line cables will slowly replace current technologies and will be used in many health monitoring applications as well.
Item Type: | Article |
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Uncontrolled Keywords: | Healthcare; PLM; PLC; ECG; EEG; FIR; Kaiser Window |
Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering |
Faculty/Division: | Faculty of Electrical & Electronic Engineering |
Depositing User: | Mrs. Neng Sury Sulaiman |
Date Deposited: | 28 Aug 2014 03:39 |
Last Modified: | 16 May 2018 07:01 |
URI: | http://umpir.ump.edu.my/id/eprint/6445 |
Download Statistic: | View Download Statistics |
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