ECG and EEG Monitoring using Power Line Communication

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

Power Line Based Biotelemetry System for Human Health Monitoring

Chronic patients have to been monitored continuously for reducing the risk in patient’s life. Recent years, healthcare equipments uses the communication modules for Tele monitoring applications. Preestablished power distribution system has drawn the attention of many researchers for communication applications. In this paper, we present the application of Power Line (PL) as a communication channel for transferring the biosignals. Transducers are placed at the appropriate locations for acquiring the biosignals, which are transmitted and received using the low voltage single phase power lines. Personal Computer (PC) interfaced with the receiver unit will be displaying the decoded signals. In MATLAB, orthogonal frequency division multiplexing (OFDM) is used for transmitting the data over the simulated power line channel (SPLC) and its performance is evaluated based on Bit Error Rate (BER). From the experimental results, it was observed that EEG and ECG signals were deformed due to the PL noise and disturbances. From the simulation results, the BER can be reduced by increasing the Fast Fourier Transform (FFT) size and by varying guard time size. It can be concluded that, power lines will be an cost effective way for communication with considerable speed and accuracy

Application of Power Line Communication in Healthcare for ECG and EEG Monitoring

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 to

Power line enhancement for data monitoring of neural electrical activity in the human body

Distance and real-time data monitoring are the necessary condition that makes any system in good working order. Recent advancements in micro-electronics and wireless technology enable the application of wireless sensors in both industry and wild environments. However, Long-distance wireless communication has several drawbacks like limited bandwidth, considerable costs and unstable connection quality. Therefore, Power Line Communication (PLC) using pre-established Power Lines (PL) becomes more attractive for high data transmission technology. This paper reviews the existing distance data monitoring systems and presents a case study for data transferring of temperature and heart beat measurement. The simulations were carried out on the detected and transmitted signals of medical data using Matlab program. Furthermore, a framework of Intelligent Neural Monitoring System (INMS) is proposed for future works. The performance of PLC as a channel to transfer the patient Heart Rate (HR) is evaluated based on the Bit Error Rate (BER)

Heart rate monitoring system based on power line communication

Nowadays, Power Line Communication (PLC) using pre-established Power Lines (PL) becomes more attractive for high data transmission technology. With the development of this technology utilizing distribution line, the medical data such as human Heart Rate (HR) can be transmitted over the power line channel. This paper presents a case study of HR Monitoring System (HRMS) involving the use of PLC as a channel to transfer the patient HR measured by Pulse Oximetry (PO). The collected data from the hospital will be stored in the system. The transmission of data on PLC is achieved by using Orthogonal Frequency Division Multiplexing (OFDM). The performance of the above techniques is evaluated based on the Bit Error Rate (BER)

Power line enhancement for data monitoring of neural electrical activity in the human body

Distance and real-time data monitoring are the necessary condition that makes any system in good working order. Recent advancements in micro-electronics and wireless technology enable the application of wireless sensors in both industry and wild environments. However, Long-distance wireless communication has several drawbacks like limited bandwidth, considerable costs and unstable connection quality. Therefore, Power Line Communication (PLC) using pre-established Power Lines (PL) becomes more attractive for high data transmission technology. This paper reviews the existing distance data monitoring systems and presents a case study for data transferring of temperature and heart beat measurement. The simulations were carried out on the detected and transmitted signals of medical data using Matlab program. Furthermore, a framework of Intelligent Neural Monitoring System (INMS) is proposed for future works. The performance of PLC as a channel to transfer the patient Heart Rate (HR) is evaluated based on the Bit Error Rate (BER)