2008 International Conference on Electronic Design
December 1-3,2008, Penang, Malaysia
Design and Implementation of Wireless Biomedical Sensor Networks for ECG Home Health Monitoring Rozeha A. Rashid, Mohd Rozaini Abd Rahim, Mohd Adib Sarijari, Nurhija Mahalin Department ofTelematics and Optical Communication, Faculty ofElectrical Engineering, Universiti Teknologi Malaysia, 81310 Skudai, Johor, Malaysia
[email protected], mohd
[email protected]
Abstract Sensor network, in the form of wireless biomedical sensor network (WBSN), composed of a number of biomedical sensor nodes and multi-hop networking capability that can be deployed for long term and continuous healthcare monitoring. Physiological signals (ECG, EEG etc) will be measured by the biosensors that provide alerts immediately when abnormalities in a patient's physiological condition are detected. Development of wearable biomedical sensors within a wireless infrastructure opens up possibilities for smart home care by providing ubiquitous monitoring of patients under their physiological states even when they move, leading to better quality of patient care. In this paper, we describe the design and implementation of Wireless Biomedical Sensor Network (WBSN) node platform featuring a low-power CMOS 8-bit microcontroller, an IEEE 802.15.4 compatible transceiver and a compact ECG sensor that does not require skin preparation, gels, or adhesives. The developed platform is costeffective and allows easy customization, energyefficient computation and communication.
1. INTRODUCTION Throughout the decade, there were a number of attempts to develop medical information systems which are reliable, affordable and accessible over the entire hospital and beyond. The situation is made possible today with the development in the web-based technology, powerful personal computer (PC) technology, international standards and broadband telecommunication networks. These factors also have enabled data from a wide range of medical equipment, such as electronic stethoscope and ECG machine, to be connected into a common information environment. Research which aims to provide continuous monitoring of patients outside the hospital
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environment also needs to be developed. The potential applications will save lives, create valuable data for medical research, and cut the cost of medical services. One scenario is the monitoring of people who suffer from heart problems who are left alone at home without any supervision and may suffer an attack anytime. Sensor network, in the form of wireless biomedical sensor network (WBSN), [1] provides the technology that is a potential solution to this problem. WBSN composed of a number of biomedical sensor nodes and multi-hop networking capability that can be deployed for long term and continuous healthcare monitoring. Physiological signals (ECG, EEG etc) will be measured by the biosensors that provide alerts immediately when abnormalities in a patient's physiological condition are detected. The wireless link is utilized to fulfill the need for patient mobility in home healthcare and to transmit real-time medical information and warning within an acceptable time limit for critical life cases, especially when more than one sensor are interconnected. Currently, there are projects that deploy wireless communication infrastructure for remote medical care environment such as in [2], [4] and CodeBlue [3]. This paper describes the design of WBSN node platform that is capable of supporting ECG monitoring. The platform adopts IEEE 802.15.4 standards for its reliable wireless communication and multi-hop capability. XBee module, an IEEE 802.15.4 compliant transceiver is chosen due to its features that satisfy the unique needs of low-cost, easy-to-use, minimal power requirement of wireless sensor network and reliable delivery of critical data between devices [5].
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ill Fig. 1. Example architecture of Wireless Biomedical Sensor Networks [1]. The design of this monitoring system is for home-care environment and is generally divided into three parts as shown in Fig 2, which is the sensor node part, hopping node part and based station part that will be explained in the following sections. This paper will also address the hardware and software development and integration.
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Fig. 3. Biopotential amplifier circuit diagram
B Wireless sensor node
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Fig. 2 Overall system design
2. HARDWARE DESIGN A EeG sensor node A biopotential amplifier for single supply operation is used to develop ECG sensor node. It uses a Driven Right Leg Circuit (DRL) to drive the patient's body to a DC common mode voltage, centering biopotential signals with respect to the amplifier's input voltage range. The circuit described as shown in Figure 3 [9] is especially suited for low consumption, batterypowered applications, requiring a single battery and avoiding switching voltage inverters to achieve dual supplies with a gain of 60 dB. A DC input range of ±200 mV was implemented using low power operational amplifiers. A Common Mode Rejection Ratio (CMRR) of 126 dB at 50 Hz was achieved without trimming.
Fig. 4. Architecture ofWBSN node platform The main of the WBSN node is the low power 8-bit microcontroller PIC18F452 develop by Microchip Technology with featuring 1.5kB of RAM, 32KB of flash, 256B data EEPROM and 8-channels of lO-bit AID converter[7]. This 8-bit RISC microcontroller features extremely low current consumption (0.2uA typical standby current) that gives the node to expand their node lifetime and the voltage operation between 2.0V to 5.0V. Furthermore the microcontroller has high speed FLASH/EEPROM technology. The FLASH/EEPROM data can be retention more than 40 years. In the transceiver unit, the component used is XBee RF Wireless module from the MaxStream. The XBee RF Wireless Module Series is designed to meet IEEE 802.15.4 standard and support unique characteristic needed such as low cost and low power transceiver [5]. The module is easy to use and provide reliable delivery of critical data between devices. The features for this modules required a 3.3V for supply voltage, have distance range up to 100m for outdoor
and 30m for indoor, ISM 2.4GHz operating frequency and also may operate through AT and API Command Modes for configuring module parameter. This module is interfaced to a host device through a logic-level asynchronous serial port. Through its serial port, the module can communicate with any logic and voltage compatible UART or through a level translator to any serial device.
C.Based Station
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with the hardware. Fig 6 shows the GUI that been designed for this project.
B. WBSN Routing Protocol As a case study, flooding routing protocol has been chosen to implement in the WBSN node platform for preliminary evaluation. Different routing protocol can be implementing into WBSN platform node e.g. Adhoc On-Demand Distance Vector Routing (AODV), Low Energy Adaptive Clustering Hierarchy (LEACH) and etc for the future research. The Fig. 7 showed the flooding flowchart programming to be implementing into WBSN sensors node.
Fig. 5 Based Station The base station consists of the wireless module (XBee RF Module) and MAX. The based station receiver module (XBee) as shown in Fig 5 is connected to the computer via RS232, a serial communication interface. It receives the sent data from the microcontroller wirelessly and transmitted it serially to the computer to be processed and displayed in the form of reconstructed ECG analog signals using the built Graphical User Interface (GUI). The user friendly GUI is programmed using Visual Basic6.0 and able to receive packet information in real time. The raw packet data stream is then decoded and plotted on the screen. The heart rate pattern displayed on the PC helps to detect any abnormalities such as sinus bradycardia or sinus tachycardia.
3.
SOFTWARE
A.Graphic User Interface(GUI)
Fig.6 GUI interface A GUI platform was successfully developed using Visual Basic6.0 Programming that be able interact
End
Fig.7 Flooding flowchart programming
4. RESULT A prototype of the ECG monitoring was constructed on PCB for testing. Validation of the system as a whole requires several complementary efforts. These include calculation of correct sampling of the signal, and human studies to assess system performance in real-world settings. There are three types of heart rate condition which are; sinus rhythm, sinus bradycardia and sinus tachycardia. Usually heart rate is calculated as the number of contractions (heart beats) of the heart in one minute and expressed as "beats per minute" (bpm). Sinus rhythm is a term that describes a normal heart beat which is characterized by a usual rate between 60 bpm to 100 bpm. On the other hand, sinus tachycardia describes a fast heart rate at more than 100 bpm. For sinus bradycardia, the heart rate is below 60 bpm [5]. An ECG signal of a person with normal heart rate (between 60 - 100 bpm) has been plotted in the GUI platform as shown in Fig. 8. The status panel shows
the current date and time also the name and age of the user when the enter button is clicked. Analysis can be done by selecting the options analysis button and the results of analysis are shown in the diagnosis result box. The input data from the microcontroller that was used to plot the signal is also displayed in the text box
5. CONCLUSION
The monitoring and acquisition of patients' physiological information are quite crucial for the further treatment. We have developed a WBSN node platform for ECG monitoring with a satisfactory functionality and can be used to capture real-time vital signs from patients. The relay of data from home environment to remote handheld computers or PDAs carried by physicians for diagnosis is under SbowmglM development. The implemented WBSN node platform :::: can serve as a research platform for further study and evaluation of WBSN and its challenges which include issues such as wireless networking protocols, power:::::efficient topologies, frequency selection, bandwidth efficiency, routing and security.
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Fig. 8 Normal sinus rhythm A standard 3-lead ECG sensor board was developed as shown in Fig 9 (a). The signal from the sensor board will be converted to digital and sent to the base station receiver module. The sensor board was constructed on a PCB as shown in Figure 9 (b). The sensor board consists of Texas Instruments TLV2454 quad low power Op-amps, resistors and capacitors. External single power supply +3.3V are supplied to the sensor board to drive the amplifiers. The sensor board was initially tested using the oscilloscope. Three leads ECG sensor were applied to the sensor board and the probe was connected to the output pin of the board. The output is captured using a Data Acquisition Card and displayed on a PC as shown in Fi ure 9 (c).
[2]
[3]
[4]
[5] [6]
[7] [8] [9]
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Fig 9. (a)ECG-sensor node, (b) ECG sensor board (c) ECG Data: Sample of a male with heart rate of 77.92bps
Chen Xijun, Max Q.-H Meng, Ren Hongliang, Design of Sensor Node Platform for Wireless Biomedical Sensor Network, Proceedings of 2005 IEEE, September 2005. R. Fensli, E. Gunnarcon, O. Hejlesen, A Wireless ECG System for Continuous Event Recording and Communication to a Clinical Alarm Station, Proceedings of Annual International Conference IEEE EMBS, September 2004 David Malan, Thaddeus Fulford-Jones, Matt Welsh, Steve Moulton, Codeblue: An Ad-hoc Sensor Network Infrastructure for Emergency Medical Care, International Workshop on Wearable and Implantable Body Sensor Networks, April 2004. 1. Muhlsteff, o. Such, R. Schmidt, M. Perkuhn, H. Reiter, 1. Lauter, 1. Thijs, G. Musch, M. Harris, Wearable Approach for Continuous ECG - and Activity Patient-Monitoring, September 2004 XBEE OEM RF modules, Product manual vl.xax-802.15.4 Protocol MaxStream.Inc, 2006.10.13 Charles E. Perkins, Elizabeth M. Royer, Ad-hoc On-Demand Distance Vector Routing, Proceedings of the 2nd IEEE Workshop on Mobile Computing Systems and Applications, New Orleans, LA, February 1999, pp. 90-100. PIC18FXX2 Datasheet, Microchip http://www.cs.wright.edu/-phe/EGR199/Lab 4/ M.Nasir Haslinah, "Home-based medical care monltonng through Wireless Biomedical Sensor Network, Thesis, Universiti Teknologi Malaysia, Apr 2008
