ECG Monitoring System Using Wireless Sensor Network (WSN) for Home Care Environment Prof. Dr. Norsheila Fisal, Department of Telecommunication and Optics, Faculty of Electrical Engineering, University Teknologi Malaysia (email:
[email protected]) Rozeha Abd Rashid, Department of Telecommunication and Optics, Faculty of Electrical Engineering, University Teknologi Malaysia (email:
[email protected]) Mohd Adib Sarijari, Department of Telecommunication and Optics, Faculty of Electrical Engineering, University Teknologi Malaysia (email:
[email protected]) Haslinah Mohd Nasir, Department of Telecommunication and Optics, Faculty of Electrical Engineering, University Teknologi Malaysia (email:
[email protected])
ABSTRACT The recent year has witnessed a significant surge of interest in sensing and monitoring in healthcare. The monitoring and acquisition of patients’ physiological information are quite crucial for the further treatment. Many patients can benefit from continuous monitoring as a part of a diagnostic procedure, optimal maintenance of a chronic condition or during supervised recovery from an acute event or surgical procedure. Wireless Sensor Network is becoming a promising technology for various applications. One of its potential deployments is in the form of wireless biomedical sensor network (WBSN) for wirelessly monitoring patients’ physiological signals (EEG, ECG, GSR, blood pressure, blood flow, glucose level, etc.) measured by wearable or implantable biosensors. WBSN, unlike wired monitoring systems, allows unobtrusive ubiquitous monitoring of patients’ physiological states and can generate early warnings if received signals deviate from predefined personalized ranges. In this paper, we propose a WBSN node platform featuring a low cost ECG sensor, sensor board to amplify, sample and filter the signal, a user-friendly graphical user interface (GUI) and also IEEE 802.15.4 based wireless sensor nodes which protocol offers multi-hop communication capability, hence providing an unlimited range of communication. As a case study, a 3-lead Electrocardiogram (ECG) sensor is developed and integrated with the WBSN node for preliminary evaluation. Keywords: Wireless Sensor Network, biosensor, IEEE 802.15.4 standard, multi-hop communication
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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 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 fulfil 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]. The design of this monitoring system is for home-care environment and is generally divided into three parts as shown in Fig 1, which is the data acquisition part, the data terminal part and the data processing part that will be explained in the following sections. This paper will also address the hardware and software development and integration.
Fig 1 : Overall System
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2. Methodology 2.1 Data acquisition (DAQ) and data terminal The data acquisition part of the monitoring system concerns with the development of ECG sensor board which consists of ECG electrodes and signal amplifying circuits. The task is to acquire the data (heart signal) from the human body, amplify and filter the signal before it is sent to its destination. The second part of the project is the data terminal that consists of microcontroller circuits for handling the acquired data and then transmitting it to the data processing part. It receives the heart signal in analog form and then converts it to digital signals with 8 bit resolution and a sampling rate of 500 Hz before sending it to the personal computer (PC). Simple routing mechanism is also implemented to enable multi-hop communication and thus ensuring the data reaches its destination via intermediate sensor nodes regardless of the distance of the patient from the base station (PC). The sensor node in Fig 2 was designed to continuously transmitting the signal wirelessly to the base station. The sensor gathers useful patient ECG data and these signals have to be amplified due to the reason that signals acquired from human body are generally weak, ranging from 0.5 mV to 5.0 mV. The amplified signals are then filtered for noise removal.
Figure 2: Sensor node 2.2 XBEE module (IEEE 802.15.4 protocol)-WBSN The routing protocol used in this system is Ad-hoc On-Demand Distance Vector Routing (AODV) which is a novel algorithm for the operation of such ad-hoc networks. This algorithm is quite suitable for a dynamic self -starting network as required by users wishing to utilize adhoc networks. AODV provides loop-free routes even while repairing broken links [6]. The routing frame (network frame) was created in order to provide broadcast function to wireless devices and also to test the system prototype. The frame identification (id) created is as shown in Fig 3.
Fig 3: network frame
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The source node (patient’s node) will first broadcast route request (RREQ) packet across the network. A node receiving the RREQ may send a route reply (RREP) if it is either the destination or if it has a route to the destination. If the destination address is similar to the id module then the data will be forwarded. Otherwise the node will rebroadcast the RREQ until it found its desired route to the destination as shown in Fig 4.
Fig 4: Data transmission through broadcasting 2.3 Base Station Vital ECG data from the patient is relayed using the AODV multi-hop routing scheme to the base station, the PC. The PC functions as the data processor. It is used to reconstruct the ECG signals from the digitized signals. The base station receiver module as shown in Fig 5 is connected to the PC via RS232, a serial communication interface. It receives the sent data from the microcontroller wirelessly and transmitted it serially to the PC 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.
Fig5: Base station receiver module
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3. Performance Evaluation
3.1 Prototype of ECG Sensor Board A standard 3-lead ECG sensor board was developed as shown in Fig 6. The board is interfaced with the microcontroller (PIC 18F452) through an ADC input pin (Port A) [7]. The signal from the sensor board will be converted to digital and sent to the base station receiver module.
Fig 6: ECG sensor board
3.2 Power Budget The power budget of microcontroller and the transceiver of each node are listed as in Table 1. TABLE 1. Node Power Budget Microcontroller: (2-5.5)V
Transceiver (2.8-3.4)V
Standby: < 0.2µA
Power down: < 10µA
5V operation: < 1.6mA (4MHz)
Transmit: 45mA(@3.3V)
3V operation: 25µA (32kHz)
Receive/Idle: 50mA(@3.3V)
Refer to the Table 1 [5], [7]. We assume the operation voltage for the node is 3.3V. The description of the states for the node is as follows: Power down mode: the node is not operating at this mode. The current is 10µA and the power is 33µW (10µ x 3.3V) Transmit mode: the data transmission by the transceiver is active and microcontroller is in 3V operation. The current is 45mA and the power is 148.5mW. Receive mode: everything is off except the transceiver receive mode and the microcontroller 3V operation. The current is 50mA and the power is 165mW.
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3.3 Results 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]. Preliminary evaluation of system performance is carried out using a patient simulator by DNI Nevada Inc. (Fig 7).
Fig 7: Patient simulator Fig 8 to Fig 10 show the plotted ECG signals at the base station (PC) as transmitted from the patient simulator at the source node. Fig 8 clearly displays a normal heart condition with a heart rate in the range of 60 bpm to 100 bpm. The GUI also has features such as patient’s data entry and an analysis button for diagnosis. An alert signal will appear if any abnormalities are detected.
Fig 8: Normal sinus rhythm
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Whereas Fig 9 shows a sample of ECG signal of a patient with an abnormal heart rate, below 60 bpm, known as sinus bradycardia. Similarly, Fig 10 also illustrates a heart rate abnormality, a sinus tachycardia, a condition when the heart rate exceeds 100 bpm.
Fig 9: Sinus bradycardia
Fig 10: Sinus tachycardia These preliminary results indicate the functionality of the overall designed WBSN node platform. The acquired heart rate patterns of the patient at home can be easily relayed to remote handheld computers or PDAs carried by medical personnel via the PC that can be assigned as a gateway to the Internet. Refer again to Fig 4. In planning, the measured bio-medical data from the home-based monitoring system will also be transmitted through the Internet, towards the appropriate Hospital Health Monitoring Center (HHMC), where this data will be integrated with the permanent medical data of the given patient. Therefore, the medical personnel at HHMC will be able to monitor various vital signs at any desired time. Should the readings suggest any adverse health situations, medical instructions can be given and actions can be taken before the situations deteriorate. This smart home health monitoring is expected to help older people or the patients with chronic disorders to live on their own longer.
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4. Conclusions 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 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. References [1] Chen Xijun, Max Q.-H Meng, Ren Hongliang, “Design of Sensor Node Platform for Wireless Biomedical Sensor Network”, Proceedings of IEEE 27th Annual Conference Engineering in Medicine and Biology, Shanghai, China, September 1-4, 2005. [2] 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. [3] 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. [4] J. Muhlsteff, O. Such, R. Schmidt, M. Perkuhn, H. Reiter, J. Lauter, J. Thijs, G. Musch, M. Harris, Wearable Approach for Continuous ECG – and Activity Patient-Monitoring, Proceedings of IEEE 26th Annual Conference Engineering in Medicine and Biology, September 2004 [5] XBEE OEM RF modules, Product manual v1.xax-802.15.4 Protocol MaxStream.Inc, (2006.10.13), www.maxstream.net [6] 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 [7] PIC18FXX2 Datasheet, Microchip (2007.12.12),www.microchip.com
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