Design and Implementation of a Wireless Sensor Network for Health Monitoring Fangling PU1
Chao LI2, Tingting GAO 3, Jiao PAN 4, Jiaping LI 5
School of Electronic Information Wuhan University Wuhan, P.R.China
[email protected]
School of Electronic Information Wuhan University Wuhan, P.R.China 2:
[email protected], 3:
[email protected] 4:
[email protected], 5:
[email protected]
Abstract—The current health care system faces new
challenge: increasing aging population, growing health cost, and mobile life. We present a kind of network architecture for Health Care Monitoring. This network named HCMNet integrates isolated wireless sensor networks (WSNs) into internet. Each WSN composed of health care sensors and one mesh router operates as a mobile ad-hoc network. Sensors can move in the range of WSNs, while mesh router is deployed as a coordinator which manages WSN other than forwards data. All sensing data and software are stored in back-end server. The database inquiry, data analysis and the system management are processed on the web page of server. A testbed is constructed on Sun SPOT platform with IEEE 802.15.4 physical layer and MAC Layer. The experiment results show that the prototype HCMNet can provide cost effective, continual, supervised, and ambulatory health monitoring to patients and residents. Keywords-health care; wireless sensor networ; AODV; Sun SPOT.
I.
INTRODUCTION
The current health care systems, which are structured and optimized for reacting to crisis and managing illness, are facing new challenges: increasing aging population, high health care cost, and mobile life. The progress of science, technology and medicine has made the status of health in the world improved significantly. The global average life expectancy at birth has risen by nearly 20 years, from 46.5 years in 1995 to over 65 years in 2002 [1]. The people over 65 years require far greater healthcare services than before. For example, the medical cost of hypertension in 1998 in the EU was reported as high as $108.8 million [2]. Between 2008 and 2018, the average increase in national health expenditures is expected to be 6.2 percent per year, while the GDP is expected to increase only 4.1 percent per year [3], threatening the wellbeing of the entire economy. An economical way to reduce the burden of disease treatment is enhancing prevention and early detection. However, traditional health care services are often provided on the clinical environment. The data collection is intermittent, leaving gaps in the medical record. Moreover, today, many
This work is supported by SUN Company, Inc.
people live and work in global environment. They expect health care can be provided anywhere. Demand for better health care and concerns for the cost have triggered the generation and development of wearable medical sensors. During the last few years, there has been a significant increase in the number of wearable health monitoring devices, ranging from simple pulse monitors, portable hypertension monitors to sophisticated and implantable sensors. Wearable devices are a key technology in restructuring health care system toward a more proactive, affordable citizen-centered health care system. Recent technology advances in integration and miniaturization of physical sensors, embedded microcontrollers and radio interfaces on a single chip have enabled a generation of wireless sensor networks (WSNs). For health care application, wearable, medical sensors can be integrated into wireless nodes. Health care data which are collected automatically, continuously, and remotely by WSNs can be stored for a long period of time. These data are conducive to doctors and patients tracking and monitoring, drug administration, and early disease detection and prevention. Moreover, compared to mobile communication and internet, the using of WSNs is inexpensive due to that the RF transceiver of WSNs usually operates on the unlicensed frequency band, such as 2.4GHz-2.5GHz. The limitation of WSNs is the space coverage and bit rate of the physical layer. For example, IEEE 802.15.4 is designed to operate at rate of 250kbit/s, over a distance from 30m up to 200m. IEEE 802.11g can operate with a rate up to 54Mbit/s, over 100m. In this paper, we propose a Health Care Monitoring network named HCMNet for pervasive, adaptive healthcare in communities where residents or patients have diverse health care demands. HCMNet is a distributed system which combines mobile ad-hoc WSNs with conventional internet, and integrates embedded devices, back-end server, online analysis, and user interfaces. Service oriented Architecture (SOA) Technology is utilized to program the software that administrates the distributed system. The software service modules and their integration in SOA are introduced in another paper. This paper focuses on the design and implementation of HCMNet. HCMNet have several benefits:
flexible monitoring, mobility, cost effective and improving service quality. The rest of this paper is organized as follows. In section II, we present the architecture of HCMNet. An Implementation based on SUNSPOT and practical experiments are introduced in Section III. The conclusion is in Section IV. II.
NETWORK ARCHITECTURE
The objective of HCMNet is to provide customized healthcare services to residents or patients at effective cost. HCMNet satisfies theses objectives by unifying and accommodating heterogeneous devices in an architecture shown in Figure 4, which spans emplaced wireless sensors, mesh router, internet, and back-end server. A. Network Nodes HCMNet consists of two types of nodes: mesh routers and sensor nodes. Each sensor node, which scatters in WSNs, is an embedded system equipped with microcontroller, a radio transceiver, a battery. A microcontroller is an integrated circuit, commonly with central processing unit, RAM, Flash memory, GPIO (general purpose digital I/O), and serial communication interfaces such as UART, I2C and SPI. Many microcontrollers include analog input and A/D (analog to digital) converters. Sensors are usually integrated into embedded system through analog input (for analog signal), or I2C, GPIO, UART interfaces (for digital signal) to form wireless health care sensor node. We make the sensor node of WSNs by connecting health care sensors with embedded systems through peripheral interfaces. To collect health care data at home, hotel, restaurant or wherever it is located, wearable health care sensors are selected. Currently, there is a significant number of wearable health care sensors generated [5]. For example, pulse oximeter measures blood oxygen, implantable pressure transducer measures blood pressure, and ECG module signals reflect cardiac disease. The development of both wireless network and health care sensor enables common disease monitoring without limitation of wire line. Mesh routers are deployed immovably in HCMNet, unlike sinks which are formed automatically in conventional WSNs. Mesh routers not only route and forward information, they also act as agents that are responsible of managing and coordinating the WSNs. The task of mesh routers includes assigning sensor nodes to users, setting the working mode of sensors, selecting radio frequency channel and unique ID for each local WSN. Additionally, mesh router can store collected data temporarily when the internet congestion happens. To meet these requirements, Mesh routers are at least composed of a computer with Ethernet interfaces and a radio transceiver module. Visits from back-end user to sensor nodes starts from internet to mesh router, then they are transferred to sensor via radio channel. These mesh routers can extend HCMNet, and facilitate the administration of local WSNs and sensor nodes.
B. Wireless Sensor Networks The WSNs in HCMNet can be set in an office building, a resident community, or a hotel. These networks are still isolated islands. Connections among them are achieved through wired Internet connection, which is the key cost of HCMNet. A key requirement of the WSNs is to minimize the influence on daily life and activity while health care sensors work. Nodes can move arbitrarily within WSNs, which makes network topology change frequently and unpredictably. To achieve effective cost and mobility in WSNs, we establish the WSNs as mobile ad-hoc networks (MANETs) with only one Ethernet connection on mesh router. Ad-hoc on Demand Distance Vector (AODV) routing protocol [6], which is proposed for MANETs, is a good choice for creating route between two nodes of WSNs. AODV is a reactive routing protocol that it establishes a route to a destination only on demand. When a network node needs a connection, it broadcasts a request for connection. Other AODV nodes forward this message, and record the node that they heard it from, creating an explosion of temporary routes back to the needy node. When a node receives such a message and already has a route to the desired node, it sends a message backwards through a temporary route to the requesting node. The needy node then begins using the route that has the least number of hops through other nodes. Unused entries in the routing tables are recycled after a time. When a link fails, a routing error is passed back to a transmitting node, and the process repeats. The advantage of AODV is that it creates no extra traffic for communication along existing links. Distance vector routing is simple, and does not require much memory or calculation. C. Server The back-end server is programmed as a web server which delivers a web page when requested by a web browser. Both the data collected by sensors and the software of the system administration, data processing and analyzing, are stored on the server. Administrator can manage the whole system by accessing the web page on server. The monitored person can inquire his health status on web server through mesh router. Back-end users, such as doctors, health care advisors or relatives of patients can also inquire the health care monitoring data on the web page. III.
TESTBED IMPLEMENTATION AND EXPERIMENT RESULTS
We use SUNSPOT platform [7] to construct a testbed to emulate HCMNet for evaluation of the overall system and of individual components. A Sun SPOT kit contains one basestation Sun SPOT unit, two free-range Sun SPOT units, and a USB cable. The basestation serves as a radio gateway between other SPOTs and the host workstation. The Sun SPOT unit has two control switches, one USB connector, 8 multicolor LEDs, three kinds of sensors---a 3D accelerometer, a temperature sensor and a light sensor, 20 I/O connector pins that includes analog input, UART data line RX and TX, I2C interfaces. Both basestation and Sun SPOT have CC2420 radio chip in the form of an IEEE 802.15.4 physical interface and an IEEE 802.15.4 MAC Layer.
A. Testbed The mesh router of testbed is composed of a computer and a basestation (Figure 1). Sensor nodes of testbed are the combination of Sun SPOT unit with blood pressure measuring module (Figure 2). The data between blood pressure module and Sun SPOT are transmitted through UART data lines D0 (RX) and D1 (TX) respectively. Sun SPOT provides two protocols, radiostream and radiogram, for communication between two devices. The communication on radiostream protocol is stream-based, buffered, reliable one. The radiogram protocol provides datagram-based communication. The radiogram protocol can not guarantee packet delivery and ordering. We have 6 Sun SPOT units to construct a small mobile adhoc network. Since each Sun SPOT has equipped AODV algorithm, the AODV algorithm is used to determine the best route when communications between Sun SPOTs are routed more than one hop. The web server software is programmed via Java development tools, Netbeans. The principle of SOA guides the software development and system integration. The procedure of software development will be introduced in another paper.
Figure 1. Mesh router of testbed.
B. Results of Experiment We have done a series of experiments to evaluate the performance of communication of HCMNet. On the condition of one-hop and line-of-sight (LOS), the maximum distance of communication between sensor node and mesh router may be 70m. Figure 3 shows blood pressure data which was once measured and transmitted by sensor node, where Systolic blood pressure (SBP) is 121 mmHg，diastolic blood pressure (DBP) 71 mmHg，mean arterial pressure (MAP) 85 mmHg，pulse rate (PR) 78 BPM. We have made different size of data packet to test the data rate of one-hop of 40m long. It took 14 second to transmit 50000-bit packet, 20.5 second for 70000-bit packet through radiostream. The theoretical date rate of Sun SPOT is 250kb/s. Through radiostream, the data rate of packets over 10000 bits is about 3.5kb/s. When 1000 packets which are all composed of 100 bytes were transmitted at a repeating rate 1 packet per second, both the bit error rate and packet loss rate are zero. Adding relay SPOTs, the communication distance can be extend to at least 200m via 4 hops. We distributed 6 SPOTs arbitrarily within a one-hop range of mesh router. Since each sensor node was in the one-hop distance to mesh router and did not need relay for blood pressure data transmission, the sensing cycle of each sensor node can be set variously according to different requirements of monitoring. In one experiment, one sensor node worked at real time mode. It collected and transmitted data once 2 minutes (blood pressure module repeating period is 2 minute.). Another sensor node operated 4 times a day, and other sensor nodes operated once half an hour. During the unworking period, the sensor node was turn off to save battery energy. This experiment lasted one day and repeated 20 times. No data loss happened. In another experiment, we allocated two SPOTs within onehop range of mesh router, two were within two-hop range, the others were within three-hop and four-hop range respectively. The working modes of all nodes can be set variously. However, the sensor nodes can not be turn off during unworking period, since the nodes may be relay of other nodes. When the sensor node did not work, it dropped into a saving mode --- shallow sleep while the radio power is still on. The experiment lasted 2 hours and repeated 40 times. No data loss happened. The experiment on testbed shows that the prototype HCMNet is suitable for healthcare monitoring. In further studies, we plan to change SPOTs to Wi-Fi platforms [8], since Wi-Fi devices are based on the IEEE 802.11 standards and the maximum net bit rate of 802.11g is 54Mbit/s. Wi-Fi technology that can increase the transmission speed of medical images, ECG signal and video, enable more kinds of health care monitoring in home.
Figure 2. Sensor node of testbed
sensing data can be transmitted in the small WSN with very low bit error rate and packet loss rate. The presented technology has potential to offer cost effective, unobtrusive, continual, ambulatory and supervised health monitoring to patients and residents. They can obtain a wide range of benefits from our prototype HCMNet, such as early detection of abnormal condition, bad habit correction, and heavy disease prevention. ACKNOWLEDGMENT The work of this paper is supported by SUN Company, Inc. REFERENCES Figure 3. The result of sensor node measuring
[1] [2]
IV.
CONCLUSION
[3]
This paper presents a kind of network architecture named HCMNet, which integrates WSNs into internet. Each WSN is organized as a mobile ad-hoc network with one allocated mesh router connecting with internet. The health care data collected by sensor node are all transmitted to mesh router, then forwarded to back-end web server through internet. The whole network administration including working mode setting for sensor node, sensing data managing and analyzing are processed on back-end server. A testbed on Sun SPOTs platform is constructed to test the performance of HCMNet, where sensor node measures blood pressure. In our experiment, the measuring cycle can be flexibly set on the various requirements of patients. The experiment results show that the
[4] [5] [6]
[7] [8]
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Figure 4. Network architecture for health monitoring.
