Wireless Sensor Networks in Health

60 Wireless Sensor Networks in Health Enrique Dorronzoro University of Sevilla

Isabel Gómez University of Sevilla

Ana Verónica Medina University of Sevilla

Luis Fernández-Luque University of Sevilla and Northem Research Institute

Jose Antonio Gómez University of Sevilla

60.1 Introduction.....................................................................................60-1 Wireless Sensor Networks in Health

60.2 Wireless Communication Standards............................................60-2 IEEE 802.15.1 • IEEE 802.15.3 • IEEE 802.15.4 • IEEE 802.15.4/ZigBee

60.3 Conclusion......................................................................................60-10 Acronyms...................................................................................................60-10 References...................................................................................................60-11

60.1 Introduction Recent advances in telecommunications are changing our society. The main reasons for this evolution are the increase of connectivity and the monitoring advances, which provide mobility to humans and increase accessibility for the handicapped. Wireless telecommunications allow transferring information between two or more devices that are not physically connected. Figure 60.1 shows wireless networks transmission technologies comparing bandwidth with power consumption. As shown in this figure, higher transmission speeds imply higher power consumption. In order to guarantee people mobility, there has to be a compromise between these two variables. It is required to use technologies that transmit with enough bandwidth but without high power consumption. From all the standards defined for wireless communications, IEEE 802.11 and 802.15, standards have a higher impact. IEEE 802.11 describes a set of standards for implementing Wireless Local Area Networks (WLAN) and IEEE 802.15 is specialized in Wireless Personal Area Networks (WPAN). WPAN is a network used to communicate devices in proximity to an individual’s body using wireless technologies such as Bluetooth, ZigBee, and IrDA. This group of standards includes a wide range of devices. A wireless sensor network (WSN) consists of a WPAN composed by autonomous sensors (sensing nodes) that cooperate to monitor physical or environmental conditions, such as temperature, sound, vibration, and pressure. WSN components are sensing nodes, transmission technology, and a standard to define the communication. WSN allows cooperation between systems where devices are close to the human body. 60-1 © 2014 by Taylor & Francis Group, LLC

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Medical, Biomedical, and Health

100 Mbit/s IEEE 802.11

10 Mbit/s

1 Mbit/s

IEEE 802.15.1 IEEE 802.15.4

Downloaded by [Universidad de Sevilla] at 23:03 25 February 2014

100 kbit/s

1 kbit/s

20 mW

40 mW

80 mW

100 mW

300 mW

500 mW

1000 mW

Figure 60.1 Body Area Network (BAN) power versus bandwidth. WLAN and IEEE 802.15 are specialized for WPANs.

60.1.1 Wireless Sensor Networks in Health WSN are becoming increasingly important for monitoring patients both in the clinical setting and at home. Remote monitoring allows monitoring of sports activities, emergencies, catastrophe responses, etc. Wireless communications also provide more comfort for the patients, with the absence of wires reducing costs and providing more flexibility. WSNs can integrate vital sign sensors and also environmental sensors such as air quality. The following section describes the WSN transmission technologies including a state of the art of the publications that implement a WSN system in health. This review has been published in Ref. [45] and updated with recent progress.

60.2 Wireless Communication Standards As previously presented, IEEE 802.11 and IEEE 802.15 family of standards are more relevant for wireless communications. But due to the high power consumption of IEEE 802.11, the IEEE 802.15 family selected for WSN. IEEE 802.15 is divided in different sections: • IEEE 802.15.1, Bluetooth. • IEEE 802.15.3 defines physical layer (PHY) and medium control access (MAC) layers for highspeed WPANs. • IEEE 802.15.4 defines PHY and MAC layers. In some occasions, ZigBee is used to implement upper layers. • IEEE 802.15.6, a task group is formed to be in charge of developing a communication standard optimized for low-power devices and operation on, in, or around the human body (but not limited to humans) to serve a variety of applications including medical, consumer electronics/personal entertainment, and others.

© 2014 by Taylor & Francis Group, LLC

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Wireless Sensor Networks in Health

60.2.1 IEEE 802.15.1 Originally developed by Bluetooth SIG., the IEEE 802.15.1 standard is defined to operate with devices that provide a short range with medium transmission speed. In 1999, the committee came up the first Bluetooth specification, version 1.0. From this moment, it started spreading because of its low power consumption and low cost. 60.2.1.1 Frequency


Bluetooth operates on the 2.45 GHz frequency band (ISM band; Industrial, Scientific and Medical band). This band is shared with Wi-Fi, so to solve possible interference problems, it implements some key technologies. One of these solutions consists of using low power signals (1 mW). Even with the low power, Bluetooth devices do not need to be in the line of sight to communicate. 60.2.1.2 Range The maximum distance that Bluetooth can reach is based on the power of the transmission. There are three classes with different ranges and signal power levels as shown in Table 60.1. 60.2.1.3 Bandwidth Bluetooth devices can be also classified according to the bandwidth (Table 60.2). 60.2.1.4 Network Topologies Bluetooth networks are called piconets. A piconet is composed of a master device that controls seven different devices. In this way, all the devices that belong to the same piconet share the same hop frequency and their clocks are synchronized with the master. One device can be part of different piconets at the same time irrespective of whether it is a master or a slave. It is possible to connect different piconets in a scatternet in order to expand the physical size of the network beyond the Bluetooth’s limited range. Having eight devices in less than 10 m causes interference between members. To prevent this problem, Bluetooth defines time slots to avoid two or more devices transmitting at the same time. Table 60.1 RF Power Classification Levels Class Class 1 Class 2 Class 3

Power (mW) 100 10 1

Maximum Allowed Range (m) 100 10 1

Table 60.2 Bandwidth Classification Version Version 1.2 Version 2.0 + EDR Version 3.0 + HS Version 4.0 + HS


Bandwidth (Mbit/s) 1 3 1 1

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However, this is not the only interference problem. The interference can also be caused by near piconet clusters in the vicinity. This problem is not resolved by time slots as this solution only works for the devices on the same piconet. This is the reason why Bluetooth implements a frequency-hopping spread spectrum (FHSS) mechanism to avoid interference between piconets. FHSS is a transmission process where the devices involved in the communication change their frequency in regularly hops according to a predetermined code. Summarizing, time slots prevent interference between Bluetooth devices that belong to the same piconet and FHSS prevents interferences between Bluetooth devices of different piconets.


60.2.1.5 State of the Art One of the advantages of Bluetooth is that it can be integrated in most mobile devices and laptops. It is common to use these devices as the master devices of the topology that is in control of the sensors that compose the network. Based on this topology, a laptop may be used as the master device on the piconet. Bluetooth publications are summarized in Table 60.3. Most of these reviewed publications are focused on monitoring parameters for a specific scenario. Some examples of the applications of Bluetooth in health are discussed later: • A polysomnography sensor is used to remotely record sleep disorders [27]. • An accelerometer and optical sensor are used in sport activities [42]. An elastic belt encircles the user’s chest and measures low frequency components of belt circumference change. Variations in this length are measured by an optical sensor and outputted as serial digital data. The accelerometer measures dynamic acceleration force produced by the user. • Electrocardiogram (ECG) sensors, Electrooculography (EOG) sensors, and Electroence phalography (EEG) sensors are mounted on a helmet for general monitoring [28]. But there is also the possibility of using Bluetooth in a smartphone as the master device [26] to collect data from other sensors such as a glucose sensor to control diabetes. Many medical systems are also using Bluetooth sensors [38]. One example uses a system with a wireless ocular telemetry sensor for glaucoma. Another example is found in [40] where the study of photoplethysmography using an accelerometer can provide valuable information about the cardiovascular system, such as heart rate, arterial blood oxygen saturation, blood pressure, cardiac output, and autonomic functions. A last example is a system for the detection of gait abnormalities or deteriorations in a patient’s home environment by using accelerometers and gyroscopes [24]. Other classes of systems are focused on monitoring activities [18,43]. This kind of monitoring system is aimed for elderly people and rehabilitation therapies. Sensors used in these applications are presented in Table 60.4. Table 60.3 IEEE 802.15.1 Reference Greene et al. [24] Istepanian et al. [26] Kayyali et al. [27] Kim et al. [28] Mansouri and Shaaranyh[38] Poh et al. [40] Tawa et al. [42] Wagenaar et al. [43] Au et al. [18]


Health Focus

Health Focus

Battery Life

Gait monitoring Diabetes monitoring Sleep disorders monitoring Monitoring Glaucoma monitoring Monitoring photoplethysmography Breathing training Monitoring of functional activities Continuous activity monitoring

Accelerometer gyroscope Glucose Polysomnography ECG, EOG, EEG Intraocular pressure Accelerometer Optical accelerometer Accelerometer, gyroscope Accelerometer

N/A N/A N/A N/A N/A N/A N/A N/A N/A

60-5

Wireless Sensor Networks in Health Table 60.4 Sensors Used with IEEE 802.15.1 Sensors Greene et al. [24] Istepanian et al. [26] Kayyali et al. [27] Kim et al. [28] Mansouri and Shaaranyh [38] Poh et al. [40] Tawa et al. [42]


Wagenaar et al. [43]

Gyroscope Glucose meter Polysomnography ECG, EOG, EEG Intraocular pressure Accelerometer Accelerometer Optical Accelerometer Gyroscope

SHIMMER add-on [15] OneTouch Ultra, LifeScan [11] Crystal Monitor PSG Series, CleveMed [8] Electrical tape, 3M SENSIMED Triggerfish [14] ADXL 330, Analog Devices [6] KXM52–1050, Kionix BOMC2-USSP, Buffalo MMA7260Q, Freescale [10] Idg500 InvenSense [2]

60.2.3 IEEE 802.15.3 The IEEE 802.15.3 standard is designed to provide a high data rate and low power consumption solution for WPAN. It is designed to provide sufficient quality of services for the real-time distribution of content such as video and music. The original standard uses a traditional carrier-based 2.4 GHz radio as the physical transmission layer. IEEE 802.15.3a is a follow-on standard still in the formative stages, which will define an alternative and improved physical layer. Current proposals based on ultra wide band (UWB) will provide more than 110 Mbit/s at a distance of about 10 m and 480 Mbit/s at 2 m. This will allow the streaming of highdefinition video between media servers and high-definition monitors, as well as fast transfer of files among servers and portable devices. Reference [44] compares the 802.11e hybrid coordination function (HCF) MAC and 802.15.3 time division multiple access (TDMA) MAC mainly in terms of throughput and power management. The conclusion after the comparison is that the throughput differences between them are quite small. On the other hand, the power management of 802.15.3 is easier than that of 802.11e. But unfortunately, its power consumption is similar to that in a Wi-Fi device, around 227 mA, when transmitting and receiving [31] so it is high for the telemedicine field when using wireless sensors.

60.2.4 IEEE 802.15.4 IEEE 802.15.4 is a standard that specifies the physical layer and MAC layer for low-rate wireless personal area networks (LR-WPANs). It offers short range and low bandwidth but with the benefit of low power consumption. It is mainly used for industrial control, embedded sensors, and it is also adequate for healthcare systems. Healthcare systems can benefit from this technology as a node can go to sleep and wake up when a new task is due thus saving battery power. 60.2.4.1 Characteristics • Frequency: Uses ISM frequency band, mainly at the 2.4 GHz band, 868 MHz (Europe) and 902– 928 MHz (North America). • Range: 10–50 m, but it depends on the environment. • Bandwidth: Data transmission range up to 250 kbps. 60.2.4.2 IEEE 802.15.4 Devices Two different device types can participate in an LR-WPAN network; a full function device (FFD) and a reduced function device (RFD). The FFD can operate in three modes serving as a personal area network (PAN) coordinator, a coordinator, or a device. An FFD can talk to RFDs or other FFDs, while an RFD


60-6


can talk only to an FFD. An RFD is intended for applications that are extremely simple, such as a light switch or a passive infrared sensor; they do not have the need to send large amounts of data and may only associate with a single FFD at a time. Consequently, the RFD can be implemented using minimal resources and memory capacity. 60.2.4.3 Topologies


It is important to understand that the network layer is not defined for this standard. This means there is no possibility to route the data between the different nodes that compose the network. There are two defined topologies. Both require a PAN coordinator that works as a network coordinator. This device must be an FFD. These topologies are illustrated in Figure 60.2. • Star topology: Communication is established between a central device and other IEEE 802.15.4 devices. This central device is called a PAN coordinator and it is unique in the network. • Point to point topology: IEEE 802.15.4 devices can form an ad hoc network. This standard does not define how to route data between nodes hence there must be a network layer implementator who is in charge of this task. Being able to route data allows the network to cover a wider area than the network topology but the power consumption is increased. 60.2.4.4 State of the Art Recent publications in this area are in Table 60.5 and the sensors used are in Table 60.6. Two of the three publications focus on fall detection [22,41] and the other is a monitoring system [21]. It is important to mention that it is a common mistake to consider that IEEE 802.15.4 and ZigBee are the same, that is, Ref. [22]. As it will be presented next, the ZigBee is implemented over IEEE 802.15.4 in a different manner and with different characteristics. The monitoring system described in Ref. [21] is composed by three different sensors, accelerometer, ECG, and saturation of peripheral oxygen (SpO2). Sensors are located into a chest band (accelerometer and ECG) and a wristband (SpO2). Although three different measures are acquired, the system is designed for general monitoring without a specific aim. References [22,41] present two systems for falling detection using a triaxial accelerometer. In Ref. [41], the information provided by the accelerometer is complemented with passive infrared (PIR) motion detectors. All three publications implement star topologies as they connect more than a sensor with a PAN coordinator. Star

PAN coordinator Full function device

Figure 60.2 Topologies IEEE 802.15.4.


Point to point

Reduced function device

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Wireless Sensor Networks in Health Table 60.5 Recent Publications on IEEE 802.15.4 Reference

Health Focus

Sensors

Battery Life

Chung et al. [21] Dinh et al. [22] Srinivasan et al. [41]

Monitoring Fall detection Fall detection

Accelerometer, ECG, SpO2 Accelerometer Accelerometer

N/A N/A N/A

Table 60.6 Sensors Used with IEEE 802.15.4


Sensors Chung et al. [21]

SpO2, ECG, Accelerometer

Dinh et al. [22] Srinivasan et al. [41]

Accelerometer Accelerometer PIR motion detectors

Nonin OEM III module [12] Conductive fabric electrode MMA7260Q, Freescale [10] ADIS16350/ADIS16355 iSensor [4] N/A N/A

60.2.5 IEEE 802.15.4/ZigBee ZigBee is a specification set built for IEEE 802.15.4 protocol. ZigBee naming is derived from the waggle dance of honeybees after their return to the beehive. ZigBee is designed to provide connectivity between high-efficiency devices with a reduced packet load. The aim of the standard is to offer low power consumption even if the bandwidth and range have to be sacrificed. It is mainly used in industrial control systems, embedded sensors, and healthcare. These applications benefit from the low node capacity and sleep modes. At this mode, power consumption is highly reduced. ZigBee is promoted by ZigBee Alliance, an international community supported by more than one hundred companies (Motorola, Mitsubishi, Phillips, Samsung, Honeywell, Siemens, etc.). Because ZigBee is built using IEEE 802.15.4, it shares frequency, range, and bandwidth as described in the previous section. 60.2.5.1 ZigBee Devices There are three different types of ZigBee devices with differing roles in the network: • ZigBee coordinator (ZC): There must be one coordinator per network. It is in charge of controlling the network. • ZigBee router (ZR): Connects separate devices in the network topology. It also provides a user application layer. • ZigBee end device (ZED): End devices transmit information to ZR or ZC devices; they cannot route data (IEEE 802.15.4 RFD). 60.2.5.2 Topologies There are three topologies defined for ZigBee networks, shown in Figure 60.3: • Star topology: The communication is established between a central device and the other ZigBee devices, powered by batteries. This central device is called a PAN coordinator and it is unique in the network. • Mesh topology: It is similar to the star topology. The difference between them is that any device can connect with other device, not just the PAN coordinator.


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Medical, Biomedical, and Health Star PAN coordinator Reduced function device Full function device


Mesh

Cluster tree

Figure 60.3 ZigBee topologies.

• Cluster tree topology: Cluster tree is a special scenario for a mesh topology where most of the devices are IEEE 802.15.4 FFD, and RFDs are connected to the network as leaves at the end of each branch. One of the IEEE 802.15.4 FFD is the PAN coordinator and the others can provide synchronization and coordination services. 60.2.5.3 State of the Art ZigBee is one of the most popular transmission technologies in WSN in health. Its low power consumption increases the battery life of the systems. Table 60.7 summarizes the recent implementations that use this standard.

Table 60.7 Sensors Used with IEEE 802.15.4/ZigBee Reference

Health Focus

Campo and Grangereaw [20]

Fall detection

Kim et al. [28] Lai et al. [29]

Respiratory rate monitoring Fall detection

Lee et al. [32] Lee et al. [30]

Monitoring Monitoring

Lee et al. [33]

Fall detection

Lou et al. [37] Lou et al. [36] Morris [et al. 39]

Scoliosis monitoring Scoliosis monitoring Body fluids analysis


Sensors Accelerometer Global positioning systems (GPS) EMFi Ballistocardiogram Accelerometer Gyroscope ECG PPG Accelerometer ECG Accelerometer Force transducer Force transducer pH Sodium

Battery Life

Device

15 days

ADXL202 Analog Devices [5] SAM-LS U-BLOX

N/A

N/A N/A DEAMCC3D Design Engineering [9] IDG300 InvenSense [1] N/A BIOPAC systems [7] KXM52 series N/A ADXL33 Analog Devices Honeywell FSO 1 [3] Honeywell FSO 1 [3] N/A N/A

N/A 24 h N/A 10 h 8 months 130 days N/A

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Fall detection applications [20,29,33] are similar to the ones presented in the previous section. Falls are detected using an accelerometer but there are additional sensors that provide extra information in some cases. Global positioning system (GPS) [20] for location and ECG in Ref. [33] are collected for cardiac abnormality detection. Monitoring is another typical focus on the application of WSN in health. References [36,37] are two interesting research papers about scoliosis monitoring. The trials of 24 h of continuous monitoring for 4–6 months are challenging to battery life of the sensors. At this point is where ZigBee shows its potential. Patients have to wear the sensors for long-time monitoring. As comfort is one of the main advantages of using WSN, patients shouldn’t have to recharge sensors batteries quite often. Low power consumption of ZigBee becomes an important factor at these types of applications. Other monitoring systems measure parameters such as respiratory rate [28], ECG [32], pulse wave signals [30] and bloody fluids analysis [39]. The battery life of these systems is important. Table 60.7 shows that there are ZigBee systems that can work continuously for more than a week [20] or even months [36,37]. Sensors used in these publications are also presented at Table 60.7. 60.2.5.4 Proprietary Solutions Even if the most popular transmission technologies presented earlier are used extensively, there are other solutions where proprietary technologies are used as listed in Table 60.8. Some publications that use proprietary solutions are discussed later. A radiotelemetry capsule is used to monitor pH, pressure, and temperature of the intestinal track [19]. The transceiver operates at the license-free 433.92 MHz industry, ISM band. It uses a frequency with ranges between 1 MHz and 1 GHz to avoid energy attenuation in human tissues. It covers a distance of about 2 m and has a battery life over 180 h. A low-power wireless acquisition module is used within wearable health monitoring systems and ambient assisted living (AAL) applications [23]. The measures are acquired by three different sensors, ECG, accelerometer, and thermometer, but it does not aim to provide a specific solution. It focuses on general-purpose monitoring. The communications on this module is via a Toumaz Sensium system on chip (SoC) [16]. This solution operates at 868 MHz avoiding the ISM band because it is overly crowded. The battery life is high, over 90 h. An example of fall detection system that implements a wireless proprietary solution is in Refs. [34,35]. The sensor used in this system is the usual one for fall detection, an accelerometer. The communication protocol in the link layer uses ShockBurst [13]. ShockBurst technology permits a low-cost microcontroller with a bit rate of 1 Mbit/s. ShockBurst technology is also used in Ref. [25], a data acquisition system for diabetic and cardiac monitoring. Sensors used in these publications are presented at Table 60.8.

Table 60.8 Sensors Used with Proprietary Technologies Reference

Health Focus

Sensor

Biao et al. [19]

Monitoring intestinal motility

Figueiredo et al. [23]

Monitoring

Lee et al. [34] Lee and Lee [35] Harvey et al. [25]

Fall detection Fall detection Monitoring

Pressure Thermometer pH ECG Accelerometer Thermometer Accelerometer Accelerometer Glucose meter


Battery Life 180 h

90 h

N/A N/A N/A

Device N/A N/A N/A N/A LIS302DL, STMicroelectronics N/A ADXL202, Analog Device [5] ADXL202, Analog Device [5] OneTouch Ultra 2, LifeScan [11]

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60.3 Conclusion Several challenges need to be overcome to enrich the current implementations of WSN [45] in health applications. However, as presented in this chapter there are numerous implementations of WSN for health. The main applications focus on fall detection and general monitoring systems. It has been observed that IEEE 802.15.4 provides high battery life for WSN giving longer operational times and the ZigBee power consumption is much lower than Bluetooth. In order to compare, the power consumption for IEEE 802.15.1 has been tested on a BlueCore2 and for IEEE 802.15.4 on a CC2430. Results are presented in Table 60.9, which shows that IEEE 802.15.4 power consumption is significantly smaller than Bluetooth both for transmission and reception. It is important to point out that the end devices in IEEE 802.15.4 networks can enter sleep modes, reducing their power consumption. In order to provide network transmission capabilities, they are usually attached to motes or a custom board. Many different kinds of sensors have been used but some of them are not medical sensors, accelerometers, gyroscopes, etc. The sensors have not a smart status, which means they are not able to connect by themselves to a WSN. In order to provide them with network transmission capabilities they are usually attached to motes or a custom board. In this chapter, it has been shown that there are several standards available in applications. But it is important to understand that the lack of any standard for the format of the data to be transmitted turns these solutions into isolated systems. The problem is the interoperability issues that reduce opportunities for integration in different platforms. A recent standard, IEEE 1451 [17], describes a set of open, common, network-independent communication interfaces for connecting transducers; it is not restricted to a single transmission technology, being able to operate with the most popular ones (ZigBee, Bluetooth, etc.). Other proposals use the X73, ISO/IEEE11073 standard, also defined by IEEE, which was originally designed to provide connectivity between medical devices.

Acronyms AAL BAN ECG EEG EOG FFD FHSS GPS HCF ISM MAC

ambient assisted living body area network electrocardiogram electroencephalography electrooculography full function device frequency hopping spread spectrum global positioning system hybrid coordination function industrial scientific medical medium control access

Table 60.9 IEEE 802.15.4 and IEEE 802.15.1 Power Consumption Standard Chipset VDD (V) TX (mA) RX (mA) Bit rate (MB/s)


IEEE 802.15.4

IEEE 802.15.1

CC2430 3.0 24.7 27 0.25

BlueCore2 1.8 57 47 0.72



LR-WPANs PAN PHY PPG RFD SpO2 TDMA UWB WLAN WPAN WSN ZC ZED ZR

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low-rate wireless personal area network personal area network physical layer photoplethysmography reduced function device saturation of peripheral oxygen time division multiple access ultra wide band wireless local area network wireless personal area network wireless sensor network ZigBee coordinator ZigBee end device ZigBee router

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