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Journal of Medical Engineering & Technology
ISSN: 0309-1902 (Print) 1464-522X (Online) Journal homepage: https://www.tandfonline.com/loi/ijmt20
Wireless body area network for health monitoring
Bahae Abidi, Abdelillah Jilbab & El Haziti Mohamed
To cite this article: Bahae Abidi, Abdelillah Jilbab & El Haziti Mohamed (2019) Wireless body area network for health monitoring, Journal of Medical Engineering & Technology, 43:2, 124-132, DOI:
10.1080/03091902.2019.1620354
To link to this article: https://doi.org/10.1080/03091902.2019.1620354
Published online: 18 Jun 2019.
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RESEARCH ARTICLE
Wireless body area network for health monitoring
Bahae Abidi
a, Abdelillah Jilbab
band El Haziti Mohamed
ca
LRIT - CNRST URAC no 29, Rabat IT Center, Faculty of Sciences, Mohammed V University, Rabat, Morocco;
bENSET, Mohammed V University, Rabat, Morocco;
cHigh School of Technology, Mohammed V University, Rabat, Morocco
ABSTRACT
A Wireless Sensor Networks (WSNs) consists basically of a group of nodes, that communicate with each other through a wireless transmission, and does not need any existing infrastructure.
The recent developments in technology and wireless communication, to be used in various applications, foster the development of Wireless Body Area Networks (WBANs). They are emerg- ing as important networks in order to reduce the need for patients, and to help the elderly and chronically ill people to live an independent life. In this paper, we propose a routing protocol for wireless body area networks, to transfer data in the network with minimum energy con- sumption, and longer network lifetime through multi-hop communication. The proposed proto- col has been verified by performing simulations, and the obtained results show that our routing protocol ensures a robust optimisation of the energy consumption which helps to increase the lifetime of the network and its stability.
ARTICLE HISTORY Received 11 June 2018 Revised 18 April 2019 Accepted 28 April 2019 KEYWORDS
Wireless sensors network;
wireless body area network;
energy consumption;
routing protocol; gateway body sensor; network lifetime; energy efficiency
1. Introduction
A Wireless Sensor Networks (WSNs) [1] refer to a group of dispersed nodes, every node is connected to one or sometimes to several sensors; depending on the topology of the network [2]. These nodes are dedi- cated for monitoring and recording the physical condi- tions of the environment and organizing the collected data at a central location, each node is small, light- weight and portable. A sensor network has typically several parts. The parts which form the sensor node are sensing unit, processing unit, communication unit and power supply unit. In WSN, the sensor nodes deployment can be random, regular or mobile to pro- duce a high quality of information. The network uses a routing protocol, to send the captured data from dif- ferent nodes at the destination. Routing [3] consists of forwarding data from source to the final destination, the route between extremities is determined by many techniques relatively to the used application. For WSNs, many routing protocols are developed, it is a system of digital rules for exchanging data between all the nodes in the network, and achieves it to the final destination with an energy efficient manner.
The small sizes of sensors, their availability [4] and the microsensors decreasing cost have expanded the sen- sor networks application ’ s domains such as: smart
homes, video surveillance, air traffic control, robot control, industrial automation and medical device monitoring. Application in medical context needs operation at low power consumption. It is one of the most important constraints, each node must operate at reasonable temperatures because their batteries are very sensitive to the rise in temperature and each exceeding in temperature leads to reduce the life expectancy. The second constraint is related to the quality of information sent by the network, the patient ’ s state is primordial and any error can be harmful. Biomedical sensors are used in health moni- toring applications, this would have a radical impact on the patients quality of life and treatment success rates. The application of Wireless Sensor Network in Biomedical is also called Wireless Body Area Networks (WBANs). They are a new emerging subfield of wire- less sensor network, where wireless sensors are placed inside or around the human body, the use of wireless body area network technology reduces the expendi- tures of patient in the hospital.
This paper proposes a design of health monitoring routing protocol which aims to monitor the health of patients to facilitate their daily lives and that by avoid- ing their displacement each time to the hospital. Also, it can help to reduce the unexpected deaths caused for example by the heart attacks. All that, taking into
CONTACTBahae Abidi bahae.abidi@gmail.com LRIT - CNRST URAC no 29, Rabat IT Center, Faculty of Sciences, Mohammed V University, Rabat 10500, Morocco
ß2019 Informa UK Limited, trading as Taylor & Francis Group https://doi.org/10.1080/03091902.2019.1620354
consideration the energy available in each sensor to minimise the energy consumption. As an extension from the previous work in [5] different biosensors are deployed on the human body at fixed places, accord- ing to each biosensor function, we have also the use of the gateway body sensor to maximise our network lifetime. We have two types of reporting data, the crit- ical data are transmitted directly to the gateway body sensor, and other data through cluster head which aggregates all the received data, and sends it to the gateway body sensor which in turn forwards all received data to sink.
The remainder of this paper is organised as follows;
Section 2 introduces the wireless body area network, followed by the proposed protocol in Section 3.
Section 4 discusses the experimental results. Finally, in Section 5 conclusion is summarised.
2. Background and motivation
Wireless Body Area Network (WBAN) [6], is a new gen- eration of wireless sensor networks. These networks composed of tiny biomedical nodes, dedicated to ensuring monitoring patients vital parameters.
Because there is a critical need for more cost-efficient solutions for supervision, and monitoring patients dur- ing and after surgery, as well as when the patient is at home. A WBAN [7] consists of low power devices operating on, in or around the human body, to serve a variety of applications including medical. Although, WSNs and WBANs share many difficulties; such as miniaturisation. The main challenges in terms of research remain in the biomedical and healthcare
monitoring application. Indeed, the evolution of WBANs [8] should follow the increasing development in the medical domain. The main objective is to ensure a constant patient monitoring at home or work.
2.1. Sensor type
The WBAN [9] can be medical or non-medical. The medical WBAN can be relegated as wearable WBAN and implantable WBAN, and thereafter. WBAN have three nodes types:
Implantable node, are those nodes that are placed inside the human body just below the skin.
Body surface nodes, are those nodes that are placed on the surface of the human skin.
External nodes, which do not have any contact with the human skin.
Concerning the non-medical WBAN, they can be classified in five subcategories, the real-time stream- ing, the entrainment application, the emergency, the emotion detection and the secure authentication.
Figure 1 shows a typical system architecture, made up of three main parts, the first one is the WBAN where wireless sensors are placed in, on or around the human body to sense the necessary changes in the health of the patient and reduce patient expenditure in the hospital. This wireless sensor is composed of nodes capable of performing some processing, gather- ing sensory information and communicating with other connected nodes in the network to achieve the
Figure 1. Architecture of Wireless Body Area Network.
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information to their final destination called sink. The second part is the Personal Server (PS), that keep data, it uses access point (internet, Zigbee, Bluetooth … ) to transfer data to the third part, the Medical Server (MS) serving for the doctors health monitoring.
2.2. Networking issues
Some implementations for WBANs use Bluetooth (IEEE 802.15.1), but this type has a complex protocol stack and high energy consumption compared to IEEE 802.15.4, therefore, more current implementations of WBANs use IEEE 802.15.4 or Zigbee as enabling tech- nology, but it is not the best solution for supporting the communication in WBANs it can be used for a quick and easy implementation. To focus on low power devices and operation on, in or around the human body, a study group of IEEE called IEEE 802.15.6 has been launched in November 2007 for the realisation of the international standardisation [10] for WBANs. This last established the first draft of the com- munication standard of WBANs in April 2010, the approved version of the IEEE 802.15.6 standard was ratified in February 2012. The purpose of this group is to establish a communication standard optimised for low power and high-reliability data communication.
Wireless body area networks are used to collect important data during a particular activity, it will be able to deliver health care services to patients not only in the hospital and medical centres but also in their homes and workplaces. So, it will help to solve the conflict between resources and needs and facilities the social stability, who make easy the communication and relation between patients and doctors, the doc- tors can ensure the monitoring of many patients in the same time. Design of miniaturised, low power, reli- able and wearable sensor nodes devices is the key requirement of a WBAN design.
As it is mentioned before, the energy consumption in WBANs is a crucial issue [11], especially in implanted biosensors, since they are inaccessible and difficult to replace. In [12], Chen et al. introduced an interference-aware WBAN, that continuously monitors vital signs of multiple patients and efficiently prioritise data transmission based on the patient ’ s condition. In 2010 [13], Su-Ho et al. suggest a heuristic adaptive routing algorithm for an energy efficient configuration management which, can reduce energy consumption while guaranteeing the quality of service (QoS) for the emergency data in Wireless Body Sensor Networks (WBASNs). The priority and vicinity of the nodes are taken into account, for the selection of reachable
parent nodes when, the nodes are disconnected due to the mobile nature of human body.
So, different energy efficient routing schemes are used to forward data from body sensor to medical ser- ver and classified into several categories such as:
2.2.1. Cluster-based routing protocol
In 2007 [14], Watteyne et al. proposed a protocol named AnyBody which, is a self-organisation protocol comprising of sensor nodes, grouped into clusters. It focuses on relaying data via cluster heads to improve the routing and energy efficiency. In 2006 [15], Otto et al. describe a prototype system for continual health monitoring at home. The system consists of an uninterrupted WBASN and a home health server. The WBASN monitor user ’ s heart rate and locomotive activity and periodically, upload timestamped informa- tion to the home server. The home server may inte- grate this information into a local database for user ’ s inspection or it may further forward the information to a medical server. Qing et al. [16] proposed and evaluated a new distributed energy-efficient clustering scheme, which is called DEEC. DEEC lets each node expend energy uniformly by rotating the cluster-head role among all nodes. In DEEC, the cluster-heads are elected by a probability based on the ratio between the residual energy of each node and the average energy of the network. The round number of the rotating epoch for each node is different according to it ’ s initial and residual energy.
2.2.2. Cross-layered routing protocol
Wang et al. [17] proposed a distributed WBASN for
medical supervision. The system consists of three
layers: the first one is the sensor network which collect
data, the second layer is mobile computing network
who is responsible for demonstration and reveal the
data and the third layer is the remote monitoring net-
work who stores the vital information; such as electro-
cardiogram (ECG), blood oxygen, body temperature
and respiration rate. The system demonstrates many
advantages; such as low power, easy configuration,
convenient carrying, and real-time reliable data. Yang
and Rhee [18] developed a wearable photoplethysmo-
graph (PPG) biosensor in the form of a ring, as an art-
icle of clothing. A ring is more likely to be worn
continuously, making it suitable for continuous moni-
toring applications. Asada et al. further refines the
design of the ring sensor in order to ensure that the
quasi-periodic signal which is called PPG signal output
is more resistant to noise components, due to motion
artefacts and changes in ambient light levels [19].
Also, they have sought to reduce power consumption by using a high frequency, low duty cycle modulation scheme. Gill R. Tsouri et al. propose augmented effi- ciency for global routing in WBSNs [20]. It is a new link cost which is designed for balanced energy con- sumption across the network. This causes a substantial increase in the network lifetime with minimal per bit energy consumption. Balanced energy consumption means all sensors equally consume energy and as minimum as possible.
In addition, there is a new cross-layer communica- tion protocol for WBSNs called Cascading Information Retrieval by Controlling access with Distributed slot Assignment (CICADA), the goal of this protocol pro- posed by Latre et al. [21] is to create a wireless multi- hop network by means of a spanning tree that is set up autonomously. A control cycle and data sub-cycle were used collectively to achieve low delays and bet- ter energy efficiency while preserving network flexibility.
2.2.3. Qos aware routing protocol
Abebneh et al. [22] proposed Energy Balanced Rate Assignment and Routing protocol (EBRAR) for WBSNs.
EBRAR is an energy efficient routing protocol, in which, routing is based on the residual energy of the sensors. Therefore, instead of one fixed path, data is intelligently sent via different routes which balance the load on sensors. Razzaque et al. use a localised multi-hop routing technique in WBSNs [23]. This protocol ensures homogeneous energy dissipation rate for all the sensors in the network. Moreover, the proposed protocol facilitates the system with custom- ised Qos achievement and it is important to note that the sensors generated data is used to categorise the services. Ahmed et al. use a hybrid approach for improving network energy efficiency [24]. This hybrid approach combines two communication modes; single hop and multi-hop. The leading one is used for emer- gency data transmission to sink and the lagging one is used for the transmission of normal data to sink.
Quwaider et al. developed a protocol tolerant to net- work changes [25]. They proposed a store and forward method that maximises the likelihood of a packet reaching its destination. Each packet is stored by mul- tiple nodes and retransmitted, but energy efficiency was the major problem. One solution to this problem was proposed by Ehyaie et al. [26]. It consists of using dedicated, nonsensing, relay nodes with larger power sources to increases the network lifetime. This method was further improved by Maskooki et al. [27], where
body movement, such as hand motion while walking or running, was utilised to achieve network lifetime improvement. The approach requires additional hard- ware and a line of sight between various network components, which limits nodes positioning on the body. Furthermore, a recent work by Quwaider et al.
develop a routing method based on body posture [28]. The authors proposed a delay tolerant routing protocol and compared it with various rout- ing schemes.
2.2.4. Temperature-aware routing protocol
Javaid et al introduce Adaptive Threshold-based Thermal-Aware Energy-efficient Multi-hop Protocol (M- ATTEMPT) [29], this protocol supports mobility of the human body with energy management. To save energy, sensor node increases and decreases their transmission range for single hop and multi-hop com- munication. If two routes are available then route with less hop counts is selected, if two routes have the same hop-count then route with less energy con- sumption to the sink is selected.
Despite the great success of WBANs, many prob- lems still remain open, for example, the problem of variation in size and shape of the body and different composition of skin, fat, muscle and bone tissues could impose a major influence on the simulation results. We have also, the biosensors used in the net- work have to receive, transmit, idle and sleep depend- ing on the network topology and each node role, all these operations consume energy from the battery of biosensor, and we have to handle these operations in order to increase the lifetime of our network.
3. Protocol overview
In this section, we propose new routing protocol called Wireless Body Area Network (WBANP). In WBANP, data will reach the final destination in multi- hop manner, the sensors are deployed in the human body, but it is difficult to frequently reload or replace them. Our wireless body area network minimises the energy consumption of sensors, and maximises the lifetime of the network, to improve the network stabil- ity. We introduce the gateway body sensor concept that serves as an access point between different sen- sor nodes and the sink, it has to collect data from dif- ferent other nodes and then transfer them to a sink.
The description of the WBANP is explained in details in the following subsections.
JOURNAL OF MEDICAL ENGINEERING & TECHNOLOGY 127
3.1. Network model
In this work, eight biomedical sensors on the human body are deployed; to capture the patient health changes according to each biomedical sensor, there- after convert it into electrical signals to be conveyed to the medical server, in order to avoid patient dis- placement every time to the hospital. All the biomed- ical nodes have equal energy and computation capabilities. There are two types: periodically monitor- ing sensor and threshold monitoring sensor. In the threshold monitoring sensor, when a specific threshold level is reached, the data must be transferred immedi- ately, for example, the data is transferred when the value for low temperature for human body is set to 35
C, while the high-temperature level is set to be 40
C, where patient is in critical situation. For the Glucose biosensor, the low critical level is 110 mg/dl, and the highly critical one is 125 mg/dl, these parame- ters illustrate the conditions of the diabetes of the patient and ensure the patient monitoring because in the critical situation the doctors will be alerted.
Concerning the periodically monitoring sensor, the biomedical sensors periodically monitor the parame- ters of pulse rate, blood pressure, heart rate, toxin level and motion. The new aspect of the proposed topology is the use of the gateway body sensor to reduce the energy consumption, all the sensors com- municate with the sink via the gateway body sensor, this gateway body sensor aggregates all received data and sends it to the sink, so it possesses higher energy resources than the other body sensors and its attached on patient ’ s chest.
3.2. The steps of system
The wireless body area network has typically a low power in the biosensors, which are required to work as long as possible. Therefore, the energy efficiency is the key requirement for such network; in order to maximise the network lifetime. Thus, for a reliable data routing path, the routing protocols should select the minimum distance path defined as the minimum physical distance between the biosensors. The first step in the proposed system consists of the biosensors deployment according to their functionality, it is a medical decision not an automatic algorithm decision.
Each biosensor is characterised by a node ID, type, location on the body and initial energy Eo. We pro- pose a multi-hop routing protocol to save energy, with the use of the gateway body sensor and the clus- ter head. The election of the cluster head is done in each round, we calculate a specific function, and on
the basis of this function each node decides whether to become cluster head or no. A node with a max- imum value of calculated function becomes a cluster head. That means a node that has a minimum dis- tance (D) to gateway body sensor and maximum energy (E). All other nodes depending on their type transmit data to cluster head, which routes data to gateway body sensor that aggregates and sends data to the sink.
3.3. Energy model
A multi-hop communication was adopted to reduce the energy consumption in our network, the data was sent to the sink through the gateway body sensor, the main idea is to combine data from different sensors to eliminate redundant transmission and reduce the number of data transmitted, because a large part of energy is lost during the transaction of reception and transmission. The energy consumption transmission model is as follow:
E
txð k; d Þ ¼ k E
elecþ k E
ampd
m(1) This equation has highlighted two components of energy. The first term reflects the energy consumed by the radio and the second term presents the energy consumed by the amplifier and depends on the dis- tance between the transmitter and the receiver.where, E
tx: is the energy consumed in transmission, E
elec: is the energy expended to transmit or receive one bit data, E
amp: is the energy required for amplifier circuit, k: is the packet size, d: is the distance between trans- mitter and receiver, m: the human body path loss exponent and to receive the message, the radio expends:
E
rxð Þ ¼ k E
eleck (2) where, E
rx: is the energy consumed by receiver.
3.4. Protocol operation: the communication flow
Sensing, reception, aggregation, processing and trans-
mission are the main sensor nodes operations in the
network, according to their type and energy. In the
WBANP design, the most important issues to be con-
sidered are the low power consumption, and the net-
work should be a scalable one. The WBANP assures
monitoring of the patient, so, the biosensors capture
all important data, send it to the gateway body sen-
sor, which in turn collects the data and then transfer
that information to a suitable destination.
This sequence of steps can be assembled in a flow- chart as it is shown in Figure 2. The flowchart shows how the data flows from the source to the sink, in function of the number of rounds.
4. Experimental results and discussions
In this section, we evaluate the performance of the WBANP presented in the previous section by simula- tion. The main goal of this work was to develop a routing protocol for wireless body area networks in order to transfer data in the network with minimum energy consumption and longer network lifetime.
We compare our scheme with two other protocols presented in Section 2, DEEC and ATTEMPT proto- cols [30], the simulations were performed using
Matlab R2012a 32 bits simulator. The processing is done in Intel i5-2450 at 2.5 GHz CPU, with 4 GB RAM to study the performances networks. In our simulation, to monitor the health of the patient, 8 biomedical sensors collect the patient physiological data (such as blood, pulse, ECG … ) implanted in a body without any move. In our scenario 2- dimensional field 1.8 m by 0.8 m was defined, taking into consideration that all nodes are fixed according to a specific (x,y) defined, with initial energy Eo ¼ 0.5 J. The gateway body sensor is attached on the patient ’ s chest. The simulation parameters are presented in Table 1. All the protocols have been simulated for the same radio model of the nodes and depending on our parameters, so that, their results can be compared.
Figure 2. WBANP Flowchart.
JOURNAL OF MEDICAL ENGINEERING & TECHNOLOGY 129
In order to evaluate the performance and efficiency of our protocol, we use the following metrics.
4.1. Alive node
Minimising the energy consumption is the first con- straint in wireless body area network, and it is critical to satisfy, the first metric adopted to measure the per- formance of our algorithm is the number of alive nodes per round, called also, the stability period. It defines how long all the nodes in the network are alive, it is necessary that all the sensor nodes stay alive as long as possible during our simulation. The number of rounds is considered as the key parameter of the network lifetime, in each round or iteration, all the operation process of our system are done until the end of the number round determined during the initialisation of our algorithm. In this subsection, to verify the WBANP protocol effectiveness, a perform- ance comparison with DEEC and ATTEMPT is done.
Figure 3 illustrates the number of alive nodes per rounds of the three algorithms. It is shown that all the nodes in WBANP still have energy until the round 4900, then in round 4991 the graph cognise a little variation due to the first node dies, whilst, for ATTEMPT protocol, the nodes lose their energy early, so the graph is no longer stable because in round 2200 the first node dies. Finally, DEEC protocol keeps all the nodes alive until the round 3800. Therefore, based on the obtained results in Figure 3 the WBANP protocol provides longer stability.
4.2. Residual energy
In this subsection, the residual energy has been chosen as criteria of analysis; in order to analyse the performance of the network. To transfer the data to the sink, the proposed multi-hop topology uses differ- ent steps in each round to save energy. The average energy consumed in each round is presented in Figure 4. The simulation results show that our WBANP performs well and consumes minimum energy till 65%
to 70% of simulation time, which represented around the round 4800. It means that in the stability period, more nodes have enough energy, so they transmit
more data packet to the sink even if the ATTEMPT approach reduces the energy consumption.
From the results of experiments, we can find that the WBANP always has presented the best results in all metrics. We concluded that WBANP performs better in the wireless body area network energy consump- tion and extend the network lifetime than DEEC and ATTEMPT protocols.
5. Conclusion
Routing protocols for wireless body area network pro- vide an excellent infrastructure for data transmission and present a lot of advantages in terms of energy consumption and network ’ s lifetime. In this paper, we have dealt with the key challenges of these networks;
the problem of energy. We proposed in this work an efficient new protocol for wireless body area network, Table 1. Simulation parameters.
Parameters Value
Size of network 1.80.8 metre
Number of sensors 8
Deployment Fixed Sensors
Gateway location 10.45 metre
Initial Energy 0.5 joules
Number of Round 8000
Figure 3. Number of alive nodes per rounds.
Figure 4. Residual Energy.
with the use of the gateway body sensor, in order to route data to their final destination. In such network, the most important constraints are operating at low energy consumption and the quality of information sent in the network. We compared our scheme with some existing methods in the literature such as DEEC and ATTEMPT protocols and showed satisfactory results in terms of network ’ s stability and lifetime.
Due to the cooperative characteristics of the wire- less body area networks, future work will focus on the study of the cooperation between nodes in order to improve system performances.
Disclosure statement
The authors declare that there is no conflict of interest regarding the publication of this paper.
ORCID
Bahae Abidi http://orcid.org/0000-0002-9403-2235
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