Analyzing the Impact of Body Postures and Power on ... · for the remote sensing of physiological parameters of the human body. The diﬀerent body postures impact the connectivity

Procedia Computer Science 32 ( 2014 ) 894 – 899

1877-0509 © 2014 Published by Elsevier B.V. Open access under CC BY-NC-ND license. Selection and Peer-review under responsibility of the Program Chairs. doi: 10.1016/j.procs.2014.05.508

ScienceDirectAvailable online at www.sciencedirect.com

The 2nd International Workshop on Body Area Sensor Networks (BASNet)

Analyzing the Impact of Body Postures and Power on

Communication in WBAN

Anum Talpura, Natasha Balocha, Nafeesa Bohraa, Faisal Karim Shaikha,b,∗, EmadFelembanb

aDepartment of Telecommunication Engg., Mehran University of Engineering and Technology, Jamshoro, PakistanbScience and Technology Unit, Umm Al-Qura University, Makkah, Saudi Arabia

Abstract

Wireless Body Area Network has become emerging technology to improve the health care and provide a cost effective solution

for the remote sensing of physiological parameters of the human body. The different body postures impact the connectivity of the

network deployed over the body. The connectivity is further degraded if the power level of the radio is kept low in order to save the

precious energy of the sensor nodes. This paper aims to analyse the impact of different radio power level for various body postures

on the communication reliability. Numerous experiments were conducted using IRIS mote at different power levels to monitor the

communication reliability with respect to different postures and movements of the body.c© 2014 The Authors. Published by Elsevier B.V.

Selection and peer-review under responsibility of Elhadi M. Shakshuki.

Keywords: Wireless Body Area Network, health monitoring, power levels, body postures

1. Introduction

Recent advances in Wireless Sensor Networks (WSNs) has evolved new era in the field of health monitoring

and fitness. This leads toward the evolvement of Wireless Body Area Network (WBAN) where the physiological

parameters of human body such as Blood Pressure (BP), Electrocardiogram (ECG), and Electroencephalogram (EEG)

are monitored and collected on the base station (BS). The collected data is then transmitted to the medical server

for further analysis by the medical practitioners. The prime objective of WBAN is to collect information about

the physiological parameters of the patient, therefore, there is a strict requirement of reliable transmission that also

consumes low power due to limited battery resources of sensor nodes. Variety of Radio Frequency (RF) standards are

available that can be used with WSNs but recently for WBAN, IEEE 802.15.4 standard is gaining momentum due to

its inherent features of very low power consumption, flexibility in moving devices and low data rate1.

Typically, a WBAN involves one BS and number of sensor nodes that can be configured in star, peer-to-peer, cluster

or tree topologies in order to transfer the data on the body1. In order to minimize interference and to cope with health

∗ Corresponding author. Tel.: +92-22-277-2277 ; fax: +92-22-277-1382.

E-mail address: [email protected]

© 2014 Published by Elsevier B.V. Open access under CC BY-NC-ND license. Selection and Peer-review under responsibility of the Program Chairs.

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895 Anum Talpur et al. / Procedia Computer Science 32 ( 2014 ) 894 – 899

nodeID = 1

nodeID = 2

nodeID = 3

nodeID = 4

nodeID = 5

nodeID = 6

nodeID = 7 nodeID = 8

base

station

(a)

(b)

(c)

(d)

Fig. 1. Data collection scenario(a) Node positions (b) Sitting (c) Walking and (d) Sleeping postures

concerns, an extremely low transmit power is needed for a node2. Generally, the human body remains in constant

motion hence, it can alter the position of sensor nodes. These sudden changes can drop connectivity of the nodes

with the BS and therefore no data will be transferred between the sensors and the BS. This paper focuses on constant

monitoring of patients, hence power and connectivity failure cannot be tolerated. Therefore, a network is designed in

such a way that on one hand it should transport the data with reliability using minimum power consumption while on

the other hand it should be robust against postural changes.

The rest of the paper is organized as follows. Sec. 2 describes the related work. Sec. 3 proposes the methodology

and its implementation on IRIS motes. Sec. 4 evaluates the results and Sec. 5 concludes the contribution of the paper.

2. Related Work

WBAN has been investigated in several contexts with different objectives such as wireless channel conditions,

medium access protocols and impact of payload length3,4,5,6,7. The issues related to the power control of the sensor

nodes is addressed in8,9,10 by considering both the single and multi-hop topologies. However, due to different body

postures the communication of a WBAN will be rapidly changing and this phenomenon is not considered much in

the related work. In11 number of different power levels have been investigated which can be effectively controlled

by power control algorithm in an indoor wireless environment. Furthermore, in12,13 an adaptive radio transmit power

controls have been investigated in terms of energy saving. Here different scenarios of patient’s activity have also been

experimented which shows the tradeoff between the fixed transmit power and reliability.

3. Methodology and Experimental setup

In order to analyze the impact of body postures and low radio power on data transmission in WBAN we collected

the Received Signal Strength Indicator (RSSI) readings from different sensor nodes to the BS. The experimental

setup encompasses three basic movements that are made in everyday activities, i.e., walking, sitting and sleeping.

For experiments nine IRIS motes14 are placed on the human body as shown in Fig. 1 which are programmed using

TinyOS-2.1.015. Each sensing node is labeled with unique ID from 1 to 8 respectively and the BS is assigned with

ID=0. Generally, the ability to manage the transmission power is available on most of the sensor nodes. The RF230

Atmel radio in IRIS motes provides 16 transmission levels ranging from +3dBm to -17.2dBm. In order to estimate

received power for each body movement for different transmit power levels the power of the radio is tuned accordingly.

The packets generated by sensor node are transmitted to the BS using broadcast from where they are passed to the PC


using serial interface. The packet generated by each node is uniquely identified from its node identity. The received

packets from the different nodes contain the RSSI value of respective sensor node. The data rate of each sensor node

is one packet per second. The RSSI readings are taken at four different power levels, i.e., T X1 = 3.0dBm (maximum

power of IRIS mote), T X2 = -2.2dBm, T X3 = -17.2dBm (minimum power of IRIS mote), and T X4 = -17.2dBm

(where antenna is covered with aluminium foil). The aluminium foil is used to further degrade the channel beyond the

minimum power of IRIS mote to observe its impact on the communication. For each posture four experiments have

been performed to observe the effects of the power on data transmission.

The efficient system must utilize the lesser amount of power for transmission such that the batteries will not drain

quickly. With low power levels, prevention of link outages should also be taken into account. Therefore, number

of experiments are taken at different power levels to diagnose the lowest value of power which provides efficient

transmission of data with minimum energy utilization. Further analysis will be made to evaluate how power would be

maintained and switched for different body movements in order to avoid loss of data and maintain the transmission

reliability.

4. Experimental Results

Results are evaluated for defining what an optimal power would be for a transmitting node in order to achieve

minimum RSSI without losing data packets. The power received at BS is evaluated at different power levels and for

0 20 40 60 80 100 120−100

−50

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Number of packets

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nodeID=1nodeID=2nodeID=3nodeID=4nodeID=5nodeID=6nodeID=7nodeID=8

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Fig. 2. Walking posture (a) RSSI at T X1 (b) RSSI at T X2 (c) RSSI at T X3 (d) RSSI at T X4


different body postures where the body is moving and performing its routine tasks.

4.1. Walking

Fig. 2 shows the results achieved when a person is walking. Fig. 2(a)-Fig. 2(d) depicts RSSI values against the

number of received packets at BS. These results are evaluated when patient is walking and moving in a room back and

forth for around 2 minutes. As the person is continuously moving the distance between each transmitting node and

BS is continuously changing. For the fixed maximum transmit power of 3dBm (Fig. 2(a)), RSSI is widely fluctuating

around average values of -40dBm to -80dBm. Nodes at wrists, thigh and ankles shows poor performance (RSSI is

always less than -55dBm) as compared to nodes at chest, abdomen and head (RSSI is always greater than -55dBm)

due to more movement while walking. The overall performance of RSSI is very good due to high transmit power and

no loss in total number of received packets. Fig. 2(b) shows variation between -50dBm to -80dBm with zero percent

packet loss. This proves medium power to be more efficient for WBAN network as compared to earlier case. Further

evaluation of minimum transmit power (Fig. 2(c)) shows deviation between -70dBm to -90dBm. Fig. 2(d) depicts that

even lesser power can be used for transmission of data packets (with some losses) which will be helpful in escalating

the battery life time. There is a tradeoff between low power and data loss, if the patient’s data is of great importance

than extreme low powers are not advisable.

0 20 40 60 80 100 120

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)


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Fig. 3. Sitting posture (a) RSSI at T X1 (b) RSSI at T X2 (c) RSSI at T X3 (d) RSSI at T X4


4.2. Sitting

The RSSI and the number of received packets is reasonably good for high transmit power (Fig. 3(a)). Similarly, at

low transmit power, the packet reliability is good and efficient in terms of energy consumption (Fig. 3(c)). Observing

the plots it can be seen that at maximum and minimum power levels, the packets loss is almost zero. But for less

than minimum and medium power levels packet loss is significant. At medium power levels loss is experienced while

any node comes under the shade of anything. Therefore, in such situation a mechanism is needed that automatically

switches the power to higher level when lower level is not enough to perform reliable transportation. In Fig. 3(d)

where power is further decreased by creating losses shows that node of thigh, chest and right wrist is showing 100%

reliable transportation. Therefore, these nodes present opportunity for energy saving and can be used with very long

battery life time.

0 20 40 60 80 100 120

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Fig. 4. Sleeping posture (a) RSSI at T X1 (b) RSSI at T X2 (c) RSSI at T X3 (d) RSSI at T X4

4.3. Sleeping

In this scenario the patient sleeps down to rest for 2 minutes on a bed. During lying down in sleep position the

stability in received values of power is very noteworthy. Fig. 4 plots the RSSI over the entire period, at several

transmit levels. At maximum (Fig. 4(a)) and medium (Fig. 4(b)) transmit power levels somehow stable and 100%


packet reliability is obtained. The energy savings at less than minimum transmit power level (Fig. 4(d)) is also very

signicant due to very small amount of packet loss.

5. Conclusion

Based on performed experiments we can investigate the potential advantages of deploying an adaptive transmit

power control mechanism for a means of saving energy for WBAN networks. While evaluating above all scenarios

understanding of wireless channel strength under different patient activities can easily be examined. Packet loss is

related with RSSI for providing packet reliability with efficient data transmission. We practically proved that radio link

quality under different body movements shows a trade-off between wastage of energy and scarifying packet reliability.

Therefore, a methodology can be generated in which transmitter computes optimal transmit power depending on RSSI

calculated for each transmitted packet via feedback from the base station. In this way appropriate transmit power

would be calculated for packet data transmission.

This analysis based research proves that such a scheme can be implemented in future that provides instantaneous

knowledge of received power is back conveyed to transmitter for a selection of good choice of transmit power. An

optimal transmit power that provides efficient power utilization with very minimal chances of packet loss.

Acknowledgement

This work is partially supported by Mehran University of Engineering and Technology, Jamshoro, Pakistan and

by grant number 10-INF1236-10 from the Long-Term National Plan for Science, Technology and Innovation (LT-

NPSTI), the King Abdul-Aziz City for Science and Technology (KACST), Kingdom of Saudi Arabia. We also thank

the Science and Technology Unit at Umm Al-Qura University for their continued logistics support.

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Analyzing the Impact of Body Postures and Power on ... · for the remote sensing of physiological parameters of the human body. The diﬀerent body postures impact the connectivity