The document summarizes a research paper on forming virtual groups in wireless body area networks (WBANs) for healthcare monitoring. It describes the need for improved patient monitoring to enable timely emergency response. The proposed system uses WBANs to automatically send patient medical data wirelessly to a central server. This allows forming virtual groups between patient, nurse, and doctor devices to enable remote analysis of patient data. The system was modeled and evaluated using the NS-2 network simulator. Key findings from the simulation include the impact of packet size on throughput and delay. The system shows potential for improved emergency response by enabling real-time monitoring of high-risk patients.

1. FORMATION OF VIRTUAL GROUPS IN
WBAN FOR HEALTHCARE MONITORING
AUTHORS:
VANDANA JAYARAJ & DR. HEMANTH.C
VIT UNIVERSITY, CHENNAI CAMPUS
COMSNETS 2016 – NETHEALTH WORKSHOP
BENGALURU

2. CONTENTS
• Introduction
• Objective & Scope
• Block Diagram / Flow Diagram
• Work Flow
• Simulation & Network Statistics
• Plots
• Observation
• Conclusion

3. THE “CODE BLUE” MOMENT
• Full patient occupancy in ICU’s
• No vigilant monitoring of vitals by medical
personnel
• Manual Alert systems
• Delay in Immediate Resuscitation and
Emergency Alerts
• Loss of life due to the lack in timely
communication of data
• Issue can be solved by using WBAN’s :
– Automatically send medical data
(wireless)
– Timely update of data
– Alert and Remote analysis
– Examination based on criticality
BLS ( Basic Life Support) &
ATLS ( Acute Trauma Life
Support)

4. WIRELESS BODY AREA NETWORKS
• Operate autonomously to connect various medical sensors and
appliances
• located inside and outside of a human body
• Mobility of patients – portable devices
• Search and find a suitable communication network
• Transmits data to a remote database server for storage
• Accurate monitoring of patient’s conditions over a period of time with
high precision

5. OBJECTIVE AND SCOPE
• Address the challenge by proposing an architecture that allows
virtual groups to be formed between devices of patients, nurses
and doctors in order to enable remote analysis of WBAN data
• Used mainly in the case of emergency for efficient monitory
techniques
• Performance is analysed based on delay, packet drop, effective
delivery
• Future scope of improvement :
• Automatic alerts when crossing threshold values
• Feedback from doctor /nurse mobile node adjusting the performance
of the sensor nodes

6. VIRTUAL GROUP ARCHITECTURE
• Group Management Service (GMS)
• Medical Data Recording Service (MDRS)
• Policy Engine (PE) based on time
• WBANS on Patients
• Medical Officers Devices
• Environmental Sensors
Fig. Virtual Group Architecture adapted from [1]

7. BLOCK DIAGRAM
WBAN Sensor
Nodes
Intermediate
node
Mobile
nodes
(Nurse and
Doctor)
1
2
3
Doctor
Nurse

8. WORK FLOW
• Project is done using the tool NS-2
• TCL Script
– Used 10 nodes for simulation
– Wireless Parameters were set
– Node Configuration and Topology
– AODV Protocol used
– Packet transmission between various nodes in TCP/FTP
based on time intervals
– Ns simulation and Termination
– Execute Network Animator Nam
• AWK Scripts used to extract data from trace file
• Trace graph was used to get desired plots

9. SIMULATION
• Network Parameters
Channel Wireless
Radio Propagation Two Ray Ground
Antenna Type Omni Antenna
Link Layer Type LL
Interface Queue
type
Queue/DropTail/
PriQueue
Max Packet in
Queue
10
Network Interface
Type
Wireless
MAC type 802.11
Routing Protocol AODV
Number of nodes 10
Packet Size 2, 10, 100 , 700, 1000
Interval 0.5
Receiver Power 0.25
Transmitter Power 0.75
• NAM Output
TOPOLOGY CREATED
PATIENTS: 1 , 2
NURSES: 6 , 8
DOCTORS: 7 , 9

10. NETWORK STATISTICS
• Virtual group (patient, nurse
and doctor) is created based
on time intervals
• Packets are transmitted from
patient node 0 to doctor node
7 from 0.01 to 1.00
• From patient node 0 to nurse
node 8 at 1.05 to 2.85
• From patient node 1 to
medical records device at 2.90
to 4.00
• This cycle continues in this
order till 7.02
• Termination at 7.05

11. PLOTS
Fig. End to End Delay Vs Packet Received Time at
the destination nodes
• There is a lot of fluctuation in
delay when the received
packet time is increased
• Packet Interval time does not
affect the end to end delay of
the overall network

12. Fig 1. Throughput of Received packets for overall
network
Fig 2. Packet Size Vs Throughput of the overall
network
• During the time interval 3.0 to 5.9, the
received packet rate is high
• Packets are being transmitted from
the intermediate node to the
nurse/doctor in the virtual group
• Packet size is given as 1000, throughput
is high when the packet size is maximum
and then immediately decreases
• There is a steady increase of packets from
the source node at the time when FTP
starts and decreases when the simulation
comes to finish

13. Fig 1. Varying Packet Size Vs corresponding
Throughput with constant Packet Interval
Fig 2. Varying Packet Size and its corresponding
End to End Delay with constant Packet Interval
• Throughput is maximum with peak
value of 189 for packet size of 100
having a constant packet interval rate
• Delay is gradually increased when packet
size increases.
• Depends on the distance at which nodes are
placed

14. OBSERVATION
• Packet sizes of 2, 10, 100, 700 and 1000 were given with a constant packet
interval rate of 0.5
• Larger the packet size, more information is sent across the network, this
takes a longer time to process and transmit by the intermediate nodes.
These nodes get loaded with sudden increase in data.
• Delay is gradually increased when packet size increases.
• Depends on the distance at which nodes are placed.
• Throughput is maximum with peak value of 189 for packet size of 100 with
a constant packet interval rate
• For packet size less than or greater than 100, throughput values are lower,
because of the overheads in MAC 802.11

15. CONCLUSION
• For every time interval the data gets updated automatically.
• This architecture can be used for a large number of group
formations which will constantly allow medical personnel to
access data
• Cost effective, efficient and reliable method of transmitting
patient data
• Prioritize data as alerts/ data based on packet size
• Intermediate node takes decisions based on threshold values

16. REFERENCES
[1] Teerawat Issariyakul, and Ekram Hossain, “Introduction to network simulator NS2” Springer,
2011.
[2] Ivanov, S., Foley, C., Balasubramaniam, S., & Botvich, D. (2012). Virtual groups for patient WBAN
monitoring in medical environments. Biomedical Engineering, IEEE Transactions on, 59(11),
3238-3246.
[3] Monton, E., Hernandez, J. F., Blasco, J. M., Hervé, T., Micallef, J., Grech, & Traver, V. (2008). Body
area network for wireless patient monitoring. IET communications, 2(2), 215-222.
[4] Blessy Johny and Alagapan Anpalagan “ Body Area Sensor Networks: Requirements, Operations
and Challenges, IEEE, MARCH/APRIL 2014
[5] M.Greis, Tutorial for the Network Simulator “ns”
http://www.isi.edu/nsnam/ns/tutorial/index.html
[6] Aminian, M., and H. R. Naji. "A hospital healthcare monitoring system using wireless sensor
networks." J. Health Med. Inform 121 (2013).
[7] Wu, Winston H., et al. "MEDIC: Medical embedded device for individualized care." Artificial
Intelligence in Medicine 42.2 (2008): 137-152

17. [8] Pantelopoulos, Alexandros, and Nikolaos G. Bourbakis. "Prognosis—a wearable health-
monitoring system for people at risk: Methodology and modeling." Information Technology
in Biomedicine, IEEE Transactions on14.3 (2010): 613-621
[9] Teng, Xiao-Fei, Yuan-Ting Zhang, Carmen CY Poon, and Paolo Bonato. "Wearable
medical systems for p-health." Biomedical Engineering, IEEE Reviews in 1 (2008): 62-74
[10] Insom, P., Wongpanitlert, P., Tipsupa, J., Rakjang, K., Kaemarungsi, K., &
Watanachaturaporn, P. (2012,January).
Implementation of a human vital monitoring system using Ad Hoc wireless network for
smart healthcare. InBiomedical Engineering International Conference (BMEiCON), 2011 (pp.
76-81). IEEE.
[11] Yadav, Narendra Singh, and R. P. Yadav. "Performance comparison and analysis of
table-driven and on-demand routing protocols for mobile ad-hoc networks." International
Journal of Information Technology 4.2 (2007): 101-109
[12] Rocu, Marius-Corneliu. "Implementation for a WBAN-ECG monitoring system
(preliminary results)." Optimization of Electrical and Electronic Equipment (OPTIM), 2014
International Conference on. IEEE, 2014

18. THANK YOU

20. ISSUES IDENTIFIED FROM LITERATURE
SURVEY
• Time and delay present during packet transmission
• Energy efficiency of the nodes
• Packet delivery Mechanism and Throughput
• Values of the collected data is to be transferred to the mobile devices
• Large amount of data like EEG, ECG, heart rate values to be sent
through a packet to the mobile device based on the priority
• But in NS2 , coding needs to be done extensively which is not possible
in the given short span of time
• Hence an alert system is provided to the mobile nodes which are the
nurse and doctor based on the criticality.

21. ALGORITHM
• Step 1 : Define options like channel type, radio
propagation model, network interface type, MAC type,
interface queue, link layer type, antenna model, maximum
packet, number of mobile nodes, Routing protocol, X and Y
dimensions of topography, simulation end time.
• Step 2: Initialization, Open Trace file and Nam Trace file
• Step 3 : Setting up the topology
• Step 4 : Creating the mobile nodes and attach them to the
channel
• Step 5: Configuring the nodes and energy model Is give

22. • Step 6: Set up Initial Locations for the nodes
• Step 7: Set up a TCP connection between the nodes
– Transmission of packets at various time intervals
– Packet size provided
• Step 8: Set node initial position in nam
• Step 9: Simulation end time and command for ending nam
and simulation (finish procedure)
• Analysis using trace graph , awk script, Nam

23. NETWORK STATISTICS
• AWK SCRIPTS
– C-like input language
– processes column-oriented text data
– Extracts data from trace file
• Variation in output are obtained when changing the packet size,
packet interval and protocol
PERFORMANCE PARAMETERS
• Throughput, Packets: Sent Received Dropped
• End to End delay, Routing Load, Average and Total Energy
• Hop Count, Packet Delivery ratio, Protocol energy consumed
• Plots of throughput and delay are observed