Comsnets wban ppt

FORMATION OF VIRTUAL GROUPS IN WBAN FOR HEALTHCARE MONITORING AUTHORS:

VANDANA JAYARAJ & DR. HEMANTH.C

VIT UNIVERSITY, CHENNAI CAMPUS

COMSNETS 2016 – NETHEALTH WORKSHOP

BENGALURU

CONTENTS

• Introduction

• Objective & Scope

• Block Diagram / Flow Diagram

• Work Flow

• Simulation & Network Statistics

• Plots

• Observation

• Conclusion

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)

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

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

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]

BLOCK DIAGRAM

WBAN Sensor

Nodes

Intermediate

node Mobile

nodes

(Nurse and

Doctor)

1 2

3

Doctor

Nurse

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

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

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

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

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

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

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

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

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

[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

THANK YOU

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.

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

• 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

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