Reliable Unicast and Geocast Protocols for ...

Continuous Vital Sign Monitoring via Wireless Sensor Network Baozhi Chen, Dario Pompili, and Ivan Marsic Speaker: Dr. Dario Pompili Assistant Professor Department of Electrical and Computer Engineering Rutgers, The State University of New Jersey [email protected] http://www.ece.rutgers.edu/~pompili “Malignant Spaghetti” - Wireless Technologies in Hospital Health Care, NYU-Poly, November 14, 2008

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Wireless Sensor Networks • Composed of wireless motes (also “sensors”) with sensing, processing, and communication functionalities. They are: – Wearable and compact – Limited in memory, energy, computation, and communication – Heterogeneous: many brands, models, platforms with different capabilities (BUT most of them use Zigbee PHY/MAC communication standard)

• Applications – – – – – – –

Healthcare monitoring Geographic data collection Pollution monitoring Habitat monitoring Tactical surveillance Disaster prevention Oceanographic monitoring 2

“Malignant Spaghetti” - Wireless Technologies in Hospital Health Care, NYU-Poly, November 14, 2008

Prehospital Trauma Triage • The process of classifying injured patients based on their need for emergency service. • In order to improve the state of the art, there is a need to: – Rapidly assess the injured patient and determine the need for trauma center care – Accurately and reliably monitor patient’s vital signs during this crucial period (~5-15 minutes to reach the hospital) – Overcome current limitations due to reliance on human interpretation for acquired patient data – Existing technology lacks effective methods for: • • • •

Prioritizing information streams Evaluating time-dependent measurement trends Managing incomplete data Providing data consistency and issuing effective alerts 3


Current Devices for Vital Sign Monitoring • • • • •

Mostly wired Depend on direct user interaction Have only partial analytic capability (not “smart” enough) Require manual archiving Have limited capability to forward propagate data to the next destination on the patient's path in different hospital settings

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Our Objective • Develop a non-invasive pervasive system: – Composed of wirelessly interconnected sensors for emergency services – Provide a pre- and in-hospital solution to real-time, multi-patient, and continuous health monitoring – Reduce signal interference of wireless devices – Process and transmit healthcare data in real time to a base station (and then to monitors, PDAs, pagers, hand-held wireless devices, etc.) – Provide reliability, security, and privacy during wireless transmissions

• Propose a novel two-tier network architecture – Exploit different capabilities of sensors, which self-organize in Wireless Body Area Networks (WBANs)

• Design two new communication protocol stacks to support this two-tier system 5 “Malignant Spaghetti” - Wireless Technologies in Hospital Health Care, NYU-Poly, November 14, 2008

Wireless Information Patient System (WIPS) •

Joint project leveraging interdisciplinary expertise – Drs. Dario Pompili and Ivan Marsic – Electrical and Computer Engineering Department, Rutgers University

– Dr. Randall S. Burd – Chief of Trauma and Burns at Children’s National Medical Center (formerly at Robert Wood Johnson Medical School)

– Dr. John K-J. Li – Biomedical Engineering, Rutgers University

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The overall objective – Develop a non-invasive system (WIPS) composed of wirelessly interconnected sensors for rapid and continuous quantification of the impact of trauma injury

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Three research thrusts: – Multi-sensor Multi-parameter Sensor Design – In-network Derived Parameters Analysis and Data Consistency – System Architecture and Communication Protocols “Malignant Spaghetti” - Wireless Technologies in Hospital Health Care, NYU-Poly, November 14, 2008

Thrust 1: Multi-sensor Multi-parameters Sensor Design •

Currently, evaluation of injured patients follows a standard protocol composed of prioritized steps (ABCDE)

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Current monitoring that aids this process includes pulse oximetry, capnography, blood pressure measurement, cerebral monitoring and temperature measurement

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This information is – hard-wired – independent rather than integrated – has no or only crude approaches for determining out of range values – heavily dependent on provider interpretation of values

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We propose WIPS, a non-invasive system composed of sensors wirelessly connected. It: – guarantees rapid quantification of injury – presents integrated, high-level data


Thrust 2: In-network Derived Parameter Analysis and Data Consistency •

In-network Derived Parameter Analysis (Heart Rate Variability Analysis, Spectral Analysis, Pulse Transit Time) – Pertinent parameters that have significant diagnostic values will be identified and derived for computation – The derived parameters will be computed using in-network processing – To date, analysis of parameters derived from vital sign measurements have been limited and often have not been tailored to injured patients

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Data Consistency – Higher-level interpretations of vital sign measurements to ensure data integrity – The simplest approach is to identify a range of values for each vital sign measurement that is consistent with human physiology – The amount of deviation from this range can then be used to estimate the accuracy of the data – We consider three approaches: – 1) a data-driven strategy for defining the variance from normal values – 2) a rule-based strategy that uses expert derived parameters for defining deviation – 3) a composite of these strategies


Thrust 3: System Architecture and Communication Protocols •

We study and address open research issues to support WIPS wireless communication among – sensors deployed on patients – mobile end-user terminals – fixed network elements such as hospital databases and medical devices

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Sensors self-organize in clusters forming BANs (Body Area Networks)

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Two types of communications in WIPS: – Intra-cluster (sensors -> cluster head) – Inter-cluster (cluster head -> base station)


Why a Two-tier Communication Architecture? • Different capabilities of the sensors can be exploited: – More capable nodes can be selected as cluster heads in charge of in-network processing and forwarding data to base stations – Low-end sensors can be fully dedicated to other tasks such as sensing and monitoring

• Privacy can be protected more efficiently – Only sensors and the cluster head inside a BAN can process patient’s data – Exposure of this data to other sensors in different BANs/clusters is avoided

• Two-tier architecture needs the support of two different communication protocols: inter- and intra-BAN 10 “Malignant Spaghetti” - Wireless Technologies in Hospital Health Care, NYU-Poly, November 14, 2008

Objectives of Inter- and Intra-BAN Protocols • Inter-BAN Protocol (only involving high-end cluster heads) – Support mobility of BANs (i.e., patients moving in different hospital settings) – Maximize channel utilization – Reduce interference between BANs – Allow simultaneous transmissions

• Intra-BAN Protocol (involving low-end sensors) – – – –

Support intra-BAN communications among static sensors Keep the protocol complexity low Limit the processing overhead of the low-end sensors Reduce the total amount of interference generated


Inter-BAN Protocol • Select route with the maximum Route Quality Indicator (RQI) • Select the best available data channel/route with the help of receiver RQI= 60 Max Lqi = 60 Max Lqi = 90

Max Lqi = 80 Max Lqi = 120 RQI= 100

Max Lqi = 110

sink

Max Lqi = 105

Max Lqi = 100

RQI= 105 Max Lqi = 108

Max Lqi = 110

Cluster Head 12


Inter-BAN Protocol (cont.) • Common Control CHannel (CCCH) – facilitate information exchange and coordination between CHs

• Channel switching: – By RTS-CTS on CCCH

• LQITX, LQIRX – tables for different channels at Transmitter and Receiver

• RQI table – used to select the best next hop (routing) “Malignant Spaghetti” - Wireless Technologies in Hospital Health Care, NYU-Poly, November 14, 2008

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Intra-BAN Protocol • CH sends out Probe Inquiry Packet • Sensors within a BAN reply with power and channel information • CH sends control packets to control sensors – switch channel, adjust power and packet transmission schedule

• Sensors access wireless medium by using a Time Division Multiple Access (TDMA) scheme • Reduce energy consumption • Guarantee low protocol complexity

Probe Inquiry Packet Probe Reply Power and Schedule Control


Data Packet

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Performance Evaluation • Protocols are implemented in TinyOS • Evaluated with real wireless sensors: – IMote2: • • • • •

Intel PXA271 Processor (416MHz) MMX DSP CoProcessor 32MB SDRAM, 32MB Flash, 256KB SRAM IEEE 802.15.4 Can process Camera Video

– TelosB: • • • •

TI MSP430 Microcontroller (8MHz) 10KB RAM, 48KB program Flash, 1MB Flash USB interface IEEE 802.15.4

• Evaluate data transmission performance by


Competing Solutions: One-channel Protocols •

One channel protocol based on Bellman-Ford (BF) routing protocol – Forwards data along the shortest path (i.e., least number of hops) – Link quality information is not used

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One-channel protocol with probing – Only one channel is used for all communications other than all channels – Selects the route with the maximum RQI (the minimum LQI value of the links along a route)

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Testbed Environment


End-to-end Packet Delay and Reliability vs. No. of BANs

• Our solution – – – –

Selects the best wireless links Provides limit signal interference Allows simultaneous transmissions Has the least data delay and highest reliability


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Delay and Reliability Fairness vs. No. of BANs

• Our solution: – Dynamically selects the best route thus providing robustness and flexibility to wireless communications – Can use multiple routes to the sink/base station (load balancing) – Has better delay and reliability fairness than competing protocols18 “Malignant Spaghetti” - Wireless Technologies in Hospital Health Care, NYU-Poly, November 14, 2008

Conclusions and Future Work • Conclusions: – We proposed a two-tier communication architecture for continuous vital sign monitoring – We developed two new communication protocols to limit interference, enable multiple transmissions and maximize wireless channel utilization and evaluated their performance – We designed our solution to be compatible with most existing wireless sensor platforms (i.e., those using the Zigbee standard)

• Future work: – Develop scheduling policies to handle traffic with heterogeneous Quality of Service (QoS) requirements – Refine the prototype – Test performance in real hospital settings – Study the effectiveness of WIPS to meet high-level objectives (e.g., 19 “Malignant Spaghetti” - Wireless Technologies in Hospital Health Care, NYU-Poly, November 14, 2008