TELEMEDICINEA Mote-based real time health monitoring system

Introduction Cardiovascular disease has been the number one killer

in the United States for every year since 1900, and according to the American Heart Association it causes more than 2,500 American deaths each day.

Electrocardiography Least invasive technique used to monitor the heart. An Earliest heart activity was monitored by Kolliker and Mueller

in 1856. In 1903, William Einthoven effectively recorded an

electrocardiogram using a crude galvanometer.

Micro-electro-mechanical systems (MEMS) technology

Smart Dust University of California, Berkley developed motes. Crossbow Technology, Inc. 1995 TinyOS

The research and development for the complete system is funded by the National Science Foundation – Community based Partnership for Integrated Research and Education (NSF-COPIRE)

group.

Introduction

ECG Theory Electrical impulses

Source of voltage. Nerve cells. Signal acquisition.

Lead II Measures the potential difference between the right arm electrode

and the left arm electrode. The third electrode (left leg) acts as neutral.

Most common diseases can be diagnosed using lead II Figure 1 shows a typical lead II ECG signal

Figure 1 lead II signal

Noise SourcesThe ECG signal has the amplitude of about 10 mV and noise measured on the body tissue is of the order of 10-100μV. Noisecomes from many low-level sources such as thermal noise andcrosstalk or from biological or environmental sources

Biological sources: muscle contraction baseline drift ECG amplitude modulation due to respiration motion noise.

Eliminated by using a low pass filter.

Environmental sources:

electrode contact noise instrumentation noise. Power line interference

Eliminated using a notch filter

Wireless Sensor Networks Research on sensor networks started around 1980 at the Defense

Advanced Research Projects Agency (DARPA): Distributed Sensor Networks (DSN) program.

Sensor network technology relies on integration of technologies from three different research areas: sensing, communication and computing.

Radio Frequency Made available worldwide Industrial-Scientific-Medical (ISM) band 2400 MHz – 2483.5

MHz

Factors influencing sensor network design

There are six main factors used to serve as a guideline to design a protocol or an algorithm for wireless sensor networks.

a) Fault tolerance b) Scalability c) Flexibility d) Transmission media e) Power consumption f) Production costs

Network Topology

The motes can operate in three types of topologies; Point to Point topology Ad-hoc topology Hybrid topology

o The Hybrid topology is shown in Figure 2 below.

Figure 2 : Hybrid Topology

o Also known as Mesh

Screen capture of motes operating in Star Topology

Figure 3 : Star topology

Screen capture of motes operating in Hybrid topology

Figure 4: Hybrid topology

Routing Sensor node (MicaZTM) deployment

Scattered sensor field as shown in Figure 5 Routing through the MIB600CATM

Figure 5: Data Routing

There are two main ways of routing data: Gossiping Flooding

Routing Protocols

Two tasks of a routing protocol: Route discovery Route maintenance

There are 5 main routing protocols: Negotiation based protocols Direct Diffusion Energy aware routing Rumor routing Multipath routing

TinyOS

It is an event-driven system It is designed to handle a high degree of concurrent applications The implementation language for the system is nested C (nesC). Node ID and Group ID

Hardware Implementation The overall system can be broken down into smaller subsystems.

The three fundamental components are the ECG circuit board, the wireless system and the monitoring computer.

System configuration can be seen in the system block diagram shown in Figure 6 below

Figure 6: System Block Diagram

ECG Circuit Board

MDA 300Data acquisition card

Mica Z Mica Z

Mica Interface Board (MIB 600)

Laptop / Personal Computer

Hardware Implementation Actual hardware implementation of the EKG circuit board,

acquisition unit and wireless sensor network is shown in Figure 7

Figure 7: Hardware Implementation

ECG System Electrodes Instrumentation Amplifier Signal Filtering

Low pass filter Notch filter

ECG system block diagram is shown in Figure 8 below

Figure 8: ECG system block diagram

Wireless System The wireless system is supposed to link the data acquired from the

physical network to a local PC Wireless system framework

First layer: Mote layer Second layer: Gateway Third layer: Visualization layer

Figure 9: Wireless system

Wireless SystemThe wireless sensor network required to accomplish the following six

tasks i. Data Acquisition ii. Encoding data iii. Data transmission iv. Data reception v. Decoding data vi. Data Interpretation

Figure 10: Wireless system requirement

MDA300CATM

MDA300CATM can be used as a low-power wireless data acquisitiondevice and it is used to interface with the MicaZ’s.

Figure 11: MDA300CATM

6 Digital channels (D0 – D5) 7 Single ended Analog channels

(A0 – A6) 3 Differential Analog channels

(A11 – A13) 4 Differential Precision analog channels

(A7 – A10) Internal Channels: for onboard sensor

for temperature and humidity.

MPR2400 (MicaZTM) Microprocessor: Atmel ATMega 128L

128KB flash; 4KB SRAM Radio: Chipcon’s CC2420

250 Kbps data rate DSSS encoding, O-QPSK modulation 14 Channels 11 (2.405 GHz) - 25

(2.480 GHz) separated by 5 MHz 64 bit Serial ID 51 pin expansion connector

Eight 10 bit analog I/O 21 General Purpose digital I/O

Power Options 2 AA cells

Figure 12: MPR2400

MIB600CATM

The MIB600CATM Ethernet interface board provides connectivity to MicaZTM’s for communication and in-system programming.

It has two main functions Gateway (mote RF to Ethernet bridge) Programming

Figure 13: MIB600CATM

Atmel16L In-system processor

51 pin Hirose expansion connector

TCP/IP serial server Port #10002 IP address

Two power options 5 VDC adapter power Power over Ethernet

Mote Programming Mote Programming can be done in two ways:

Direct programming, where the mote is physically connected to the MIB600CATM

Over the Air Mote Programming (OTAP)o GoldenImageo Program is deluge-enabledo Node 0 programmed

Advantages of over the air programming sensor nodes are deployed in harsh environments

Programs developed by Crossbow Technology Inc. XMDA300CA_LPTM TOSBaseTM

Packet Formation The XMDA300_LPTM breaks the data into packets to effectively

route it to the base station. A typical message packet is shown in Figure 14 below.

Figure 14: Typical message packet

The MAC Delay is the delay in milliseconds prior to transmission. The 8-byte Preamble helps the receiver to synchronize its timer to the incoming data. The 2 Synchronization bytes indicates the start of the data. The typical MicaZTM Tiny OS message is 41 bytes long; it can be up to 125 bytes long.

Packet Formation The TinyOS message structure is shown in Figure 15 below

Figure 15: TinyOS Message structure

The MicaZTM TinyOS message contains: Header Payload Length 1 byte Frame Control 2 bytes

Sequence Number 1 byte Destination ID 2 bytes

TOS Address 2 bytes TOS AM Type 1 byte TOS Group ID 1 byte Service Data Unit Data Payload 29 bytes Frame Check Sum CRC 2 bytes

Packet Description

The XMDA300CA_LPTM program divides the data into four packets

As follows.

Packet 1 data[0] : sensor id, MDA300 = 0x81 data[1] : packet number = 1 data[2] : node id data[3] : reserved data[4,5] : analog adc data Ch.0 data[6,7] : analog adc data Ch.1 data[8,9] : analog adc data Ch.2 data[10,11] : analog adc data Ch.3 data[12,13] : analog adc data Ch.4 data[14,15] : analog adc data Ch.5 data[16,17] : analog adc data Ch.6

Packet 2

data[0] : sensor id, MDA300 = 0x81 data[1] : packet number = 2 data[2] : node id data[3] : reserved data[4,5] : analog adc data Ch.7 data[6,7] : analog adc data Ch.8 data[8,9] : analog adc data Ch.9 data[10,11] : analog adc data Ch.10 data[12,13] : analog adc data Ch.11 data[14,15] : analog adc data Ch.12 data[16,17] : analog adc data Ch.13

Packet Description

Packet 3 data[0] : sensor id, MDA300 = 0x81 data[1] : packet number = 3 data[2] : node id data[3] : reserved data[4,5] : digital data Ch.0 data[6,7] : digital data Ch.1 data[8,9] : digital data Ch.2 data[10,11] : digital data Ch.3 data[12,13] : digital data Ch.4 data[14,15] : digital data Ch.5

Packet 4 data[0] : sensor id, MDA300 = 0x81 data[1] : packet number = 4 data[2] : node id data[3] : reserved data[4,5] : battery data[6,7] : humidity data[8,9] : temperature data[10,11] : counter data[14] : msg4_status (debug)

Packets observed At the present stage of the project, the data packets have been

segregated and saved on the local machine. One of the subgroups in the NSF COPIRE group is presently working on representing the packet data visually.

The sample packets are monitored by running Xlisten application on Cygwin.

Figure 16: Sample packets

Interference Issues

The license-free 2.4 GHz band encouraged the development of different technologies such as wireless LAN, Bluetooth and ZigBee. Appliances such as microwaves, cordless phones, baby monitors also operate in the same frequency spectrum.

The main concern of using this band is the possibility of intersystem interference.

Direct Sequence Spread Spectrum (DSSS) involves spreading bandwidth to allow multiple nodes to simultaneously use the same bandwidth.

Advantages of spread spectrum Resistance to multipaths fading and narrowband jamming. Data security

Security Issues

Health Insurance Portability and Accountability Act (HIPAA) of 1996.

TinySec is a link-layer security architecture

Transmitting the data over the Internet, protocols such as IPSec, Secure Sockets Layer (SSL), Transport Layer Security (TLS) and Secure SHell (SSH) secure communications.

Sensor networks are susceptible to environmental or intentional physical attacks such as: node capture physical tampering denial of service

Applications

Sensor networks may consist of many different types of sensors andcan be used for continuous sensing, event detection and locationsensing, due to this, they can be used to cater to diverse health relatedapplications.

Wearable health monitoring systems Data indicating an imminent medical condition, an emergency

service can be notified. Patients with either chronic conditions or who are undergoing

supervised recovery can be monitored from the comfort of their own homes.

Wireless sensor nodes could also be used to locate doctors and nurses within hospitals.

In pharmaceutical applications, sensor nodes could be used to track shipments

Military applications

Future Development Presently the project is still in the software development phase and

the NSF-COPIRE group is working on logical representation of the data on the local PC or a handheld device like a PDA and creating a database.

In the future, using the Mica2DotTM motes instead of the MicaZ’s to increase the portability of the system.

Figure 17 shows the Mica2DotTM mote in comparison to a US quarter.

Figure 17: Mica2DotTM

The ultimate goal of this system is relaying the vital data to doctors and emergency medical technicians and ambulance systems.

Conclusion

The NSF COPIRE project has taken the first step towards the next major advance in the evolution of cardiology. The prototype consists of reduced cabling and reduced configuration issues.

The current state of the project is a platform on which design enhancements can be made, the proposed end product is very realistic and attainable.

In the future, wireless health systems could help to meet the health needs of the entire household. This will lower the cost of healthcare and effectively preventing a public health crisis.

Wireless sensor networks, in future, will be an integral part of our lives, monitoring multiple health related signals and offering faster response times.

As TinyOS is a public / open source domain, it will unify academic and industrial research efforts, thus, improving sensor networks.

NSF COPIRE group

Demonstration

Questions

Thank you