EXTENDED HEALTH VISIBILITY IN THE HOSPITAL

ENVIRONMENT

H. Fernández López, J. A. Afonso, J. H. Correia

Industrial Electronics Engineering Department, University of Minho, Campus de Azurém, 4800-058, Guimarães, Portugal

Ricardo Simões

Technology School, Cávado and Ave Polytechnic Institute, Urbanização das Calçada

Edifício Galo - SN R/C, 4750-117, Arcozelo, Barcelos, Portugal

Institute of Polymers and Composites, University of Minho, Campus de Azurém, 4800-058 Guimarães, Portugal

Keywords: Vital signals monitoring, Health monitoring device, Wireless sensor networks, ZigBee.

Abstract: Wireless sensor networks can help healthcare providers enhance patient monitoring and communication

capabilities. This paper describes the present state of the development of a vital signal monitoring network

applied to the hospital environment. The proposed network is based on non-obstructive sensors able to

communicate through a low power wireless sensor network based on the ZigBee protocol. This network

enables continuous patient monitoring, creating entirely new mechanisms for providing healthcare under a

plethora of cases (e.g. post-op, continuous care, and chronic diseases). The main advantages of this system

include increased patient mobility, faster detection of potential problems, real-time feedback to caregivers

and patients, and faster response to emergency situations.

1 INTRODUCTION

We have specified a system that facilitates vital

signals gathering in a hospital environment that

resembles the basic configuration analyzed in

(Cypher, Chevrollier, Montavont, & Golmie, 2006)

with some improvements. We have added a

mechanism to send messages back from the

hospital’s monitoring system to the patient. With

this system we want to introduce the concept of

“extended health visibility”, where non-critical

patients can be continuously and unobtrusively

monitored while simultaneously being informed

about their condition and receive messages from the

hospital caregivers (e.g., a doctor appointment, a

reminder to take their medicine, or a visitor arrival

notice). Through this system, instead of collecting

vital signals only a few times along the day,

hospitals will be able to maintain continuous patient

records which will provide better emergency

condition detection and response, enhanced

diagnosis capabilities, and promote, among the

patients, a better appreciation of the care being

provided.

Despite the evident benefits that can result from

the adoption of wireless technologies, there are still

many concerns that limit the widespread application

and challenge researchers to devise potential

solutions. It is essential to satisfy demanding

requirements in terms of quality of service such as

sustainable throughput, bounded delay and reliable

packet delivery. At the same time, it is necessary to

guarantee that the power consumption of the sensor

nodes is small, since they are powered by batteries,

in order to increase their autonomy. Another

difficulty arises from the fact that some sensors must

be sampled quite often, generating a large amount of

data and, consequently, requiring the network to

operate under high load, which is not common in

typical wireless sensor network scenarios. Several

strategies are been used to overcome those problems

and they include the use of techniques to compact

data and the efficient use of the communications

channel.

In order to adequately introduce and describe our

solution, we present a quick review of related work.

The scenario envisioned in (O'Donoughue, Kulkarni,

& Marzella, 2006) differs from ours because the

422

López H., Afonso J., Correia J. and Simões R. (2009).

EXTENDED HEALTH VISIBILITY IN THE HOSPITAL ENVIRONMENT.

In Proceedings of the International Conference on Biomedical Electronics and Devices, pages 422-425

DOI: 10.5220/0001551304220425

 SciTePress

developed system aims at transmitting vital signals

from in-patients in a very restricted area, an

intensive care unit. In our case, patient mobility

poses another challenge. It will be necessary to

provide means of efficiently collecting the signals

throughout the hospital’s targeted areas without

losing information.

Two different scenarios are also considered in

other related works. In case of mass casualty,

overwhelming quantities of patients need to be

monitored and triaged. AID-N is a real-time patient

monitoring system that integrates vital signs and

location sensors, ad-hoc networking, electronic

patient records, and Web portal technology to allow

remote monitoring of patient status (Tia, Greenspan,

Welsh, Juang, & Alm, 2005). CodeBlue also

considers critical care environments (Lorincz et al.,

2004). It is a common protocol and software

framework which allows wireless monitoring and

tracking of patients and healthcare professionals.

Our work shares the basic concerns of systems

planned to operate in those scenarios, namely device

discovery, naming, routing and security.

Nevertheless, we are not concerned with data

prioritization but in assuring the reliability of the

data transmission.

Telediagnosis and teleconsulting are considered

in the AMBULANCE project (Pavlopoulos,

Kyriacou, Berler, & Koutsouris, 1998). A portable

device, carried inside an ambulance, allows

telediagnosis, long distance support and

teleconsultation by specialized physicians. It allows

the transmission of vital signals and still images of

the patient from the incident place to the hospital.

While AMBULANCE uses GSM, a system

primarily designed to handle voice communications,

we have chosen to use ZigBee (ZigBee.Alliance,

2007), an emerging wireless sensor network (WSN)

protocol primarily conceived to be applied in low

traffic scenarios.

In the next section, we present some tests results

considering the electrocardiogram data acquisition

and its wireless transmission. The conclusions and

future work will be presented in the last section.

2 EXTENDED HEALTH

VISIBILITY

Gathering current patient medical data promptly and

accurately is vital to proper health care. Continuous

monitoring offers the capability of identifying and

responding to events as they occur, possibly

preventing a dangerous condition, instead of simply

allowing its diagnosis after the danger has taken

place.

2.1 The Envisioned Solution

The envisioned system is not intended to eliminate

current existing devices or routines but to improve

patients monitoring capabilities. Under this

assumption, it is not intended, for instance, to

replace wire-based continuous monitoring devices

from intensive care units. Urgency, observation,

ward and recovery from procedures that require

local anesthesia or sedation are possible scenarios.

The system in development is based on a ZigBee

ad-hoc wireless sensor network with routers and

gateways distributed all over the hospital spaces

intended for monitored patients. This network will

be responsible for receiving data from sensor units

and transmitting this information to the main

application running in the nurses’ station through a

ZigBee to Wi-Fi gateway. The data sent to the main

application will be processed and will become

available, through a web portal, to registered

healthcare providers carrying a portable device (e.g.,

a Personal Digital Assistant, PDA), as depicted in

Figure 1, where only one ZigBee network is shown.

Figure 1: Envisioned system architecture.

Five vital signals will be monitored: cardiac rate,

electrocardiogram (ECG), arterial pressure, pulse

oximetry and temperature. Medical sensors will be

designed to be minimally obtrusive.

The main application will analyze patient data

and, based on thresholds defined by the physician,

generate alerts to healthcare providers if a critical

condition occurs. Furthermore, it will be possible to

alter threshold values individually. Additionally,

portable devices will allow healthcare providers to

remotely access patient information and change

monitoring configurations at any time. In the patient

perspective, the system will be able to provide a

mechanism for communication between patients and

EXTENDED HEALTH VISIBILITY IN THE HOSPITAL ENVIRONMENT

423

the nurses’ station. Nurses will be able to send

messages to patients and to receive assistance

requests.

2.2 Current Project Status

ZigBee is a wireless network standard which

resulted from the collaborative efforts of a

consortium of companies known as the ZigBee

Alliance. IEEE 802.15.4 (IEEE, 2003) is a standard

defined by the IEEE for low-rate, wireless personal

area networks which specifies the physical (PHY)

and the medium access control (MAC) layer used by

ZigBee. The specification for the physical layer

defines a low-power spread spectrum radio

operating at 2.4 GHz with a bit rate of 250 kbps.

There are also PHY specifications for 915 MHz and

868 MHz that operate at lower data rates.

Even though ECG data rates are relatively high

compared with data rates generated by other sensors,

they are well below the bit rate of a ZigBee network

operating at 2.4 GHz, so it is expected that ZigBee

will be able to carry the generated traffic using its

CSMA/CA protocol, provided that high traffic loads

are avoided, in order to limit the percentage of

packets lost due to collisions. ZigBee was chosen

because it allows the construction of networks

composed by a large number of nodes that can cover

large areas through the use of multihop

communication, in contrast, for example, with

Bluetooth, which supports only seven end nodes per

piconet in a short-range star topology. Additionally,

ZigBee is a standard based protocol that operates on

a license-free ISM band and provides low-cost, low-

power and small form factor modules.

The ZigBee network developed is based on

JN5139 modules manufactured by Jennic (Jennic,

2008). Basic network functionalities have already

been tested using several end devices that

continuously send simulated ECG data in a star

network topology.

2.2.1 The Wireless Network for ECG

Monitoring

The ECG application was chosen as the first one to

be assessed because it is the most demanding one.

The network operates in the 2.4 GHz band and the

access to the radio channel is gained using the

unslotted CSMA/CA. The chosen sample rate is the

same used by commercial monitoring ECG

equipments, 120 Hz (Fulford-Jones, Gu-Yeon, &

Welsh, 2004).

2.2.2 Power Consumption Estimation and

Measurement

Power consumption is an important issue. It is

desirable that end devices consume the least possible

power to allow for continuous operation for long

periods without batteries replacement. To estimate

the battery lifetime, we must consider that the CPU

is always active because frequent ADC

measurements are required. During these periods,

the module consumption is equal to 9.21 mA. In

reception and transmission modes the current

consumption reaches 37mA (Jennic, 2007).

The module reads the ECG sensor thirty times,

once every T

= 8.33 ms (which is the inverse of the

sampling rate, 120 Hz) using an internal 12-bit

resolution ADC, and then, every 250 ms, sends a

data packet with the measurements. One module

cycle is depicted in Figure 2, where current

consumption values are shown for each activity:

ADC reading (ADC), backoff (BP), clear channel

access (CCA), data transmission (T

acknowledgment waiting (t

ack

) and acknowledgment

reception (T

ACK

Figure 2: Module current estimation.

Taking those operation parameters into

consideration, it is possible to determine that the

average current over the 250 ms period is equal to

9.84 mA. The total operating time considering the

module is powered by two AAA 1200 mAh batteries

is approximately 122 hours or 5 days.

The current drained by the module as a function

of time was measured to confirm the power

consumption estimation using a data acquisition

board driven by a MATLAB program. In Figure 3 it

is possible to observe the current variation over a

period of approximately 300 ms where ADC sensor

readings and backoff, CCA, data frame transmission,

ACK

and acknowledge reception are shown.

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Figure 3: Module current measurement.

2.2.3 Network Operation Tests

We have tested the packet error rate by considering

just one end device transmitting a 2-byte payload

data frame to the coordinator. Five runs were

executed involving the transmission of a total of

40,000 packets at different intervals. No packet was

lost in any run but we have observed packets

retransmissions during the longer tests probably due

to interference from Wi-Fi traffic. The number of

packets that required retransmission in each run is

shown on Table 1. The results confirm the

satisfactory coexistence between ZigBee and Wi-Fi

networks.

Table 1: Transmission test results.

Interval between

packets

Number of retransmitted packets in

each run

1 2 3 4 5

100 ms 6 5 6 0 0

20 ms 1 0 0 0 0

10 ms 0 0 0 0 0

5 ms 0 0 0 0 0

A second test was performed using five ZigBee

modules to simulate a small ZigBee star network.

Four modules were used as end devices to gather

and transmit ECG signals using the unslotted

CSMA/CA mode. Every 250 ms a 45-byte payload

data packet was sent to the fifth module, which was

programmed to perform as the network coordinator.

It also checks if any data packet from any end device

is lost and reports it. Ten runs involving the

transmission of at least 2400 packets by all four end

devices were executed. No packet was lost in any

run, which can be considered a promising result.

3 CONCLUSIONS

Wireless sensor networks promise ubiquitous vital

signal monitoring that might completely transform

the way health care is provided.

We have proposed a system that facilitates vital

signal gathering in a hospital environment for what

we call extended health visibility. Instead of

collecting vital signals only a few times along the

day, healthcare professionals will have access to

continuous patient records which will provide

several improvements compared to current

capabilities. Power consumption estimation and

measurements, as well as network performance test

results were discussed. These preliminary results

seem to validate the potential applicability of the

proposed system for the intended application.

ACKNOWLEDGEMENTS

This work has been supported by the Portuguese

Foundation for Science and Technology and the

POCTI and FEDER programs.

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