LONG-TERM MONITORING OF VITAL SIGNS FOR MOBILE

PATIENTS

Antonio Coronato

and Alessandro Testa

1,2

Institute of High Performance Computing and Networking (ICAR), Via P. Castellino 111, 80125, Napoli, Italy

Dipartimento di Informatica e Sistemistica, Universitá di Napoli Federico II, Via Claudio 21, 80125, Napoli, Italy

Keywords: Vital Signs Monitoring, Mobile Computing, Pervasive Healthcare, Ambient Intelligence, Reliable

Monitoring.

Abstract: Hospitalization is a very expensive and resource consuming alternative for those patients that have to be

continuously monitored. The design and realization of health monitoring applications has attracted the

interest of large communities both from industry and academia. Currently many cardiac diseases are

unpredictable; remote and continuous monitoring for reliable detection of these problems becomes

essentially useful especially for elderly patients.

In the paper it is described a novel long-term wearable vital signs monitoring system which can real-time

measure physiological signs such as ecg and spo2 (saturation of arterial oxygen) equipped with bluetooth

connection. We propose a system architecture for pervasive healthcare that will open up new opportunities

for continuous and reliable monitoring of assisted and independent-living residents by means of a set of

services already included in Uranus (a service oriented middleware architecture for smart environments

which provides basic functions for the rapid and easy integration of different kinds of biomedical sensors)

and new added services to achieve a higher dependability level. A final analysis is shown to comprise the

advantages of this monitoring system.

1 INTRODUCTION

The medical field is one of the areas, where

pervasive healthcare computing appears as a tool of

growing importance and the commercial

applications developed for medical and healthcare

systems are rising both in number and in users

(Sarashon-Kahn, 2010). Although a rising elderly

population worldwide has led to the establishment of

an increasing number of long-term care institutions,

the rate of healthcare nursing personnel is growing

far slower than that of growth in the elderly

population.

Wearable sensor technologies have made many

improvements during the last decade and have

attracted the interest of stakeholders from different

domains like, as an example, healthcare.

A new concept in healthcare, aimed to providing

continuous remote monitoring of user vital signs, is

emerging. Currently many cardiac diseases are

unpredictable; thus, remote and continuous monitor-

ing for reliable detection of these problems, such as

ventricular arrhythmia, becomes essentially useful

especially for elderly patients with end-stage heart

disease. The advances in sensor technology, as well

as in communication technology and treatment of

data, are the basis on which the new healthcare

systems can be realized. Also, systems that are

designed to be minimally invasive for health

monitoring and are based on smart technologies

conformable to the human body will help to improve

considerably the autonomy and the quality of life of

patients.

In-home and nursing-home pervasive networks

mayassist residents and their caregivers by providing

continuous medical monitoring, memory

enhancement,control of home appliances, medical

data access, and emergency communication.

Such kinds of environment are very critical

forhuman safety and so the related applications must

beconsidered safety critical and such a criticality

shouldbe analyzed during the design phase. Some

criticalityfor a long-term monitoring system of vital

signs isthe battery low power, the WiFi

disconnection, the sensed data not delivered, the

sensed data corrupted, etc.

This paper presents a system design oriented

Coronato A. and Testa A..

LONG-TERM MONITORING OF VITAL SIGNS FOR MOBILE PATIENTS.

DOI: 10.5220/0003812500150020

In Proceedings of the 2nd International Conference on Pervasive Embedded Computing and Communication Systems (PECCS-2012), pages 15-20

ISBN: 978-989-8565-00-6

 2012 SCITEPRESS (Science and Technology Publications, Lda.)

around remote, continuous medical monitoring using

medical devices. Its advantages for indoor and

outdoor monitoring are described in the next

sections. The proposed system allows health

personnel to monitor patient’s vital signs from a

remote location without requiring the physician to be

physically present to take the measurements.

Moreover, we concern on dependability

(Avizienis et al., 2004) as the ability to avoid service

failures that are more frequent and severe than

acceptable. In pervasive computing, fault tolerance

techniques help us to enhance dependability and

some recent projects have employed related

techniques, as described in (Chetan et al., 2005).

Faults in a system are unavoidable and so the

systems are never totally reliable, safe, available or

secure (Avizienis et al., 2004). Pervasive healthcare

systems need to take into account how to recover

from such faults.

So, it is described a novel long-term wearable

vital signs monitoring system which can real-time

measure physiological signs such as ECG, SpO2

(saturation of arterial oxygen) and is fault tolerant.

The system presented uses an underlying

middleware infrastructure, namely Uranus, which

provides a set of basic services for the development

of vital signs monitoring applications and also uses

new services and facilities to make the system more

reliable.

The rest of the paper is structured in the

following paragraphs. The related work is presented

in Section 2; Section 3 presents Uranus, which is a

middleware infrastructure that we have specifically

developed for dependable pervasive healthcare

applications.

Section 4 describes the architecture of the long-

term vital signs monitoring system. In Section 5 we

discuss about the results on the dependability of the

proposed system. Finally, Section 6 reports our

concluding remarks.

2 RELATED WORK

Monitoring of physiological signals is not a new

domain for research. A large number of monitoring

systems, whose effectiveness and convenient

economic impact have been widely demonstrated

(e.g. (Darkins et al., 2008)), have been realized for

many diseases. Concerning, for example,

cardiovascular diseases, which represent the leading

cause of death worldwide, many wearable and

portable eHealth systems have been developed (e.g.

(Cleland et al., 2005) (Lee et al., 2007)) (Mortara et

al., 2009). The non-invasive monitoring capability of

these systems concerns not only the prevention of

cardiovascular diseases (e.g. myocardial infarction

and stroke), but also their management, as in the

case of chronically ill patients.

The number of recent research projects and

commercially available systems proves the great

useful of biomedical devices in the pervasive

healthcare field. In the research presented in

(Rodriguez et al., 2005), there are two main

architectures for ambulatory vital signs monitoring

systems, which use the mobile device with a direct

link (wireless, usually Bluetooth) to the wearable

sensors.

In (Khanja and Wattanasirichaigoo, 2007) a

ZigBee sensor data collection network is the basis of

the acquiring system, being responsible for routing

all data to a server. The received data are then

available to be visualized either through a web

browser or through a PDA based application. Chen

et al. (Chen et al., 2005) described monitoring of a

set of vital signs based on mobile telephony and

internet.

Although there are many papers that have

proposed systems for monitoring vital signs,

currently there is still no system to ensure reliable

and continuous monitoring even when a patient is in

motion (inside and outside the home). Also, our goal

is to combine wireless communication, PDA phones

and the new advances in sensor technology to enable

the elderly to have their vital signs long-term

monitored and recorded anywhere and at any time.

3 UNDERLYING MIDDLEWARE

ARCHITECTURE

This section provides a description of both the

architectural model of Uranus (Coronato and De

Pietro, 2011) and its main services, which are

depicted in figure 1.

We briefly describe the Uranus’ components that

are important for proposed system architecture of

long-term monitoring.

Human Computer Interaction section includes

mechanisms for the handling of natural and

advanced interactions in a smart environment.

Currently, it provides services like TextToSpeech

Service to synthesize vocal messages,

SpeechRecognition Service to recognize vocal

commands and Messaging Service to send textual

messages to the user’s mobile device. This section is

structured in different layers. The lowest layer

integrates hardware devices; the heterogeneity of the

PECCS 2012 - International Conference on Pervasive and Embedded Computing and Communication Systems

Figure 1: The underlying middleware architecture.

components at this layer is handled by means of

software elements called facilities, which hide

hardware devices to upper layers.

Upon this layer, a Facility Service provides the

set of homogeneous facilities that stand below. As

an example, for the case of RFID sensors (not shown

in the figure), RFID Facilities handle all the RFID

antennas deployed in the environment; thus, each

RFID antenna has its own facility that will manage

interactions between the hardware component and

the rest of the software system. Upon this layer,

information coming from all RFID Facilities (even

for different kind of antennas) are collected by the

RFID Facility Service which provides it to the rest

of the services after a preliminary elaboration.

Hardware sensors and actuator are included in

the Sensing and Controlling section (bottom-right

side). Also, it is present a Communication section

that offers communication functionalities. The Event

Service exposes an asynchronous communication

mechanism. This service supports the publish-

subscribe mechanism (Felber et al., 2003) and is in

charge of dispatching events between software

components.

There are other services to provide the network

connections (Connection Service) and to handle the

data streams (Stream Service). The context is

provided by the services that are in the top-left

section of the middleware. The Topology Service is

useful to represent the topology of the environment

in a unique and uniform manner. In particular,

locations are classified as semantic locations

(buildings, floors, rooms, specific pieces of a room)

and physical locations (the area sensed by an RFID

antenna, the area covered by a WiFi access point,

etc.) (Coronato et al., 2009). All movements of a

mobile resource or user among the locations are

tracked by means of a mechanism offered by the

Tracking Service. The Location Service provides

physical location information for mobile resources

and users: it locates mobile users and resources that

are tagged with RFID tags or WiFi enabled

(Coronato et al., 2009). The User Service provides

basic authentication mechanisms for users and by

means of a list it controls the people that are active

in an environment. Finally, the Resource Service

extends standard mechanisms for registering and

monitoring resources, like laptops, PDAs and

sensors.

Last section is related to the correctness. We just

report the services that compose it: the

RunTimeStateHolder Service (this service holds and

exposes the state of an ambient as intended in

Ambient Calculus (Cardelli and Gordon, 2000)); the

RunTimeChecker Service (this service checks, on

behalf of an ambient, the correctness properties); the

Timer Service (this service holds and verifies

temporal constraints), and the Monitoring Service

(this service monitors the entire system).

One of the key points of Uranus is the possibility

of conferring stringent dependability requirements,

which is an emerging issue in eHealth monitoring

LONG-TERM MONITORING OF VITAL SIGNS FOR MOBILE PATIENTS

applications (Bohn et al., 2003).

4 SYSTEM ARCHITECTURE

This section presents the system architecture (see

figure 2) developed on top of Uranus which

performs a long-term monitoring of vital signs.

This system has been realized to monitor long-

term (e.g. for 48 hours) the value of the oxygen in

the blood of a chronically ill patient. A residential

gateway is deployed at the home of the patient,

although the monitoring must continue even when

the patient is at work or elsewhere outside the home.

This rises the need of handling implicit requirements

like the power consumption of battery driven

devices, network switching, and reliability

assurance.

The system includes an oximeter, equipped with

Bluetooth connection, permanently attached to the

patient, which senses the value of the oxygen and

transmits it to a PDA. The PDA, in turn, forwards

data to the residential gateway. Data are transmitted

either over the WiFi domestic network while the

patient is at home, or over the GPRS network

otherwise. The system must be able to detect

connection failures when the patient leaves the

house; i.e. it must switch from the WiFi connection

to the GPRS connection. On the contrary, when the

patient comes back home, the system must reuse the

WiFi domestic connection. Current implementation

integrates the resources described in table 1. Another

important issue concerns the power consumption of

battery driven devices, which is a limiting factor for

long-term monitoring. Although the emerging of

new technologies (Kansal et al., 2007) and new

standards like the bluetooth low energy profile, this

issue can not be considered definitively solved

(Zhang and Xiao, 2009). For this reason, the system

must be able to detect low battery levels and to

migrate onto spare devices.

To realize this system we have implemented new

services and facilities in addition to those offered by

Uranus; they are useful to add new functionalities:

the management of the different kinds of

communication (Bluetooth, WiFi and GPRS), the

inquiry (by means of the Bluetooth communication)

of medical devices to use for the monitoring, the

level of the PDA’s battery and finally the switch of

the connection type (WiFi -> GPRS and vice versa).

By means of these added modules, we are able to

tackle dependability issues for these systems.

The new Services and Facilities are:

BatteryMonitor (service) checks the level of the

battery of the PDA;

ConnectionMonitor (service) handles connection

handover and switches if necessary;

Discovery (service) provides the

BluetoothDiscovery;

BluetoothDiscovery (facility) looks for the devices

with Bluetooth enabled;

IPConnection (facility) to realize a communication

between the residential gateway and the PDA

through a WiFi or GPRS connection;

WiFiConnection (facility) to realize a WiFi

connection when patient is at home;

BluetoothConnection (facility) to realize a

communication between the PDA and the

medical device (ECG or SpO2) equipped with

Bluetooth connection;

GPRSConnection (facility) to realize a GPRS

connection when patient is not at home.

We can assume that the patient is equipped with one

(or even more) spare PDA. When the level of the

battery of the primary PDA reaches a certain

threshold, the Battery Monitor Service alerts the

Coordinating Midlet, which sends a message -

through the Messaging Service- requiring the

turning on of the spare PDA. Next, the two

coordinating midlets start a coordination protocol. In

particular, they discover each other by means of the

Discovery Service. Then, the primary PDA releases

its bluetooth and WiFi connections, while the spare

PDA starts to handle the data stream.

The PDA receives data -sensed by the

oximeterthrough a Bluetooth Connection facility.

Next, the PDA’s Stream Service transmits the data to

the Residential Gateway’s Stream Service either

through a WiFi Connection, while the patient is at

home, or a GPRS Connection if the patient is

elsewhere. Finally, the data stream is received and

analyzed by a Monitoring Application built on top of

the residential gateway. The Connection Monitor

surveys the availability of the domestic WiFi. In

particular, in the case of the patient leaving home,

the Connection Monitor detects the WiFi

disconnection fault and requires the Connection

Service to start a GPRS connection. In contrast,

when the patient comes back home, the Connection

Monitor reveals the availability of the domestic

network and imparts the Connection Service to

which from the GPRS Connection to a WiFi

Connection.

PECCS 2012 - International Conference on Pervasive and Embedded Computing and Communication Systems

Table 1: HW resources.

Producer Model

PDA Nokia N8

ECG Sensor Alive Tech. Pty. Alive ECG

Oximeter Alive Tech. Pty. Alive Pulse Oxim.

Figure 2: System architecture.

5 DISCUSSION

This section presents some considerations

concerning the usefulness and effectiveness of

Uranus. Some results on the dependability of the

presented system can be deduced. We focus on the

fault coverage.

We consider four types of faults:

 Battery low power

 WiFi disconnection

 Sensed data not delivered (on the time)

 Sensed data corrupted

Concerning the first two types of faults, the system,

being equipped with battery and connection

monitors along with additional logic for

coordinating the spare PDA, is able both to detect

and recover the fault. In addition, if the system is

equipped with a timer (also available in Uranus) for

monitoring the delay and jitter of transmitted data, it

will also be able to detect excessive delay in the

transmission of vital signs.

However, with the current architecture there is

no mechanism for recovering from this fault.

Finally, in the case of sensed data corrupted, the

system is not able to detect the fault and then

recover it.

In the table 2 we report the types of faults

considered; in particular we indicate the detected

faults and if there is a recovery procedure. For

example when a Battery low power fault occurs, by

means of BatteryMonitor Service, the system detects

it and activates a recovery procedure alerting the

patient to turn on another spare PDA.

Table 2: Example of fault coverage.

Detection Recovery

Battery low power  

WiFi disconnection  

Sensed data not delivered 

Sensed data corrupted

6 CONCLUSIONS AND FUTURE

WORK

Vital signs monitoring is a field of application that is

receiving great attention from several kinds of

LONG-TERM MONITORING OF VITAL SIGNS FOR MOBILE PATIENTS

stakeholder interested in the realization of systems

and applications which are effective, reliable,

economically convenient, and capable of improving

the quality of life for patients.

The proposed long-term vital signs monitoring

system can measure various physiological signs,

such as ECG, SpO2. The system allows health

personnel to monitor a patient from a remote

location without requiring the physician to be

physically present to take the measurements and also

is able to detect and recover some fault that may

occur such as battery low power, WiFi

disconnection, sensed data not delivered and sensed

data corrupted.

We believe this system design will greatly

enhance quality of life, health, and security for those

in assisted-living communities.

The current implementation, as discussed above,

is the first version of our system. Future

enhancements to the system include: i) a graphical

display of the incoming data; ii) an alarm generation

capability to alert the care provider of a reading

outside the given limits. This alert will be

automatically sent to a PDA or similar device; iii)

interfacing of additional medical instruments,

including a blood pressure; iv) the ability for the

care provider to view stored readings remotely from

a PDA or computer.

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PECCS 2012 - International Conference on Pervasive and Embedded Computing and Communication Systems