EXPERIENCES IN REMOTE MONITORING OF PATIENTS

WITH CHRONIC DISEASES USING MOBILE TECHNOLOGIES

Jaime Galán-Jiménez, Alfonso Gazo-Cervero and José-Luis González-Sánchez

Polytechnic School of Cáceres, University of Extremadura, Avda. Universidad S/N, Cáceres, Spain

Keywords: Chronic Diseases, Biomedical Devices, Bluetooth, UMTS, J2ME, SOAP, MOBILE Tele-monitoring,

eHealth.

Abstract: During recent years the number of patients who suffer from chronic diseases has noticeably increased in

developed countries. This implies an increase both in costs and resource allocation of the health system and

in the commuting frequency to health centers by patients as well. These costs can be reduced by using

mobile communication technologies. In addition, these technologies can also be used to improve the

patients´ quality of life who suffer from chronic diseases, their relatives and caregivers. However, wireless

communications can be affected by interferences generated in the patient’s domestic environment. The work

presented in this paper describes an architecture which aims to improve assistance quality using health

monitoring services and remote monitoring of patients that suffer from chronic diseases.

1 INTRODUCTION

Medical care for chronic patients is becoming a

priority problem in developed countries, although

there is also a notable increase in developing

countries. It is estimated that chronic pathologies

will represent more than 60% of worldwide illness

in 2023. Heart failure is a chronic disease under

constant growing, mainly due to the ageing of

population and survival of patients with a heart

condition. This illness has a great impact over

cardiovascular problems, like diabetes and high

blood pressure.

Another emerging point is the cost for the health

system caused by the increase of hospital

admissions due to chronic heart failure.

Consequently, it is crucial to find steps that would

improve their quality of life. In this way, it is

possible to improve both the diagnosis of cardiac

events and to avoid or delay an admission to the

hospital and treatment compliance.

Current developments of mobile communications

technologies allow the creation of solutions for

health services and online monitoring not available

in the past. These solutions aim at reaching final

users who do not possess specific technological

knowledge.

The diagnosis of a chronic disease means to a

greater or lesser extent a decrease in both patient and

caregivers’ quality of life. The nature of the chronic

pathology usually implies regular monitoring with

continuous trips to health centers. Minimizing

commuting by patients to centers could increase

reaction time in potential complications. In some

cases, patients can be trained for making monitoring

tests in their own houses. However, this approach

can only be applied to a set of simple tests and

therefore raise uncertainty on obtained results.

Alternative solutions have been considered to make

homemonitoring more effective and efficient.

In the last few years, there has been considerable

research activity in wireless body area networks

(WBAN) (van Dam et al., 2001). MobiHealth project

(Van Halteren et al., 2004) has developed and trialed

a highly customizable vital signs monitoring system

based on a body area network and a mobile-health

service platform utilizing next generation public

wireless networks. For example, (Jovanov et al.,

2005) focus on computer assisted physical

rehabilitation by designing a WBAN based on

intelligent motion sensors. Other approaches like

(Latré, 2004) aim at developing energy efficient

network protocols for this kind of networks.

However, the use of different mobile and

wireless technologies can entail some problems

related to the effects produced if all of them operate

at once in the same environment: the interferences

they cause to each other. The simultaneous use of

Gal

an-Jim

enez J., Gazo-Cervero A. and Gonz

alez-S

anchez J. (2010).

EXPERIENCES IN REMOTE MONITORING OF PATIENTS WITH CHRONIC DISEASES USING MOBILE TECHNOLOGIES.

In Proceedings of the Multi-Conference on Innovative Developments in ICT, pages 93-98

 SciTePress

technologies and the way they transmit to the

medium in a reduced environment can generate

interferences that affect the performance of the

networks they make up. This results from the free

use of the industrial, scientific and medical bands,

which are internationally reserved, not intended for

commercial use and open to everyone who wants to

use them.

This work proposes the application of mobile

communications to track chronic disease patients

who need frequent trips to medical centers. The

technological infrastructure developed in this work

allows a selected group of patients to not modify

significant aspects of their daily life. This

infrastructure is composed by a network of

biomedical sensors and mobile devices. Biomedical

devices collect individual biomedical data, which is

sent through mobile devices to centralized

information systems from the infrastructure. Data is

directly obtained by patients who take their

measurements from their own houses by using

mobile communications. Thus, mobile

communication technologies minimize the number

of visits to health centers from patients and enhance

their quality of life as well as their relatives and

caregivers. The system provides information to

medical staff for managing different services

associated to medical monitoring, treatment

compliance control and alert receipt.

Thus, this document focuses on technical aspects

of the proposed architecture for a set of specific

pathologies and parameters in remote tracking as

well as on the deployment problems caused by the

existing interferences in patients’ home.

Following on from this Introduction, Section

Two focuses on pathologies, biomedical parameters

and monitoring devices. Section Three shows the

full system architecture whereas Section Four

includes information related to the deployment and

evaluation methodologies. Section Five shows a

study of the influence over mobile devices caused by

radio interferences. Finally, Section Six offers some

conclusions and future pathways for research.

2 PATHOLOGIES, PARAMETERS

AND BIOMEDICAL DEVICES

This work focuses on cardiology health service. Our

aim is controlling heart failures from hypertensive

patients older than 50 years and prone to weight

increase. In collaboration with (GRIMEX, 2010),

some meetings took place to identify pathologies

and biomedical parameters to track:

Weight Control. Liquid Retention. Patients' daily

weight is controlled due to potential anomalies

related to liquid retention. Weight thresholds have

already been considered regarding the actual health

state of chronic patients. A daily weight tracking

should be done to obtain a trend about these

variations. In case of rapid weight increasing,

alarms for medical staff are sent. We used a

Bluetooth weight control device model (A&D

Medical Precision Health Scale, 2010).

Heart Rate Control. Tracking of heart rate in

patients is conducted using individual

electrocardiography monitors. Measurements are

done on a daily basis and in case the patient is

feeling unwell. Similarly to weight control, alarms

that detect anomalies notify medical staff, who are

the ultimate responsible of patient care. The device

used for heart rate control is (Card Guard PMP

SelfCheck ECG, 2010), with Bluetooth capabilities.

Blood Pressure Control. Blood pressure is

another factor that would anticipate heart failure.

The patient conducts blood pressure measurements

on a daily basis using a blood pressure monitor. If

measurements are beyond a predetermined

threshold, an alarm to the medical staff is generated.

Similarly to weight control, there is a trend analysis

that shows variations of systole, diastole, and

arterial pulse in time. The Bluetooth blood pressure

monitor model used is (A&D Medical Digital Blood

Pressure Monitor, 2010).

3 GENERAL SYSTEM

ARCHITECTURE

This section presents the architecture developed for

this work, which is depicted in Figure 1. It is

composed of a communications infrastructure that

incorporates a set of biomedical sensors for chronic

patients distance monitoring.

The architecture components are:

 Biomedical Devices (three each patient): they

obtain patients’ biomedical data (weight,

heart rate and blood pressure).

 Mobile Devices (one each patient): Data from

biomedical devices is received and sent to a

central server.

 Central Server: Stores and processes all data

that comes from measurements of the

monitoring processes.

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Figure 2: Example of weight monitoring and data sending.

4 DEPLOYMENT

AND EVALUATION

The deployment of the experiment has been carried

out with patients selected following a random

process. All of them are members of groups of

patients currently monitored in the Cardiology Unit

in the Don Benito-Villanueva de la Serena Hospital

of the province of Badajoz in Extremadura, Spain

(Pérez et al., 2009).

Inclusion criteria are described below:

 Patients with diagnosis of chronic heart

failure (HF).

 Recently hospitalized for this reason.

 Currently in situation of medical stability.

 Patients’ home inside an UMTS coverage

area (metropolitan areas of the region).

Exclusion criteria include:

 Psychophysical handicap to do the

experiment or lack of assistance.

 Fail a test about how to use the devices.

 Refuse signing an informed consent.

 Lack of UMTS coverage in the place

where patient lives.

A sample of 9 patients and duration of 6 weeks

were estimated for the period of the experiment.

With the aforementioned criteria, the study was

carried out on men and women between 49 and 69

years of age, both experienced in the use of mobile

communication technologies and without any

previous experience.

(a) (b)

Figure 3: Monitoring and treatment compliance alerts.

Results allowed doing a division into two clearly

distinct groups according to the age:

Group A (Aged 59-69): The five patients over 59

years old did not have any experience using mobile

devices. Three of them used biomedical and mobile

devices and carried out the tests with the help of any

other people. The other two patients lived alone with

their spouses and did not rely on the help of third

parties to use the devices and carry out the

measurements. The result of the experiment with the

patients that received some support was

optimum/satisfactory. However, in the case of

patients with no help, the result was deficient/not

satisfactory.

Group B (Aged 49-58): The four patients with

diagnosis of heart failure over 50 years old had

experience in the use of mobile devices and carried

out the tests autonomously, without help of third

parties. Result: optimum/satisfactory.

For those patients without experience in the use

of these technologies, the help provided by third

parties was fundamental. Problems arising from

patients that could not carry out the measurements

can be avoided with training both for the patient and

his family environment. Ergonomics and usability

both biomedical and mobile devices have been

essential in this pilot experiment. The main problem

detected when using biomedical devices was the

electrocardiography monitor.

Several interviews have been held with some

patients at the beginning, at mid-term and at the end

of the pilot experiment. Moreover, there was a final

survey for every participant, both doctors and

patients. Patients seemed to be keen on participating

within the experiments and admitted the validity of

the approach. Participating doctors also admitted the

validity of the system and the need of its integration

in health services.

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Figure 4: Test environment.

5 STUDY OF INTERFERENCES

IN MOBILE MONITORING

Another topic investigated is the effect produced

when mobile and wireless technologies are exposed

to certain situations in some interference

environments (Angrisani et al., 2008); (Mathew et

al., 2009); (Theuang et al., 2009). The simultaneous

use of these technologies and the way they transmit

to the medium in a reduced environment can

generate interferences which have negative effects

to the performance of the networks they make up.

This can cause a performance decrease during tests

when transferring data through the communication

established between biomedical devices and the

mobile device. This performance decrease could

also be evident when data is sent from mobile

device to the central server if there are devices

prone to generate interferences operating all at once

in the same environment. As an example, there is

some equipment inside hospitals that can cause

deficient performance of WLANs (Jiang et al.,

2009); (Subramanian et al., 2008).

In order to analyze interference among wireless

technologies, the WildPackets OmniSpectrum

Analyzer was used. We have also developed an

application to obtain real data about the

performance variation in these situations (Galán-

Jiménez et al., 2008).

Three types of tests have been done in this

study: 1) File download using FTP protocol. 2)

Download of the same file using HTTP protocol. 3)

A video file transmission using RTP protocol. The

three aforementioned tests have been carried out for

each of the following situations: file transfer via

Bluetooth, microwave oven, Bluetooth headsets

connected to PC, baby monitor and wireless video

game controller. In other words, we have introduced

a new source of interference to measure the

Figure 5: Performance graph of a HTTP download when

the source of interferences is a Bluetooth transfer.

variation of the wireless network performance

caused by these specific devices. All of these

devices can be found in any of the monitored

patients’ home. Figure 4 shows a scheme of the test

environment.

To obtain reliable and consistent results, tests

have been made following the same methodology:

1) With the spectrum analyzer we obtain the

interference values that a specific device

produces.

2) Next, we start a 100 seconds traffic capture and

the transmission to test.

3) After a 30 seconds interval, we switch on the

interference source to get the effect that it

causes to the wireless network performance.

4) This interference source is active for 30

seconds. Then, we switch the device off.

5) Finally, the capture and transmission finish 100

seconds after start.

Figure 5 shows the chart provided by the

developed software extension. It corresponds to the

HTTP download when the situation which generates

interferences is the file transfer via Bluetooth.

In Table 1, we can observe that the biggest

performance decrease is produced when the baby

monitor is switched on (100%), followed by the

microwave oven in which case is around 80%.

Otherwise, the test done with the Bluetooth headsets

does not affect to the performance of the wireless

communication. Test carried out with the wireless

video game controller and the file transfer using

Bluetooth technology affect to the test that involves

TCP traffic (around 45% of performance decrease),

but they do not affect to the multimedia

transmission with RTP.

By means of the last table, we can assure that

wireless technologies interact each other and their

simultaneous use limits their performance

depending on the type of traffic and on the devices

which are active in the same environment.

EXPERIENCES IN REMOTE MONITORING OF PATIENTS WITH CHRONIC DISEASES USING MOBILE

TECHNOLOGIES

Table 1: Percentage of performance decrease by test.

Transfer Device

FTP

Download

HTTP

Download

RTP

Transmission

Microwave oven

79 %

88 %

75 %

Bluetooth

transfer

40 %

50 %

0 %

Bluetooth

headsets

0 %

Baby monitor

100 %

Game controller

41 %

50 %

0 %

6 CONCLUSIONS

One of the immediate consequences derived from

the successful result of the work is the experience

about remote monitoring of patients with chronic

diseases. Among all of the technological

innovations contributed to this work, we emphasize

the use of biomedical sensor networks and their

communication with mobile devices in

environments where patients live. Besides obtaining

biomedical information, we have studied different

ways to send this information to central health care

systems from both clinical and operative point of

view. Third generation telephony has been taken in

advance to remotely monitoring patients through the

new developed medical Web site. We have

analyzed the effect of interferences among mobile

and wireless technologies over data transmissions in

similar situations like the existing ones in this type

of remote monitoring services.

Future research lines will allow identifying most

suitable patients’ profiles and pathologies to be

monitored using this kind of technologies. Benefits

and disadvantages of using them in communities’

creation could also be studied. These communities

are referred to both patients and people in their

environments. An early identification of the

problems in patients’ health would be possible by

using the information obtained by means of mobile

communication technologies. It would be feasible to

identify anomalies in treatment compliance as well.

ACKNOWLEDGEMENTS

We would like to express our sincere gratitude to all

doctors and patients who have participated in the

experiment. This work is sponsored in part by the

Ministry of Industry, Tourism and Commerce

through the MESEAS project (Ref. FIT-350301-

2007-14 PROFIT-S.I.).

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