aal@home: A New Home Care Wireless Biosignal

Monitoring Tool for Ambient Assisted Living

Joana Sousa

, Susana Palma

, Hugo Silva

1,2

and Hugo Gamboa

1,3

PLUX - Wireless Biosignals, Lisbon, Portugal

IT/IST - Instituto de Telecomunicac¸˜oes, Lisbon, Portugal

CEFITEC - FCT - Universidade Nova de Lisboa, Lisbon, Portugal

Abstract. In this article we describe a new wireless biosignal system which

monitors in a long-term basis, the users at their homes. The system consists of

wearable sensors that measure heart rate, blood oxygen saturation and physical

activity levels, sending data to a mobile phone and from this to a remote monitor-

ing station located in a clinical facility. Whenever an abnormal situation occurs,

an alarm is triggered and caregivers can provide assistance. The system has been

deployed at a major Portuguese public hospital and 30 patients under long-term

oxygen therapy have been continuously monitored remotely. The results report

that the patients feel comfortable and safe when they are continuously remote

monitored and for caregivers the system allows them to optimize their time and

give better and faster assistance.

1 Introduction

Life expectancy has been increasing in the last years. In Europe, in 1960, it was of

45.6 years old for men and 49.7 for women while in 2050, projections show that it will

increase to 79.7 and 85.1 years old for men and women, respectively. Also, a clear shift

is being witnessed from 1960 up to now regarding the proportion of elderly people (65

years and over) in the overall population [1]. According to Eurostat base scenario, in

2008 the proportion of old people in Europe (EU 27) was 17.08% (84 million), in 2020

it will be 20.06% (103 million) and in 2050 it will be 28.81% (148 million) [2,3]. As

a consequence, the old age dependency ratio in the EU 27 is rising from 25.39% in

2008 up to 50.42% in 2050 [2,3]. This situation will have an enormous economic and

social impact in a number of areas, namely in healthcare systems. The increase of the

number of elderly people will lead to an increase in the proportion of population with

physical or mental impairments, disabilities and chronic illnesses which can difﬁcult the

accomplishment of daily life activities and consequently increase the potential need for

assistance. Faced with this problem, Europe is coming across a challenge: to develop

health and social means that allow to provide safety, comfort and good quality of life to

the older population.

At the same time, technology has also been evolving and it has now spread across

several areas such as telecommunication services, education, research and healthcare,

among others. The results obtained in Research and Development studies in the ﬁelds of

electronics, signal processing and wireless communications, have shown that we have

now technology with potential to respond to the challenge of providing tools to enhance

Sousa J., Palma S., Silva H. and Gamboa H..

aal@home: A New Home Care Wireless Biosignal Monitoring Tool for Ambient Assisted Living.

DOI: 10.5220/0003339900980107

In Proceedings of the 1st International Living Usability Lab Workshop on AAL Latest Solutions, Trends and Applications (AAL-2011), pages 98-107

ISBN: 978-989-8425-39-3

 2011 SCITEPRESS (Science and Technology Publications, Lda.)

healthcare, safety and quality of life of the elderly and other disabled population groups.

Taking advantage of these base technologies, the Ambient Assisted Living (AAL) so-

lutions are now emerging and this is currently one of the most important research and

development areas, where accessibility, usability and learning play an important role

[4]. AAL solutions aim to apply intelligent technology in order to help people with

speciﬁc demands, such as disabled or elderly population to live independently at their

homes longer [4]. Thus, AAL has potential to improve the quality of life of elderly

people and to decrease the costs associated with this population.

Several studies have been reported in the last years, presenting solutions and tech-

nologies for AAL ﬁeld. For example, Hristova et al. [5] presented a prototype system

with a number of context-aware services such as heart rate monitoring, medication

prompting, generation of agenda reminders, weather alerts and emergency notiﬁca-

tions for ambient assisted living applications. Flynn et al. [6] have developed a wireless

biomonitor for AAL which integrated a wearable blood pressure and ECG sensors. On

the other hand, Stelios et al. [7] have developed a system capable of providing localiza-

tion data for ambient assisted living, integrating an event detection platform.

Despite the advantages of the AAL solutions, the acceptance of technology by el-

derly people still is a threat. There are some examples of the high acceptance of tech-

nology in this sector of the population, such as the usage of mobile phones, ATM ma-

chines. However, people do not accept everything that is technological possible and

available. The use and acceptance of technologies depend on adequate design, advan-

tage and practical use of the device, biographical experience of the potential user as well

as physical, mental and cognitive skills. Therefore, the main requirements of an AAL

product involve not only health, safety and independence aspects but also mobility and

social contact [1].

In this article we will describe a new system designed for home care and inde-

pendent living proposes, aiming to provide an infrastructure for continuous long term

biosignal monitoring in near real-time. The target group for using this system is com-

posed by the senior users who still have full mental capabilities and are able to have

their independence but need to have some of their physiological parameters monitored

on a long-term basis. An example of potential users are people with chronic respiratory

or cardiac problems. For example, cardiovascular disease is the most frequent cause

of death among the European population aged 65-84, both for men and women. This

includes not only ischaemic heart diseases and other heart pathologies but also cere-

brovascular diseases [8].

The rest of the paper is organized as follows: Section 2 describes the AAL system;

Section 3 presents the system validation; Section 4 details the main results and Section

5 highlights the main results.

2 aal@home

Our AAL system, aal@home, was developed aiming the continuous long term mon-

itoring of patients in their homes. The system is based on ﬁve features: (a) wearable

system; b) integration and modular system; c) wireless communication; (b) continuous

monitoring; (c) portability.

The aal@home system uses wireless communication in order to provide portability

and give comfort and mobility to the users. These characteristics are further enhanced

because the system is based on miniaturized and light-weight sensors that can be easily

worn by the users all day long. The real-time continuous monitoring allows the doc-

tors, nurses and orderlies to monitor in real-time the physiological parameters of each

end-user throughout day.

Monitoring different physiological parameters generally implies the use of different

devices from different brands. However, the use of several devices at the same time

is not comfortable for the user, contributing for the loss of portability and usability of

the solution. Regarding this issue, we have developed a modular system which enables

the integration of multiple parameters into a single brand system. With this design, we

improve the usability of the system and provide the caregivers with a tool that allows to

choose monitoring cardiovascular and activity parameters simultaneously or just one of

these parameters.

2.1 Overview

aal@home consists in a wearable system used for biosignal acquisition that integrates

one or two independent wireless sensor nodes, depending on the needs of the patient.

Data acquired is sent wirelessly to a mobile phone that operates as a mobile gateway,

promoting the interaction between the wireless sensor nodes and a remote monitoring

station. This monitoring station is located in a clinical facility and allows the medical

staff to monitor the status of a number of patients, at the same time. Each mobile gate-

way is associated with a number that allows the system to identify each end-user. The

mobile gateway also provides local on-screen visualization of the monitored physiolog-

ical parameters: physical activity, heart rate and oxygen saturation level. This feature

provides the user with ”self-monitor” capabilities, giving him a sense of conscience and

responsibility for the status of its health. In situations for which the mobile phone is out

of network coverage, the software on the mobile gateway is enabled with data buffering

and re-transmission capabilities.

The remote monitoring station is provided with a database containing information

about each end-user and is the point where the collected signals are stored. Through a

web interface also installed in this computer, the caregivers can monitor the physiolog-

ical parameters that are being sent by the mobile gateways. A schematic representation

of the web interface is represented by Figure 1. Furthermore, the aal@home system de-

tects anomalous situations and sends notiﬁcations and alarms to the central monitoring

station whenever the end-user has his/her physiological parameters out of the estab-

lished boundaries. This feature ensure that a fast and effective assistance is provided to

the patient whenever he needs it.

2.2 Sensors

Currently, aal@home monitors three physiological parameters: activity level, heart rate

and blood oxygen saturation. In order to accomplish these measurements, the system

integrates two kinds of sensors: a tri-axial accelerometer and a pulse oximeter.

100

Fig.1. Schematic representation of the web interface of aal@home.

Tri-axial Accelerometer. Physical activity level is monitored throughout day by a

portable and miniaturized wireless tri-axial accelerometer placed at level the waist level,

represented by Figure 2. The technical speciﬁcations of the accelerometer are listed in

Table 1.

Fig.2. Wireless tri-axial accelerometer.

Table 1. Speciﬁcations of the accelerometer.

Connectivity Class II Bluetooth Connectivity; 10 m range

Resolution 12 bit

Sampling Rate 1000Hz

Measurement Range ± 3G

Weight 74g

Dimension 84x53x18 mm

Battery Li-On; 7.4V; 800mAh

Physical activity level is determined by correlating acceleration magnitude with the

physical activity intensity level, expressed in ”Counts” and ”MET” units. From the

acceleration magnitude, the system calculates the Counts that are the base physical ac-

tivity measurement unit. Counts are then converted into METs (”Metabolic Equivalent

101

of Task”), which is a standard unit to characterize energy expenditure in physical activ-

ities [9,10]. The conversion of Counts to MET is performed through a non-linear signal

processing algorithm. This processing algorithm correlates Counts values with MET

values using two regression equations based on the method described by Crouter et al.

[11]. This way, the physical activity level is classiﬁed according to the respective MET

value [10], as shown in Table 2.

Table 2. Activity levels classiﬁcation according to MET values.

MET Value Intensity of the activity

≤ 3 Light

3 >MET ≥ 6 Moderate

MET >6 Vigorous

Pulse Oximeter. We have integrated in the aal@home system a pulse oximeter for

measuring heart rate (HR) and blood oxygen saturation (SpO2) [12], allowing to moni-

tor heart failures or vascular problems. The device, represented by Figure3 has a ﬁnger

clip pulse oximeter sensor [12] and is enabled with Bluetooth connectivity, to trans-

mit the data in real-time to the mobile phone. Currently, we have a Bluetooth ﬁnger

clip sensor under development that will be used for this purpose in the future. Table 3

presents the technical speciﬁcations of this sensor.

Fig.3. Wireless Pulse Oximeter.

Table 3. Technical speciﬁcations of the pulse oximeter.

IR Wavelength 870 nm

RED Wavelength 635

Bandwidth (-3dB) 0.5 Hz to 6 Hz

2.3 Data-Flow

In aal@home, data-ﬂow is made in two phases: ﬁrst from the sensor nodes to the mobile

gateway, and then from the mobile gateway to the remote monitoring station. Each user

has its own mobile gateway and is monitored by wireless sensor nodes, for which the

alarm thresholds are remotely conﬁgured by the practitioners at the monitoring station.

The interaction between aal@home components is shown in Figure 4.

102

Fig.4. Data-ﬂow between aal@home components.

The raw signals are measured at 1000Hz by the accelerometer and at 200Hz by the

pulse oximeter. The data is sent in real-time and via Bluetooth RF connection to the

mobile gateway, which buffers and processes this data, showing the Counts, MET, HR

and SpO2 values continuously on-screen. From the mobile gateway, data is streamed to

the remote monitoring station by TCP/IP socket connection over cellular 3G or 802.11

WiFi network. The remote monitoring station consists of an Internet-enabled computer,

installed at the healthcare institution. A MySQL relational database management sys-

tem runs on the computer and allows the system to receive and store all incoming data

from each mobile gateway, associating that data to the corresponding patient record.

In the remote monitoring station, caregivers can access to the data through a web

interface and monitor the evolutionthroughout time of physiological parameters of each

end-user. This interface also enables the caregivers to deﬁne the regular bounds of each

physiological parameters and communicate with the end-users.

It may occur that the mobile devices are out of network coverage, causing loss

of data in the central monitoring station. In order to prevent this situation, a protocol

was developed for transactional management of the transmitted data, that together with

the buffering capabilities of the mobile gateway, avoids data loss due to lack of network

coverage or communication problems. From the remote monitoring station it is possible

to check the status of the mobile communication.

2.4 Safety

For monitoring the physiological parameters and consequently to ensure the safety of

the patients, aal@home uses a real-time communication protocol that contributes for

the enhancement of the speed and effectiveness of the assistance that is provided to

patients at their homes.

From the web interface of the remote monitoring station, caregivers can deﬁne the

physiological regular bounds for each end-user’s signals. Whenever some abnormal

situation occurs, alarms and notiﬁcations are generated in the mobile gateway and sent

to the remote monitoring station in order to inform caregivers of the users’ need of

assistance. The alarms and notiﬁcations can also be generated by the user itself by

pressing a pre-deﬁned key on the mobile gateway. Furthermore, when caregivers detect

103

some deviations in the physiologicalparameters, they can also send a short text message

to the end-user, advising them on how to proceed, through the same communication

channel but in the inverse order: remote monitoring station → mobile gateway → end-

user.

The system is also prepared to send notiﬁcations to the central monitoring station

whenever the connection is lost, or low battery or incorrect sensor placement are de-

tected on any of the devices worn by the end-users.

Thus, the aal@home system provides a bilateral communication tool not only for

monitoring the end-users but also to provide the means to quickly and effectively detect

problems and take the necessary actions.

3 Validation

3.1 Pilot Installation

aal@home has been deployedat a major Portuguese public hospital and 30 patients have

been continuously monitored remotely by doctors. The selected evaluation group was

composed by patients with an average age of 55 years old, and suffering from Chronic

Obstructive Pulmonary Disease (COPD) under long-term oxygen therapy. These pa-

tients need periodic visits to the hospital unit on a weekly basis. The selection ofpatients

with respiratory insufﬁciency was based on the fact that frequent travels to the hospital

are difﬁcult and demanding on their health, therefore, a home based long term monitor-

ing could be more beneﬁcial. Consequently, the number of hospital visits would tend

to decrease as well as the associated costs. Also, the quality of the assessments would

improve since the patients would be monitored in a continuous basis instead of just

visiting the doctor on a weekly basis. The pilot study started on December 2009 and is

currently still ongoing.

3.2 Training

Before starting this study, all the people involved in the process, from caregivers to pa-

tients and including other agents that provide individual assistance to end-users at home

have received basic usage training with aal@home. For this purpose, a quick guide was

prepared, summarizing the most elementary information regarding the regular usage of

the devices, such as: connecting, disconnecting and charging the wireless sensor nodes

and mobile gateway, interpreting the on-screen data and SMS visualization.

Furthermore, caregivers received an initial training, focused on essential aspects

related to the system such as: features available on each device, alarm management,

device assignment and replacement procedures and charging.

4 Results and Discussion

The results obtained from the Pilot Installation are centered on the usability of the sys-

tem and the practitioners’ acceptance regarding its application in a real life scenario.

104

The results was acquired based on the observation and feedback of the patients and

caregivers.

The tests also report that the patients feel comfortable and safe when they are con-

tinuously monitored by the wearable equipments. Their independence and autonomy

are not compromised by the use of the sensors nor by the fact that they are being con-

tinuously monitored by a remote system. Also, as a result of the training program,

there were no major issues with the use of the system both by the end-users at their

homes or by the caregivers. Our support technical staff was involved in the training on

a more continuous way: they were available to help the users or caregivers whenever

they needed in order to enhance the learning process. From the caregivers’ perspective,

results show that the system is a useful tool which enables the caregivers to optimize

their time and provide better and faster assistance to the patients. Moreover, aal@home

allows caregivers and clinical practitioners to have a closer contact with the patients,

and follow them up on a much more regular basis, contributes to improve the diagnosis

process, customize, and enhance the assistance given to the patients. Moreover, since

the system can provide a greater long term communication between the clinicians and

the patients, the number of visits to the hospital decreases, improving the quality of life

of the users.

The tests show that usability is a key issue regarding the applicability of our system:

the users (both the monitored people and the practitioners at the clinics) need to be

capable of understanding all features of the equipments and be able to comfortably use

them. Only having this knowledge, the full potentialities of this remote monitoring tool

may be used. Regarding this issue, our present goal is to improve the usability of the

system so that the training step becomes more straightforward and thus takes less time

to be performed. Therefore, we are now engaged in the creation of intuitive and more

user-friendly software applications for the project, so that interpretation of the presented

data on the central monitoring station is straightforward, this way further enhancing the

caregivers’ performance. All modiﬁcations and new developments, that are being done

with this purpose, take in consideration the feedback of the patients as well as the health

specialists that are participating in the Pilot Installation.

Comparing this system with others, aal@home system presents a functional proto-

type with a portable and miniaturized sensors. The sensors are provided for being inte-

grated as wearable sensors, and so to increase the comfort of the patients. Moreover,the

system monitors at least three physiological variables, while other systems only monitor

one or two variables [6,7]. This way, aal@system takes advantage not only in terms of

usability, but also in terms of design, since it was projected as a multifunctional system.

5 Conclusions

We are facing an increase in the proportion of elderly people with respect to the overall

population. As a consequence, the demands of this fraction of the population are also

increasing and becoming more delicate towards the society. This problem is having

a strong impact on the national healthcare systems. However, technology is growing

faster and we believe that it has now the potential to create innovative tools and infras-

tructures that allow the governments and private institutions to respond to the society

105

needs. AAL is one of the most viable and promising solutions to bridge the lack of tools

for assisting and enhancing the quality of life of the elderly population.

In this article we presented a wireless and portable system for long-term monitoring

in long term physiological parameters, adapted to people who have special needs.The

system allows to monitor HR, SpO2 and activity level through wearable sensor nodes.

This feature together with wireless communication and miniaturization makes the sys-

tem comfortable for the patient and easy to carry with him/her during the normal day-

life. aal@home’s main feature is the safety tool which provides caregivers with an

easy-to-use resource to closely follow up the users at distance, this way creating the

conditions for a faster and more effective assistance to the patient in case of emergency.

Despite the fact that the system is still in pilot phase, the results so far are very

positive and demonstrate that according to the requirements, it has a good usability

and portability and is able to enhance the caregivers’ quality of work. Moreover, pa-

tients have been feeling comfortable and safe since they are continuously monitored.

For caregivers, aal@home is being a good tool for a closer monitoring process and for

customizing the assistance to each patient. Additionally, the pilot tests are showing that

the number of visits of the patients to the hospital can be decreased with aal@home.

This fact will certainly have a strong impact not only at social levels but also at eco-

nomic level because aal@home can provide a mean for decreasing the costs of the visits

as well as the number of people in the hospitals.

Acknowledgements

This work was partially supported by the National Strategic Reference Framework

(NSRF-QREN) program under contracts n 4329 and 7900 (respectively: Internation-

alization and Living Usability Lab for Next Generation Networks), and by Fundac¸˜ao

para a Ciˆencia e Tecnologia (FCT) under grant SFRG/BD/65248/2009, whose support

the authors gratefully acknowledge.

References

1. Steg, H., Strese, H., Loroff, C., Hull, J., Schmidt, S.: Europe is facing a demographic chal-

lenge Ambient Assisted Living offers solutions. IST Project Report on Ambient Assisted

Living (2006)

2. Giannakouris, K.: Ageing characterises the demographic perspectives of the european soci-

eties. Eurostat: Statistics in Focus. Retrieved 9 (2009) 08072

3. Eurostat - tables, graphs and maps interface (2010)

4. Stephanidis, C., ed.: Universal Access in Human-Computer Interaction. Ambient Interaction.

Volume 4555. Springer Berlin Heidelberg, Berlin, Heidelberg (2007)

5. Hristova, A., Bernardos, A., Casar, J.: Context-aware services for ambient assisted living: A

case-study. In: Applied Sciences on Biomedical and Communication Technologies, 2008.

ISABEL08. First International Symposium., IEEE (2008) 1–5

6. Flynn, B., Angove, P., Barton, J., Gonzalez, A., Donoghue, J., Herbert, J.: Wireless Biomon-

itor for Ambient Assisted Living. In: Oral Presentation at Conference on Signals and Elec-

tronic Systems (ICSES), Citeseer (2006)

106

7. Stelios, M., Nick, A., Efﬁe, M., Dimitris, K., Thomopoulos, S.: An indoor localization

platform for ambient assisted living using UWB. In: Proceedings of the 6th International

Conference on Advances in Mobile Computing and Multimedia, ACM (2008) 178–182

8. Niederlaender, E.: Causes of death in the EU (2006)

9. Ainsworth, B., Haskell, W., Leon, A., Jacobs, D., Montoye, H., Sallis, J., Paffenbarger, R.:

Compendium of physical activities: classiﬁcation of energy costs of human physical activi-

ties. Medicine and Science in Sports and Exercise 25 (1993) 71

10. Ainsworth, B., Haskell, W., Whitt, M., Irwin, M., Swartz, A., Strath, S., O’Brien, W., Bas-

sett Jr, D., Schmitz, K., Emplaincourt, P., et al.: Compendium of physical activities: an

update of activity codes and MET intensities. Medicine and science in sports and exercise

32 (2000) S498

11. Crouter, S., Clowers, K., Bassett Jr, D.: A novel method for using accelerometer data to

predict energy expenditure. Journal of applied physiology 100 (2006) 1324

12. Medeiros, J., Martins, R., Palma, S., Gamboa, H.: Blood Volume Pulse Peak Detector with

a Double Adaptive Threshold. In: 6 International Conference on Technology and Medical

Sciences, TMSi (2010)

107