Assistive Technology for Risks Affecting Elderly People in Outdoor

Environment

Hady Khaddaj Mallat, Rami Yared and Bessam Abdulrazak

Faculty of Sciences, Informatics Department, University of Sherbrooke, Quebec, Canada

Keywords: Wearable Device, Assistive Technology, Risk, Elderly People, Outdoor, Activities of Daily Living.

Abstract: Risk situations may affect elderly people during outdoor Activities of Daily Living. The gravity of this

problem becomes more significant with the rapidly growing number of elderly people around the world.

Assistive technology is a promising solution to enhance safety of elderly people in outdoor environment. It

plays an essential role in providing them with a higher quality of life and autonomy. In this paper, we

present the result of our study on major risk factors that affect elderly people during outdoor activities. We

also discuss existing assistive technology across recent work related to outdoor risks. In addition, we

provide a framework for existing assistive technology that addresses outdoor risks. To the best of our

knowledge, this is the first review about major risks that affect elderly people in outdoor environments, and

that describes technological solutions in the domain of ambient assistive technology.

1 INTRODUCTION

Elderly people are subject to variety of risk situation

in Activities of Daily Living (ADL). The gravity of

this problem becomes more significant with the

growing number of elderly people in the society.

The number of people aged over 60 is expected to

increase from 605 million to about 2 billion between

the years 2000 and 2050, which represents an

increment of aging population from 11% to 22% (of

the whole world population). Due to the advance in

healthcare systems around the world, people live

longer and the number of elderly people is

increasing constantly. Therefore, researchers are

paying a special attention toward condition of

elderly people including work on: understanding the

population, their needs, challenges faced, and risks

in ADL.

Aging is associated with cognitive and

physiological decline, which causes activity

limitations and participation restrictions (Helal et al.

2008). Consequently, elderly people become less

active and more prone to social isolation and

loneliness, which complicates their health situation

and causes premature mortality (Yang et al. 2013).

On the other hand, participation in activities has

promising benefits at physical, sociological and

psychological levels (Sugiyama and Thompson

2006). It can result in lower risk of dementia and

improves well-being (Morrow-Howell et al., 2014).

Moreover, physical activity slows down progression

of diseases, and it is in general a promoter of health.

Increasing participation in social activities improves

cognitive abilities for aging people (Krueger et al.,

2009), and consequently leads to higher Quality of

Life (QoL). However, elderly people face hazards

and barriers that prevent them from being active and

performing outdoor ADL, including physical,

psychological and social barriers (Barnsley et al.

2012; Wennberg et al. 2010).

There is no consensus on the definition of

outdoor environment, open environment, hazard and

risk in the literature. In this paper, an outdoor

environment is considered to be any environment

outside home, including open-air areas. “Risk” and

“Hazard” are generally used interchangeably in the

literature. Inspired from the work of Marzocchi

(Marzocchi et al., 2012), we consider in this paper,

Risk as “the probability that a negative consequence

can occur in a given period of time following a

specific adverse event.” Hazard as “a source of

danger” (Abdulrazak et al. 2015).

We can classify the existing interventions to

reduce the consequences of risks affecting elderly

people in two categories: (human and technological

interventions). The human intervention includes

health and social assistance, provided by caregivers

or relatives accompanying an elderly people. This

Khaddaj Mallat H., Yared R. and Abdulrazak B..

Assistive Technology for Risks Affecting Elderly People in Outdoor Environment.

DOI: 10.5220/0005485100050016

In Proceedings of the 1st International Conference on Information and Communication Technologies for Ageing Well and e-Health (ICT4AgeingWell-

2015), pages 5-16

ISBN: 978-989-758-102-1

 2015 SCITEPRESS (Science and Technology Publications, Lda.)

approach may have negative impacts on elderly

people including emotional impact (e.g. since it

reduces the privacy space of elderly people) and

economical impact (e.g. it is often associated with a

cost to the person, family or the health system). The

technological intervention, on the other hand,

involves all Information and Communications

Technology (ICT) (including hardware, software,

devices, systems, etc.) that have been developed to

assist elderly people. Two common terms are

interchangeably used in the literature to identify this

technology: Assistive Technology (AT) and

Gerontechnology.

Recent advances in ICT (e.g., mobile and

pervasive technologies (based on context

awareness), internet of things, cloud computing,

sensor networks) enabled the creation of new

categories of solutions that may assist elderly people

in ADL. Emerging research on technologies to assist

elderly people with disabilities addresses a broad

variety of needs. In the health care domain, it has

been applied for the development of divers solutions

including wearable medical devices, smart

environments, applications for safe navigation, or

assistance applications in case of an accident or

crime (Helal et al. 2008). Although these

technologies are useful for risk assistance, their

acceptance/rejection depends on several factors,

including personal, environmental, psychosocial or

economical. High attention has to be paid to the

design of the interaction between human and the

machine (Abdulrazak et al. 2012).

Based on our literature study, we have identified

the most frequent risks as: fall, wandering, health

issues, infection, hygiene, nutrition, crime, abuse,

and traffic accidents. The most addressed risks by

ICT are fall, wandering, and health issues. In this

paper, we review these three major risks, and discuss

related assistive technology. To describe the

progress made in this domain, we searched and

matched real work and existing technology for each

risk. Our goal is help readers to better understanding

the recent progress in assistive technology. To the

best of our knowledge, this paper is the first review

on assistive technology related to risks faced by

elderly people in outdoor ADL.

This paper is organized as follows. After this

introduction, Section 2 introduces the methodology

followed in our research. Section 3 describes the

three major risks that elderly people face in outdoor

environment (i.e., fall, wandering, and health

issues). Section 4 presents Assistive Technology

systems that help elderly people in risk situations. In

this section, we review and enlist the assistive

technologies that have been developed to provide

assistance for the three major risks. We also

introduce our framework of risk related existing

assistive technology. Finally, Section 5 concludes

the paper.

2 METHODOLOGY

Our goal in this paper is to provide a review of the

major risks and dangerous situations affecting

elderly people in outdoor environment and how

technology may help them, rather than a systematic

review. We present in this section the methodology

we used to identify the major risks that affect elderly

people in outdoor environment, and to review the

existing research on assistive technology for these

risks. Our methodology is based on the literature

identified through a search on the following

databases: PubMed, ScienceDirect, IEEE Xplore and

Google Scholar. These are the main databases that

catalogue the research on risk factors faced by

elderly people in outdoor ADL and the related

assistive technology.

• We searched PubMed for the following terms:

‘‘risk factor,” ‘‘danger situation,” ‘‘hazard,”

“emergency,” ‘‘outdoor,” ‘‘barrier’’ and

‘‘frailness.” The choice of these terms in

PubMed is motivated by the fact that this

database is specialized in human/ medical

factors.

• The ScienceDirect, Google Scholar, and IEEE

Xplore databases were searched for

combinations of the terms ‘‘elderly people,”

“assistive technology,” “teleassistance,” “mobile

health,” “pervasive healthcare” and the terms

listed above. The choice of these terms and

databases is motivated by the fact that these

databases are more technology related.

Based on reading of the abstracts retrieved from

databases, we identified articles that describe risks

and hazards that affect elderly people. We also

identified potential assistive technology that may

support elderly people in these risk situations.

We disregarded in our study articles that discuss

research related to elderly people in other contexts

(e.g., studies on chronic diseases, disabilities or

other minor risks with no existing related assistive

technology). For each article in the resulting set,

along with other articles cited in the resulting article

set, we identified how major risks affect elderly

people in their ADL. We also extracted devices

systems or applications that may assist elderly

ICT4AgeingWell2015-InternationalConferenceonInformationandCommunicationTechnologiesforAgeingWelland

e-Health

people facing such risks, and identified the three

main addressed risks. We then iteratively clustered

the risks and assistive technology until we arrived at

the categorization described in this paper, as well as

our framework for existing assistive technology

related to outdoor risks.

3 MAJOR RISKS IN OUTDOOR

Various hazards cause risks for elderly people

outdoor. We identified the three major risks

addressed in the literature as: fall, wandering and

health. These three risks (and others) may precipitate

the following common consequences:

• Physical: imply injury and impairments.

• Psychological: include fear of further hazards

and risks, distress, and embarrassment.

• Social: imply loss of independence, mobility

and social ties, as well as high probability to

move into residential/health/care facilities.

• Financial and Medical: include higher cost and

medical efforts linked to the handling of the risk

situation. This burden can be on personal

financial, relative and health systems.

• Governmental and communitarians: imply

hospital admissions (e.g. number of beds) and

health insurance cost.

These undesirable risk consequences affect elderly

people widely. Therefore, research and industry

present various practical solutions to detect, prevent,

assist in risk situation, and to alleviate the

consequences.

Risk situation may have numerous causes and

factors. Inspired from World Health Organization

(WHO) International Classification of Functioning

disability and health (WHO-ICF 2002), we can

highlight three major factors: personal, health and

environmental.

• Personal factors may include age, sex,

education level, social involvement and

previous accidents (risk faced situations).

• Health factors include medical/genetic

problems such as visual and cognitive

impairment, reduced sensation, and use of

medications.

• Environmental factors comprise all the

contextual information on the visited

environments, including hygiene, pollution and

weather condition, obstacles, lighting level,

floor leveling and walking surfaces.

Following, we discuss each of the three major risks

separately.

3.1 Fall

Fall can be considered as the possibility of an

involuntary and sudden change in position, causing

an individual landing at a lower level such as the

floor, the ground, or an object, with or without

injury (David Butler-Jones 2005).

Fall is the most common and frequent risk that

elderly people face in outdoor ADL. In fact, a

Canadian study revealed that 65% of falls among

elderly people occurred outdoors, while they are

walking on a familiar route (David Butler-Jones

2005).

Personal factors that may cause fall include

mainly age and previous falls. Health factors include

chronic medical problems such as, reduced

sensation, muscular weakness, and diseases as

stroke. Environmental factors comprise poor

lighting, sliding floor and slippery surfaces (Kelsey

et al. 2010; David Butler-Jones 2005; El-Bendary et

al. 2013).

In addition to the common consequences

presented above, psychological consequences

include extreme fear of further falls (El-Bendary et

al. 2013) and social consequences are limited

outdoor activities.

3.2 Wandering and Disorientation

Wandering can be considered as a psychomotor

instability that leads an elderly people to move

toward unspecified destination. Disorientation is

referred to as getting lost because of missing

referential points (Finkel et al. 1996).

Wandering is more frequent for elderly people

because of memory impairment, particularly those

who have dementia or Alzheimer disease (Perälä et

al. 2013; Yamada et al. 2014). Around 35.6 million

people live with dementia through out the world

(According to the WHO). Wandering concerns 11%

of independent people and 28% of those who need

occasional help (Beauvais et al. 2012).

Wandering and disorientation may lead elderly

people to dangerous situations while performing

outdoor activities. In situations where elderly people

are disoriented or lost, they become more frightened

(Douglas et al. 2011), and subject to abuse (Goergen

and Beaulieu 2013).

In addition, wandering has social and

psychological consequences including fidgety of

elderly people and anxiety of relative/family, as well

AssistiveTechnologyforRisksAffectingElderlyPeopleinOutdoorEnvironment

as high risks of losing independence and transferring

to special facilities to ensure safety.

3.3 Health Issues

Health issue is defined as the state in which the

person is unable to function normally without pain.

Health issues are often defined as physiological

malfunctioning and impairment (Brubaker 1990).

Health issues are an unwelcome accompaniment

to advancing age for the majority of elderly people.

Most elderly people suffer from a variety of

symptoms and at least one chronic disease (Brubaker

1990). The most known diseases are the

cardiovascular system disease (e. g., heart attack),

the respiratory system diseases (e.g., Bronchitis),

diabetes mellitus, hypothermia, hypertension, mental

problems (e.g., Alzheimer and Parkinson’s diseases)

(Hellström et al. 2004, Ludwig et al. 2012). In

Europe, cardiovascular diseases cause 45% of deaths

among people aged 75 years or younger (Ogorevc

and Lončarevič 2014).

These medical conditions are highly prevalent

among elderly people, and may affect them severely

till causing death. The improvement of healthcare

systems around the world has enabled elderly people

to living longer. However, this phenomenon is

associated with an extreme burden on healthcare

system budgets and shortage in medical specialized

caregivers (Helal et al. 2008).

4 ASSISTIVE TECHNOLOGIES

Embedding artificial intelligence in ICT, employing

context-awareness approaches, and connecting

heterogeneous devices have a wide potential of

utilization in different outdoor situations (Doukas et

al. 2011; Rashidi and Mihailidis 2013).

• Sensor devices (e.g., Global Positioning System

(GPS), RFID, accelerometer, bio-sensors) allow

acquisition of contextual data;

• Various mobile and wearable computing

devices (e.g., personal computers, smart phones,

tablets) facilitate context collection, aggregation

and processing;

• Applying artificial intelligence techniques allow

quantification and detection of human behavior;

• Approaches for positioning, monitoring,

orientation, navigation, and communication

enable continuous outdoor assistance of elderly

people.

Combination of these technologies can be used to

develop new types of assistive pervasive

technologies for elderly people. The progress of

assistive technology is continuous until establishing

digital smart environments that are sensitive,

adaptive, and responsive to human needs, habits,

gestures, and emotions (Acampora et al. 2013).

Advances in the development of technologies have

the potential to extend the assistance from indoor

(e.g., home, office, care facility) to outdoor, and

provide a continuum of assistance in an Open Smart

Environment (Abdulrazak and Roy 2011;

Abdulrazak et al. 2011).

The building of an open smart environment to

assist elderly people outdoor requires the integration

of computational methodologies (Algorithms) and

ambient intelligence (Doukas et al. 2011). There are

three main areas of research interest in this domain.

• First (monitoring and sensing): design and

develop technology for remote monitoring and

sensing, in order to identify instantly and

accurately the contextual environmental

changes, through the use of sensors, mobile and

software tools for automated data collection and

their analysis.

• Second (risk detection), design and develop

technology for early detection of hazards, risks

and accidents, to trigger an emergency

intervention.

• Third (intervention), design and develop tools

for:

localization of an elderly people;

coordination and planning of the intervention;

usable and useful human machine interaction

for better intervention.

Researchers have more focused on developing

assistive technology for home assistance (indoor)

(Nehmer et al. 2006) in comparison with outdoor

Assistive Technology. The limitation of work on

outdoor Assistive Technology is due to:

• The heterogeneity of context information

acquired via sensors;

• The lack of standards, and the heterogeneity of

the semantics, syntax, languages and protocols

used by the various providers in outdoor

environments.

• The highly changing and in some cases unstable

environmental conditions (e.g., availability of

wireless communication, accessibility of

network services).

• The complexity of managing the mobility of the

user.

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• The complexity of building applications that

handle the above items.

Outdoor assistive technologies are based on

wearable devices to manage risks (such as sensors

embedded in clothes, watches, belts, smartphones).

Several of the existing solutions are hardware

custom based, which increase the cost of

development and pricing, as consequences limits the

solvability of their market.

The recent developed technology of smart

wearable devices (including smart phones, watches

and glasses) already integrates numerous sensors,

powerful computing, and varieties of

communication protocols. The companies that

commercialize these devices also provide developers

with programming IDEs that facilitate building

applications with different aims. This wave of smart

devices has enabled reducing the cost of developing

applications significantly. Researchers focus more

on application rather than hardware. As

consequences, numerous existing outdoor assistive

technologies have been developed for the major

mobile platforms (e.g., iOS, Android, Blackberry)

(Klasnja and Pratt 2012).

Assisting elderly people outdoor can be

preformed following

a specific request from user

an automatic detection of a situation. The

specific request can be an emergency call triggered

by user with the help of a simple mobile interface

(e.g., panic button) (Abdulrazak et al. 2013; Ferreira

et al. 2013). We can illustrate the logic of handling

risks using assistive technology in Figure 1. The

framework contains multiple phases including data

acquisition by monitoring and sensing, data

processing, detection of the risk and interventions by

calling emergency center or caregivers for example.

This framework is detailed for each risk in the

following sections.

Figure 1: Schema of assistive technology framework.

Following we discuss the outdoor assistive

technologies linked to the three risks (Fall,

Wandering, Health issues) from the point of view of

existing research work, how these technologies

assist elderly people, and how it improves their QoL.

4.1 Fall

Use of assistive devices that implement ambient

intelligence technology, can promote better handling

of fall risk. Diverse methods can be used to detect

fall. According Mubashir and Yu (Mubashir et al.

2013; Yu 2008), a fall can be detected by three main

techniques, through the use of wearable devices,

ambience devices and vision-based devices (i.e.

camera). Therefore, use of this technology can detect

falls whether they happen in outdoor or indoor

environments. However, in assistive technology for

outdoor environment, fall detection is mainly done

through the use of wearable devices, such as

smartphones and sensors. These devices can also

help to create support from caregivers to help the

elderly people in the best delay. This can be done by

using several methods and algorithms to select, and

then to communicate with the best available

caregivers around the injured person.

An exhaustive review for body worn sensors to

detect falls has been made by Schwickert et al.

(Schwickert et al. 2013). The authors listed, gathered

and discussed a representative published work on

fall and body-worn sensors. We present in Table 1

various examples of existing assistive technology

that address fall risk of elderly people in outdoor

environments. We depict in Figure 2 the logic of

Figure 2: Schema of assistive technology framework for

fall risk.

AssistiveTechnologyforRisksAffectingElderlyPeopleinOutdoorEnvironment

handling fall risks using assistive technology. The

data acquisition from wearable devices, such as

accelerometer or camera, represents the first phase.

After that, this data is analyzed and processed to

detect a fall risk. The detection of fall is obtained

from different algorithms and computational

methods as many approaches. The last phase is the

intervention of caregivers to assist injured person in

the best delay. For example, calling and notifying an

emergency call center or a family member.

4.2 Wandering

Advances in sensing, monitoring, communication

and computing techniques enable safe walking and

accurate navigation. Existing solutions for

wandering detection are mainly based on GPS.

According to (Lin et al. 2014), there are three types

of key techniques that were applied in the existing

work to assist elderly people in case of wandering in

outdoor environment: event monitoring, trajectory

tracking, and localization combined with Geo-fence

technique.

• The first technique (event monitoring) is to

determine a wandering behavior based on

activity monitoring. Through the analysis of

these events, we may detect a wandering

behavior in case of rhythmical repetition.

• The second technique (trajectory tracking)

detects wandering risk using the trajectory

tracking technique, while motion trajectories

differ from trajectories patterns that the elderly

people are supposed to take.

• The third technique (localization combined with

Geo-fence technique) consists on user

localization in outdoor environment and

analyzes this location to detect any deviations or

boundary transgressions.

Figure 3: Schema of assistive technology framework for

Wandering.

Table 1: Examples of existing assistive technology (AT) for fall risk.

Techno. Assistive Technology Ref.

App. and

accelerometer

sensor

Smartphone-based fall detection applications (app) that monitors the

movements of user, recognizes a fall, and automatically sends a request

for help.

The applications are based on smartphone embedded sensors (e.g. three

axial accelerometer, motion).

An adaptive threshold algorithm is used to distinguish fall. In case of fall,

rerecorded emergency contacts (e.g., relative, caregiver) are contacted

by phone call, SMS and email.

iFall (Sposaro and Tyson 2009)

MyVigi (Beauvais et al. 2012)

PerfallD (Dai et al. 2010)

E-FallD (Cao 2012)

A smartphone-based (Abbate et

al. 2012)

FallAlarm (Zhao et al. 2012)

Body sensor

network

Wearable motion detection device using tri-axial accelerometer or/and

Gyroscopes to detect and predict falls.

Accurate, Fast Fall Detection

(Li et al. 2009)

HMM (Tong et al. 2013)

Watch-worn

based on

sensor

The detector is easy to wear and offers the full functionality of a small

transportable wireless alarm system.

SPEEDY (Degen et al. 2003)

Wearable

camera

An activity classification system using wearable cameras is used to detect

falls. Since user wears the camera, monitoring is not limited to confined

areas. It extends to wherever user may go (indoor and outdoor)

(Ozcan et al. 2013)

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Table 2: Examples of existing assistive technology (AT) for wandering risk.

Techno. Assistive Technology Ref

App,

GPS and

GIS

GPS based systems to detect wandering risk. These systems enable caregiver (or family

members / volunteers) to register safe zones for user. If the user moves outside the safe zones for

a predetermined time, the system infers wandering situation using various algorithms (e.g.,

Bayesian). These systems may have various features including: navigate user home after

detecting a wandering risk, send notifications to caregiver containing user-location (by phone

call, SMS and/or email), establishes a line of communication between user and caregiver, as well

as a web site with real-time localization map. These systems can be:

• Based on worn GPS sensor (e.g., on Shoes, belt, watch): These systems are hardware custom

ased. The worn part is mainly composed of a GPS sensor and signal transmission modules to

transfer the

osition coordinates to a central monitoring station. The central monitoring station

is in charge of processing the risk (e.g., GPS-Shoes, Digital Angel).

•

Based on a GPS sensor integrated in a smart device (e.g., smartphone, smart glasses, smart

watch): In this case, the devices have processing resources and the risk is often

processed/detected by an app (e.g., iWander and MyVigi).

(Sposaro et al.

2010)

(Beauvais et

al. 2012)

(Lin et al.

2006)

(Parnes 2003)

(www.gpsshoe

.com)

App and

camera

DejaView is a camera-

ased system designed to aid recall of daily activities, plans, people,

laces, and objects. It senses (using the camera) the user’s surroundings and inferring context.

The system then unobtrusively cues a user with relevant information, helping them orientate

themselves and aiding both their prospective and retrospective memory.

(De Jager et al.

2011)

App,

Camera

and

worn

laser

device

Camera based systems to remotely guide users. The systems provide navigation aid in complex

and unknown areas. These systems are often composed of camera, compass and GPS. The

remote center (caregiver location) can manually or automatically interpret user-data to infer the

user status. In case of assistance need, the caregiver can remotely access the scene of the user

using the user worn camera. These systems also enable caregiver to guide/direct the user by

speech or by laser-projected arrows.

(Tervonen et

al. 2014)

(Xiao et al.

2013)

We depict in Figure 3 the framework used to

develop outdoor wandering risk related assistive

technology. This model represents the four main

phases: data acquisition from wearable devices, data

processing, detection of the wandering risk and the

intervention to assist elderly people such as making

an emergency call or a caregiver call. We also

present in Table 2 examples of existing

technological solutions to handle wandering risk

4.3 Health Issues

Health issues are both numerous and dangerous for

elderly people, some of them may cause death if

they are not handled immediately through ubiquitous

assistance services.

The outdoor assistance starts by integrating

sensor infrastructures capable of detecting changes

in the health conditions. Providing healthcare

services in outdoor environments is mainly

performed with the help of wireless technology,

sensors and wearable devices (often named WBSN:

Wearable Body Sensor Network). The sensor

network is made of wearable biosensors and

actuators that are interconnected to gather the

patient’s functional and contextual parameters.

These sensors can vary depending on the type of

data that we want to collect, e.g.,

Electrocardiography(ECG), Electroencephalography

Figure 4: Schema of assistive technology framework for

Health issues.

AssistiveTechnologyforRisksAffectingElderlyPeopleinOutdoorEnvironment

(EEG), Pulse Oximeter Oxygen Saturation (SpO2),

heart and respiration rates, blood pressure, glucose

level, body temperature, spatial location, among

others. In addition, these WBSN systems also

consist of a mobile-based unit that implements some

applications with the use of built-in sensors (e.g.,

camera, GPS, and accelerometers), which can serve

to assist elderly people in some risks (Chiarini et al.

2013). These mobile-based units connect with the

body sensor network forming a system together.

The use of pervasive computing and ambient

intelligence technology offers good opportunities to

enable ubiquitous assistance and support elderly

people in these emergency situations (Taleb et al.

2009; Acampora et al. 2013). This technology

enables self-health management (Mamykina et al.

2008). E.g., applications developed for diabetes

patients enable self-manage and help to identify

situations that require necessary interventions (El-

Gayar et al. 2013). Furthermore, using wireless

technology and wearable devices allows notifying

elderly people about their health status, and also

alert medical personnel and people nearby of the

emergency situation.

Table 3: Examples of existing assistive technology (AT) for health issues.

Health

issues

Techno. Functionality of the system Ref.

Cardiovascular

Custom mobile

health

monitoring unit

and wearable

ECG sensors

A custom mobile health monitoring system using WBSN. The system is based on ECG

connected to a network hub or a 3G phone for cardiac arrhythmias detection. The used real-

time ambulatory ECG detection algorithm enables diagnosis for cardiac arrhythmia events. In

case of emergency, it establishes a direct interaction between user and service providers.

(Li et al.

2014)

WBSN, Wearable

ECG and

Android app.

A mobile health monitoring system using WBSN and Android phone. The system operates

similarly to the previous one. The Android phone (in the case of this system) processes the

data and detects abnormal situation (alarm). The phone also forwards the alarm (with ECG

data) to a cloud Alarm Server, which pushes the messages to doctors’ phone.

(Guo et al.

2013)

Cardiac and

Hypertension

WBSN and

Android app.

iCare is a mobile health monitoring system using WBSN and smart phone. Similarly to the

previous systems, this one monitors the health status (Cardiac and Hypertension) of elderly

eople and provides tailored services for each person based on personal health condition.

When detecting an emergency, the smart phone automatically alert pre-assigned people (who

could be a family member or a friend) and call the emergency center.

(Lv et al.

2010)

Diabetes

Mobile app. and

peripheral

sensors

A mobile phone application designed for self-care management of people with Diabetes

Mellitus type 1. The system enables to keep notes of personal data (e.g., pre-measured

glucose levels and blood pressure, food and drink intake, physical activity). In case of feeling

unwell or an emergency, user can press a button to transmit immediately his/her position with

the personal data to both an emergency call center and an attendant physician.

(Mougiakak

ou et al.

2009

)

Respiratory

WBSN

(Wristband

sensors and

pulse-oxymeter)

and

Smartphone app.

SweetAge system is WBSN base on wristband sensors and pulse-oxymeter connection to a

smartphone via Bluetooth. It enables to tele-monitor vital signs (i.e., oxygen saturation, heart

rate, near-body temperature). The system displays an alert in case of abnormal res

iratory

situation (a measurement is outside the predefined range). The system instructs users to

contact their health care provider in case of need.

(Pedone et al.

2013)

Parkinson

On-body

acceleration

sensors

A WBSN composed of on-

ody acceleration sensors to assist people with Parkinson’s

disease. The system measures user movement and automatically detects Freezing Of Gait

(FOG) by analyzing frequency components inherent in movement. When FOG is detected,

the system generates a rhythmic auditory signal to stimulate user to resume walking.

( Bächlin et

al. 2010)

General

Mobile app.

(and bracelet in

the future).

iHELP is a mobile application mainly designed for heart attack risk, but could be extended to

other risks. It offers a quick and easy sending of multiple SOS alarm messages to family

members, friends, professional rescuers and all users of iHELP mobile ap

lication within a

radius of 300 meters (The radius can be configured).

(Ogorevc and

Lončarevič

2014

)

WBSN and

mobile app.

PEACH integrates various bio-sensors in a WBSN (including blood pressure sensors,

respiration sensors, and skin conductivity sensors) to detect alterations of physical conditions

and dangerous health situations. It assists user by quickly create an ad hoc rescue groups of

nearby volunteers.

(Taleb et

al. 2009)

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This technology allows care cost-saving, because

mobile technologies have a great potential to

transform healthcare and clinical intervention,

especially in assisting elderly people with chronic

diseases to live independently (between $1.96 billion

and $5.83 billion in saved healthcare costs

worldwide by 2014 (Chiarini et al. 2013)). Just a

simple example on how to face the shortage of

expert caregiver, the task of a nurse that monitors

the health status of an elderly person each day can

be alleviated by using body sensor network system.

These solutions usually work in indoor and outdoor

environments. Table 3 depicts well-known existing

systems created to assist elderly people in diverse

health issues, including cardiovascular, diabetes,

hypertension, and Parkinson diseases.

Following, we exemplify the technological part

that consists of different technique phases illustrated

in Figure 4 as a framework procedure, to reach the

whole goal of assistive technology.

5 CONCLUSIONS

Nowadays, there is great pressure to handle the

situation of ageing people in our society, since most

of them live alone and with no accompanying family

member. Therefore, a solution as moving to

healthcare facility can take place to support and

provide care to them, however some negative

emotional and economic impacts may arrive and at

the end this solution may not be the best. Thus,

assistive technology is an advantageous option for

elderly people. This population sector is vulnerable

to several major risks. We presented in this paper the

results of our study on risks affecting elderly people

in outdoor activities of daily living. The results of

our study reveal that the most addressed risks by

ICT are fall, wandering, and health issues. We

reviewed in this paper these three major risks, and

discussed related assistive technology. We also

proposed a framework that illustrates the logic of

handling risks using assistive technology.

The recent advances in pervasive, mobile and

wearable technologies opened new perspectives to

enhance elderly people quality of life, by assisting

them in activities of daily living. We have presented

in this paper interesting representative examples of

recent assistive technology linked to outdoor risks.

Still, these solutions are fragmented and more

research on combined ubiquitous assistance services

is needed to cover the need spectrum of elderly

people. An interesting proposition could be an

integrated service platform that accommodates

safety assurance, health support services, and daily

activity assistance. Such platform could take care of

anomalous events detection, daily activities

tracking/assistance, and health status monitoring.

(Lin et al. 2012). This platform could leverage

stationary sensors deployed in living environments

and mobile sensing artifacts carried by elderly

people. In this context, our team aims to provide

elderly people with a comprehensive assistive

system that manages risks. We are working on

extending our mobile platform named PhonAge

(Abdulrazak et al. 2013) to manage risk situations.

We also are working to cover lager spectrum of risks

that affect elderly people such as, nutrition, crime,

and infection.

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