Design, implementation and wide pilot deployment of FitForAll: an easy to use exergaming platform...

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DOI 10.1109/JBHI.2014.2378814, IEEE Journal of Biomedical and Health Informatics

IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS

[19][21][27][28][29][30][31]. Custom exergaming solutions

mostly follow design guidelines and best practices focused in

specific intervention types such as balance improvement

[8][9][15][18][30][32][33][34][35], instead of exploring

overall physical well-being of elders.

Summarizing, significant gaps emerge when examining

exergaming studies and interventions for active and healthy

aging. There are, conspicuously, only a few studies making

any attempt at formal assessment of the usability of

computer/web-based exergaming platforms [16][26]. What is

more, an overall “prototype” attitude [20] is often

encountered: studies focus on demonstrating efficacy on rather

small user samples rather than following formal usability

testing on large cohorts. Indeed, a significantly greater number

of studies explore intervention efficacies through standardized

survey methods [8][9][10][15][18][19][25][35][36], but with

methodological generalization obstacles in their findings due

to small participant cohorts and short evaluation periods

[7][8][9][13][14][15][18][19][22][24][25][26][27][28][29][30]

[31][32][33][34][35][36][37][38]. Quite obviously, follow up

(repeated measures) tests in specific time periods (e.g. 6-

mohths, 12 months, etc.) after initial trial would also be

building up on evidence.

Last but not least, recent neuroscientific [39] and

neuropsychological [40] reviews on game-based elderly

interventions emphasize the importance of naturalistic or

personally meaningful environments and designs that should

be inducing a mismatch of supply and demand, with high task

variability, fulfilling basic individual senior needs, but be

engaging, so as to maximize long-term adherence.

Presented here is the assessment of a rigorously designed, low

cost, custom exergaming platform, utilizing off-the-shelf

contemporary controller hardware. This work is the first in the

field that utilizes validated standard tests to assess intervention

impact as well as platform usability. Additionally, this is the

first controlled study combining relatively large sample sizes

(n>200) with a rigorous intervention program (2 months, 5

d/week) providing results which could be generalized and

form the baseline for future similar efforts. The objective of

this work is to evaluate whether elderly-tailored exergaming

systems can be user friendly and effective enough to achieve

good physical exercise adherence and to improve the quality

of life. This effectiveness requires rigorous adherence to

established exercise protocols and valid assessment of

physical status in order to dynamically adjust the physical

challenges to the elderly users according to their needs and

abilities [14][20][21][24][25]. The architectural challenge

stemming from this overall objective is the incorporation of

standard physical exercise protocols and standard physical

assessment tests in exergaming software engineering practice.

The remainder of this paper is structured as follows. In the

Methodology section, the FitForAll exergaming platform and

its architecture are presented alongside the design principles

and criteria used. In order to give a clear view at the

methodology used for the evaluation of the system in terms of

usability and efficacy, a section of the Methodology deals with

the intervention and the evaluation tools as well as the

participant samples. A final methodology subsection presents

details of the statistical analysis methodology to be used for

the extraction of results. In the results section the evaluation

outcome in terms of usability, efficacy and adherence are

illustrated. At the end of the paper a Discussion section puts

the threads together by shedding light on the conducted

evaluation and its outcomes in the light of current research

work on the field of serious exergaming for elderly, along with

research limitations and further envisaged work.

II. MATERIALS AND METHODS

A. The FitForAll exergaming platform

The FitForAll (FFA) platform consists of specifically designed

games aiming at elderly exercise and

maintenance/advancement of healthy physical status and well-

being. FFA offers elderly-specific exercises within an

engaging game environment aiming at promoting physical

exercise protocol adherence. Fig. 1 illustrates information as

well as interaction layers between the users (seniors) and the

FFA system. Through contemporary controllers (Nintendo Wii

Remote Controller, Nintendo Wii BalanceBoard -Fig. 1:

Hardware Layer), FFA: (i) captures sensory information such

as acceleration, or body mass transfer by translating user body

movements and postures (Fig. 1. Physical Layer); (ii) converts

them to game input (Fig. 1 Data Layer) and compares them

with the physical exercise and gameplay objectives (Fig. 1

Semantic Layer); (iii) updates the game scenario accordingly

(Fig. 1 Game Layer); and (iv) provides appropriate forms of

feedback (Fig. 1 Presentation Layer) to the senior (Fig. 1

Outcome Layer). The Fullerton [41], an overall physical

assessment test (Fig. 1 Data Layer), evaluates the seniors’

physical status progress, based on their profile (Fig. 1 User

Profile), and adjusts the exercise intensity and difficulty level

accordingly.

The implementation of the application was based on the .NET

framework. The main application encapsulated the

communication with peripherals input devices based on the

Managed Library for Nintendo's Wiimote [42]. Filtering and

algorithmic processing of the controllers’ acquired signal, as

well as, identification of inconsistencies in calculation of body

posture and gestures and their correction are accommodated

after the acquisition process. The Microsoft XNA Game

Studio [43] was employed for the rendering of 2D and 3D

graphics. The 2D graphics were images while the 3D objects

were simple 3D models edited in 3Ds Max Studio and Google

Sketchup.

B. FFA game design principles and considerations

The design of the games that comprise FFA was guided by

tapping into expert knowledge from established protocols of

exercise used for facilitating a healthy lifestyle for the elderly.

Specifically, several such physical training protocols were

dissected and the recommended standard physical exercises

that are their building blocks were identified and recorded

[3][5]. Afterwards, a game was designed for each exercise that

incorporated in its control scheme the required physical

exercise (cf. Fig. 2). The game encapsulated the exercise in an

interesting and attractive, for the specific age group, game

concept [44], by adhering (during design) to a cohort of

guidelines and recommendations. The latter were identified in

the literature [21] or provided by the experts’ experience.

TABLE I summarizes the identified guidelines and

recommendations along with the FFA approaches respectively

[21]. The vast majority of them have been extracted by

implications in the literature [11], one session trials [14], focus

groups [24], discussion with elderly people [21],

multidisciplinary workshop and SWOT analysis [20] or short

trials with less than 15 participants [25].

Fig. 1 The FitForAll architecture concept. The hardware layer (FFA input)

captures user’s movement and transforms them to game input, which is tested against the physical exercise and gameplay objectives (semantic layer)

according to the user profile (data layer). The output of the FFA system

(presentation layer) provides the appropriate feedback to the senior to adjust his/her movements accordingly. Expert knowledge like depicted in Outcome

and Semantic Layers (protocols, recommendations) was taken into account.

C. The FFA game suite

The elementary component of the FFA platform is the game.

Focusing on the senior’s game experience, each game is

formed as a goal-oriented activity through a virtual

environment, with simple and understandable graphics (cf.

Fig. 5). The physical task/exercise (physical activity objective)

is accomplished in conjunction with the in-game goal (game

objective), while the player’s performance is tracked.

Interaction with the game is event based, triggered when a

game’s logic rule is met (cf. Fig. 5 A, B and C). Events

provide either real-time notifications about goal achievements

(result events) (cf. Fig. 5 C) or guidance on appropriate task

execution and successful completion (action events) (cf. Fig. 5

B). In FFA, the combination of games in an ordered sequence,

configured to specific physical exercise objectives, instantiates

a physical training “session” which may stand on its own or be

part of a whole intervention protocol, as FFA is integrated into

a full elderly assisted living system through the use of web

services [45] and (health) user records [46][47]. Health care

providers are able to add or modify games, sessions and

therapies through a native interface (cf. Fig. 3). Forming a

session is achieved by selecting a cohort of games and

defining their order and parameters which will affect the

overall exercise difficulty. A pool of supported games is

available to therapist-users during a session’s elaboration.

Fig. 2 Physical exercises identified in the literature and incorporated in the FFA games as strength training exercises (upper row), or stretching and

flexibility exercises (middle row), or balance training (bottom row; first two

(2) pictures) and aerobic (bottom row; last two (2) pictures) exercises.

The full game suite (cf. Fig. 5 and Fig. 6) is composed of

aerobic, strength, balance and flexibility computerized

exercises blended with games. The following game types

compose the game suite. In Hiking or Cycling (aerobic

exercises) seniors are supposed to march on the spot or cycle

on a stationary mini-bike; FFA makes use of an avatar moving

through a city landscape to render exercise enjoyable (cf. Fig.

5 A). In Ski Jump (strength, flexibility) the senior is to move

the center of mass to a specific position, thus controlling an

avatar’s jump performance (maximum length travelled) (cf.

Fig. 5 B). In the well-known Arkanoid (dynamic balance)

seniors control the horizontal position of a bar and attempt

hitting a moving ball (directed to destroy bricks) (cf. Fig. 5 C).

In another dynamic balance game, Apple Tree, seniors move

to control a basket picking apples from a tree (cf. Fig. 5 D).

Likewise, in Fishing (dynamic balance too) seniors control the

vertical position of a boat which attempts fishing the

horizontally moving fishes (cf. Fig. 5 E). In Mini-Golf seniors

move their center of mass and attempt to put a ball into a hole

by overcoming different barriers (cf. Fig. 5 F). Finally,

numerous exercise tasks increase upper and lower limb

strength by weightlifting and resistance gaming exercises,

while stretching and warm-up exercises account for flexibility

training. Senior feedback and overall reward is empowered by

pictures of positive valence which are revealed gradually with

increasing repetitions and upon completion in an effort to

engage seniors.

Fig. 3 Administration interfaces. Left: editing sessions and games in terms of parameters, difficutly and order, Right: Configure default connections for Wii

Remote Control and Wii BalanceBoard.

D. System setup, launching and game navigation

Since connectivity and setup of the Wii Devices, through the

Bluetooth Stack provided tool, is a tricky task for

inexperienced senior users, FitForAll implements an auto

connect functionality by utilizing the Bluesoleil Bluetooth

Stack API. The default controller devices and its parameters in

terms of auto connectivity are configured by the FitForAll

administration panel (Fig. 3).

Upon system launching, the senior is guided by an intuitive

interface to connect the controller devices (cf. Fig. 6 A). Once

connection is established, the senior is able to choose either

the training session that FFA automatically recommends or

one of the available training sessions (cf. Fig. 6 B). Before the

game environment is launched, auxiliary interfaces offer

instructions about the game play and the physical task to be

undertaken (cf. Fig. 6 D). After reading the instructions, the

senior may press the start button to continue. A short count-

down prepares the user before the game. Additionally, the

senior is able to pause or skip a game at any time by simply

touching the screen (cf. Fig. 6 F).

TABLE I LITERATURE GUIDELINES AND RECOMMENDATIONS FOR EXERGAMING DESIGNS FOR ELDERLY.

Guideline to follow, rationale and evidence

Description FFA approach

Physical condition

considerations

[14][20][21][24][25]

Limited extremities use (consider diseases or

injuries)

Capacity for use of just one arm/leg.

Care for exercises performed by standing or in sitting.

Flexibility for skipping exercises at user’s discretion (cf. Fig. 6 C).

Range Of Motion (ROM)-Adaptability [14][21][24]

Bigger tolerance at high precision gestures Configurable tolerance of movement range (cf. Fig. 3).

Continuous Player Support

[14] Avoid assumption that different gestures are

remembered over whole game period. Comprehensive illustrations of instructions through the interface

(physical activity and game objectives) (cf. Fig. 5 B).

Instructions screen pops-up on movement inconsistencies or total detection absence (cf. Fig. 6 D).

Avoid small/fast moving

objects [21][25] Produce strain and anxiety Well discriminated objects (cf. Fig. 5).

Well defined game start up (with count-down period)

Adequate time for user adjustment to virtual environment Clean user interface [21] Clear instructions

Avoid redundant information

Simple, well defined graphics (cf. Fig. 5).

Big, visible buttons for screen navigation (e.g. pause, skip) (cf. Fig. 6) Attractive and friendly user

interface [11][20] Engages user in-game Simple, illustrated instructions and graphics. (cf. Fig. 6)

Suitable topics[21] Topics adjusted to elderly people’s interests. Real life scenarios, e.g. collecting apples, catching fish etc (cf. Fig. 5). Provide audiovisual

feedback [11][21][24] Necessary to understand game interaction.

Positive feedback immediately after a task’s completion

Avoid negative feedback

Achievements Panel (cf. Fig. 5 D)

Auditory signals (whistle, clapping) declare action sequence

Supporting, rewarding, motivational pop up messages, delivered as text or color codified indicators, upon significant events (cf. Fig. 5 E)

Adjustable difficulty

[14][20][21][24][25] Appropriate activity/challenge level keeps

active players engaged while avoiding overstraining others

Avoid cognitive and motion complexity

Option of several difficulty levels on startup. (cf. Fig. 6 B)

Subset of Fullerton [41] assessment tests performed every 7 sessions, automatically suggests difficulty level.

Encourage social interaction

[11][21] Encouraging/cheering game partners increase

Score feedback increases competitiveness among the seniors. (cf. Fig.

6 E) Exertion Management

[14][20] Manage fatigue, prevent overexertion Alternating between more/less physically intense game periods to

allow recovery.

Pause or skip exercise capacity at any time (cf. Fig. 6 F).

Simple Setup [14] Easy menus, startup and shutdown. Intuitive, illustrated instructions for devices’ connection (cf. Fig. 6 A)

Start on single button press. (cf. Fig. 6 B)

Record/display user's past behavior [11]

Show historical information related to physical activity

Difficulty level progress implies physical improvement

Provide information at

opportune moments [11] Avoid annoying messages at inappropriate

times. Pop up messages only on game event occurrence game start-up and

completion. (cf. Fig. 5)

Game pauses for user focus on message (cf. Fig. 5)

E. Physical intensity and difficulty level selection: an

evidence based step towards system adaptability

As was mentioned previously, a session has a specific

difficulty level. This comprises of two components: the

physical exercise intensity component (e.g. more repetitions

per exercise), which is the dominant one and the gameplay

difficulty (e.g. avoid obstacles during the golf game). Apart

from the option of creating/modifying interventions, FFA

incorporates a default intervention protocol, tailored to elderly

[3], which consists of four difficulty levels. The first level

promotes light exercise while the last one promotes more

intensive physical exercise. Periodically, a formative

assessment [48], by means of a short computerized subset of

the Fullerton test (cf. Fig. 4), is requested to be performed by

the seniors prior to the intervention’s session. Four of the six

Fullerton tasks are facilitated by the FFA through Wiimote

(attached on the arm or the leg) to measure number of arm’s

curls (cf. Fig. 4 A), number of stand-ups from a chair (cf. Fig.

4 B), time to cover predefined distance (cf. Fig. 4 C) and

number of steps in a predefined time allotment (cf. Fig. 4 D).

The other two of the six tasks are simply measured by the

seniors and entered manually to the system by an intuitive

virtual keyboard on the screen. Following the design

guidelines, each task is accompanied by detailed and

illustrated instructions. Performance improvement in at least

three Fullerton tasks is required for promoting the seniors to

the next difficulty level while deterioration to at least two

tasks is enough for a level decrease.

Fig. 4 Partial computerization of the Fullerton overall physical status

assessment test. FFA measures number of arm’s curls (A), number of stand-ups from a chair (B), time to cover predefined distance (C) and number of

steps in a predefined time allotment (D) by means of the Wii Remote

Controller.

F. Intervention

The FFA platform was widely used and evaluated during

the trials of the Long Lasting Memories (LLM) project funded

by EU [49][50][51]. In compliance to the ACSM/AHA

recommendations [3], an appropriate number of training

sessions was created. Each trainee had to accomplish 20mins

aerobic exercises, 8-10 resistance exercises, 10mins flexibility

exercise and a set of balance targeted exercises. The warm-up

and cool-down processes constituted the initial and final

session’s components respectively. Exercise intensity was

constant per session but was gradually increased, based on the

formative assessment, throughout the whole intervention to

meet fitness level improvements [3][4][52]. Exercises kick-off

at the light intensity level with a target to reach 50-60%

maximum heart rate (HRmax) and can proceed to the very

hard level with a target set at 80-90% of HRmax. The

intervention was conducted on a series of elderly user groups

(cf. Fig. 7) and was supervised by formal carers. For

comparison, an (active) control group was used which, instead

of the FFA intervention, received cognitive training, identical

in terms of total duration and session intensity as well as

grouping attributes. The whole study was ecologically valid

and was conducted in numerous settings in Thessaloniki

(Greece) within: day care centers of the Greek Association of

Alzheimer's Disease and Related Disorders; municipal social

care centers as well as senior centers; and local parish

community centers.

Fig. 5 FitForAll indicative game interfaces and in-game feedback. A. Hiking:

colored representation of action required. B. Ski Jump: user guidance. C.

Arkanoid: game event message. D. Apple Tree: achievements panel. E. Fishing: motivating messages on low performance. F. Mini-Golf: red color

indicates time end up.

G. Evaluation Method

Both subjective and objective measures were used to evaluate

the FFA platform. Evaluation was conducted mainly in two

fronts, the user level (usability, adherence) and the efficacy

level (fitness impact, Quality of Life Impact). User experience

was evaluated through the (standard) Software Usability

Measurement Inventory (SUMI) questionnaire [53]. SUMI

may report results on efficiency (to which extent users feel

that the software helps them), affect (user’s emotional

reaction), helpfulness (intuitiveness and ease of use), control

(how in-control of the application the users feel), learnability

(how quickly users feel they were able to master the

application) and one overall scale (Global) (TABLE III).

Additionally, participants also completed the System Usability

Scale (SUS) [54], a “quick and dirty” survey scale on

usability. Finally, an ancillary set of questions, focusing on the

platform’s impact on the elderly, ease of use and its potential

as a commercial product.

An attendance log was used for measuring the adherence to

schedule. Each participant was asked to accomplish 5 daily

sessions per week. While not all of the participants managed

to follow this intensive schedule, all managed to complete the

required total sessions (set at a minimum of 16). Adherence

was measured as the ratio of the number of participation

sessions over the number of planned sessions.

On the efficacy front, the Senior Fitness (Fullerton) Test

[41] was chosen as an index of elderly fitness. Assessing

upper and lower body strength, upper and lower body

flexibility, agility/dynamic balance and level of aerobic

endurance, this test was performed to both participant groups

(FFA intervention and control). Additionally, improvements in

quality of life (QOL) were assessed through the WHOQoL-

BREF [56] questionnaire, which addresses four (4) QOL

domains: physical/psychological health, social relationships

and environment (4-20 range scale).

Fig. 6 Auxiliary/navigation interfaces. A. Illustrated guidance for connecting

the peripheral controller devices. B. Well discriminated buttons for selecting options. C and D. Illustrative guidance on how to utilize the wiimote and the

balance board. E. Overall scores and performance on session end. F. Game

pause when user taps screen- option to skip or restart.

H. Participants and system use

FFA was the Physical Training Component in the LLM

project [51]. Thus, a relatively large number (415) of

European senior citizens engaged with it for a minimum of 2-3

times per week for a total duration of 7-8 weeks according to

the LLM database records [46]. The system was used for 6231

sessions between 2010-2012; each session lasted for

approximately 60 mins. For the purposes of this paper,

however, the rigorous evaluation procedure described above

was trialed and successfully completed only by 116 of those

(28%) participants. Likewise, the control group for the

purposes of this study which was conducted in Thessaloniki

(Greece) consisted of a demographically similar group of 116

participants. Specifically, inclusion criteria for both the

intervention and the control group were: age ≥ 60, fluent

language skills, normal or corrected-to-normal vision and

hearing, examination and formal permission from a

cardiologist and time commitment followed by a signed

informed consent (obtained prior to trial commencement). A

dropout was considered by means of not achieving the

minimum number of sessions (16) or five (5) consecutive

absences (FFA dropout rate was 21.2% as opposed to 22.2%

for the controls). No financial incentive was provided to

participants. The protocol was approved by the Ethical Boards

of the Greek Association of Alzheimer's Disease and Related

Disorders and the Medical School of the Aristotle University

of Thessaloniki.

Fig. 7 Photos from the intervention in a day care center in Thessaloniki,

Greece. Participants utilize mini bicycles, weights and chairs according to the game’s suggestion.

I. Statistical analysis

Since standard usability tools were used, our analysis followed

well-defined literature procedures. SUMI questionnaire data

were transformed so as to be comparable against the

SUMISCO standard database average, fixed at "50" for each

of the scales. Mean and standard deviation (SD) values of the

Global and the five (5) additional subscales were calculated.

Likewise, the SUS score was normalized and transformed to

percentiles, allowing the usability of the developed system to

be comparable against a corpus of more than 5,000 SUS

observations [55]. This provides an indicator of the overall

usability of FFA as a system.

Efficacy data were analyzed using the statistical software

SPSS v.21 for Windows. Chi-square analysis was used to test

for gender and age differences between intervention and

control groups. Non-parametric models were chosen for the

physical fitness and QOL data analysis as the majority of

variables were not normally distributed. For continuous

variables pre- and post-intervention changes, within groups,

were analyzed with the Wilcoxon signed rank test, while the

Mann-Whitney U test was used for the differences (post – pre

intervention and post – pre control) between intervention and

control groups respectively. Descriptive statistics for

continuous variables are represented by mean±SD, while an

effect was considered statistically significant if a p-value of

less than 0.05 was obtained.

III. RESULTS

In both groups, female participants have been the majority

(TABLE II) in agreement with what is widely reported in

relevant literature [9][16][18][31][36][57]. Although

participants of both groups were asked to use the system 5

days per week, average FFA attendance was 4 days/week,

achieving a total mean of some 25 sessions. No statistically

significant differences were observed between groups with

respect to age (p=0.287) or gender (p=0.331) (TABLE II).

TABLE II DESCRIPTION OF GROUP DEMOGRAPHICS AND SESSION

ATTENDANCE

Control Intervention

Number of participants 116 116

No of females (%) 89 (76.7%) 95 (81.9%) No of males (%) 27 (23.3%) 21 (18.1%)

Age (years) 69.08 ± 6.6 69.98 ± 6.2

Age (Min-Max) 60-83 60-87 Total intervention sessions

(~1 hour per session)

24± 4 25± 6

SUMI results appear in TABLE III. Values for Efficiency,

Helpfulness, Control, Learnability and Global score are all

above 60%. This puts the FFA platform well above the mean

scores of the SUMISCO database when considering levels of

user satisfaction.

TABLE III SUMI QUESTIONNAIRE RESULTS

Mean St

Median Minimum Maximum

Global 68.33 5.85 71.0 42 73

Efficiency 64.84 8.96 68.0 35 72

Affect 68.57 6.99 72.0 20 72 Helpfulness 65.73 5.38 68.0 36 72

Controllability 61.69 7.47 65.0 24 72

Learnability 60.09 12.45 65.0 18 71

The mean raw SUS score was 76.36 with no participant rating

below 50%, while the normalized score was 77.7% [55].

Training schedule adherence was found to be good enough,

that is, 82%, as shown in the histogram of Fig. 8.

TABLE IV contains efficacy results (post – pre intervention

differences). Concerning the physical assessment test, the

intervention group showed statistically significant difference

to all the domains of the test in contrast with the control group.

The 8-Foot-Up-And-Go refers to time and thus lower score is

translated to better mobility and dynamic balance.

The within group comparisons show statistically significant

differences regarding pre and post results to all the domains of

the intervention group, while only lower body strength was

improved in the control group (but in obviously lower levels

than the intervention group). Regarding QOL assessment, the

intervention group, compared with the control group, showed

statistically significant difference to the three first domains.

However the differences post-pre interventions within the

same group are statistically significant in both the intervention

and the control group in domain 4 suggesting that

improvement in this domain was observed on both the

intervention and the control group.

On the qualitative questionnaires, 96.6% reported that the

FFA intervention has improved their social life and helped

them meet new people and 85.4% perceived that the FFA

platform allows them to control their health better.

Additionally, 87.1% of the users reported that with a

maximum of 5 days familiarization with the platform they

were able to use it without help, while another 92.2% reported

that they considered this as a commercial level quality ICT

platform, worth paying for if it was ever marketed.

Fig. 8 Intervention adherence as a histogram of the proportion of sessions attended by FFA participants with respect to the planned sessions.

TABLE IV EFFICACY RESULTS IN TERMS OF FULLERTON AND WHOQOL AND THEIR SUBDOMAINS. BOLD P VALUES DENOTE STATISTICALLY SIGNIFICANT

DIFFERENCES.

Test Sub-domain Control (N=116) Intervention (N=116) Between groups differences (post-pre)

Pre mean±SD

Post mean±SD

Wilcoxon P value

Pre mean±SD

Post mean±SD

Wilcoxon P value

Mann-Whitney U-test

Chair Stand (lower body strength)

13.84±2.97 14.56±3.62 p=0.000, Z=3.506

13.03±3.99 16.35±5.34 p=0.000, Z=7.895

p=0.000, Z=-6.248

Arm Curl (upper body strength) 20.50±4.63 20.60±4.71 p=0.250, Z=1.150

15.90±4.31 22.09±5.48 p=0.000, Z=8.802

p=0.000, Z=-9.751

2-minute Walk in place (aerobic endurance)

75.06±21.87 74.27±21.56 p=0.955, Z=-0.056

70.02±24.17 86.59±28.43 p=0.000, Z=7.343

p=0.000, Z=-7.582

Chair Sit and Reach (lower body flexibility)

0.20±8.893 0.79±9.17 p=0.748, Z=0.321

-1.10±10.834 4.25±10.71 p=0.000, Z=7.856

p=0.000, Z=-6.892

Back Sctratch (upper body flexibility)

-10.02±11.85 -9.57±11.59 p=0.237, Z=1.182

-10.05±11.24 -7.42±10.39 p=0.000,

Z=6.149

p=0.000,

Z=-5.113 8 Foot Up And Go (complex

coordination, agility and dynamic balance)

5.49±1.25 5.47±1.22 p=0.715, Z=-0.366

6.55±1.81 5.78±2.18 p=0.000, Z=-7.568

p=0.000, Z=7.086

Physical 15.60±2.00 15.50±1.96 p=0.759, Z=-0.307

14.77±2.37 15.28±2.15 p=0.006, Z=2.746

p=0.012, Z=-2.502

Psychological 12.17±1.84 12.33±1.58 p=0.256, Z=1.136

11.66±1.71 12.28±1.69 p=0.000, Z=3.854

p=0.013, Z=-2.482

Social 5.62±1.36 5.44±1.30 p=0.120, Z=-1.557

5.22±1.10 5.40±0.93 p=0.109, Z=1.603

p=0.026, Z=-2.223

Environment 16.43±1.84 16.76±1.86 p=0.025,

Z=2.234 15.97±1.95 16.83±1.78 p=0.000,

Z=4.160 p=0.066, Z=-1.839

IV. DISCUSSION

To our knowledge, this is the first elderly-focused exergaming

platform evaluated on a daily basis through an 8-week

intervention with more than 100 participants. On the usability

front, the results are very encouraging indeed: they enhance

existing literature which lacks of exergames usability

assessments in a standardized way [16][26]. This is of

paramount importance if exergaming/serious games platforms

are supposed to be designed not only as prototype systems, but

as products with an aimed readiness level good enough to be

introduced into the healthy and active aging market [20].

The results obtained with FFA show that its market readiness

is good enough, as the global scores of SUMI and SUS

indicate, thereby interpreting the high levels of users’

perception on usability. As already mentioned before (cf.

TABLE I), commonly accepted design considerations for

developing exergames for elderly [11][14][21][22][25] are

highly related to usability, which seems to be a vulnerable

point in commercial platforms for general audiences

[12][21][24][28]. The high individual scores of the SUMI

scale imply that the FFA platform is tailored to the elderly

population. Controllability and learnability scores, the lowest

of the rest, while well above the average, are justified since the

user base consisted of elderly users with implicit issues in

acquiring new knowledge and subsequently utilizing novel

control schemes [16][58].

Our findings are also consistent with conclusions of earlier

studies that exalted the role of exergames usability and

enjoyment [15][59] to that of motivation and adherence to the

physical exercise protocol [8][10][12][14][25][28][30][32].

While the achieved adherence level (82%) is in line with

previous studies [19], our results should be considered within

the general context of intensive schedules requiring a 5 day

weekly attendance.

A multidimensional, moderately intense activity program that

includes endurance, strength, balance, and flexibility training

is generally considered optimal for older adults [10][52]

contrary to vigorous activity [2][3][4], which affects

adherence negatively [3]. Fullerton post-test improvements of

FFA participants along with the high schedule adherence

levels demonstrate that the FFA platform provided not only

the aforementioned high schedule adherence, but a high

physical exercise adherence too. Moreover, Fullerton results

show statistically significant improvements for all domains of

physical outcomes, in contrary to the vast majority of

literature which reports either improvements simply in

Balance or merely some trends in physical improvements

[10][18][25][27][28][30]. In our case, the FFA group

improves significantly with respect to the control group in all

levels. It is interesting to note, however, that there existed a

statistically significant post-intervention difference in lower

body strength in the control group as well. This could be

attributed to controls' engagement for routine walking activity

(the majority of controls also had to walk from home to pilot

site where the study was conducted a few times a week; thus

there were performing some latent routine aerobic exercise).

The greatest improvement of the WHOQoL-BREF score was

observed in overall living environment and psychology

(including but not limited to evaluation of positive/negative

feelings, self-esteem, memory and concentration) in

consistency with other findings [27]. This could possibly be

attributed to the positive effect of video game playing on

participants' mood as reported in recent literature [13][14].

Naturally and expectedly, the physical aspect of life quality

was significantly improved.

Finally the social domain of the WHOQoL-BREF survey

revealed no statistically significant improvement during the

intervention. However, the between group difference was

statistically significant, thereby probably indicating that FFA's

social impact was significantly more relevant than the simple

socialization experienced by the control group.

From the technical viewpoint, the architecture of this work

incorporated a computerized subset of Fullerton as a formative

assessment component (Fig. 1 Data Layer, Fullerton

Assessment) for purposes of augmented adaptability and

adjustable difficulty. Contrary to other works which consider

the difficulty only on the gameplay axis (objects’ speed and

size, controllers sensitivity, etc.) [9][21][33], the realization of

the FFA architecture perceived the difficulty in two axes: the

gameplay difficulty as well as the physical exercise load. In

order for an appropriately validated set of physical challenges

to be presented in each elderly user, an equally formal,

validated way needed to be incorporated as a criterion for

modifying the physical exercise load. In that context it was

essential that the introduction of a formal assessment

instrument such as the Fullerton, needed to be incorporated as

a formative assessment tool in the platform’s architecture.

Equally important is the fact that this is the first exergame, to

the best of the author’s knowledge, that incorporates in its

architecture design and implementation the standard physical

exercise component (Fig. 1 Semantic Layer, Physical Exercise

Objectives), which refers to planned, structured, and repetitive

movement to improve or maintain one or more components of

physical fitness, contrary to physical activity which refers to

body movement that is produced by the contraction of skeletal

muscles and that increases energy expenditure [2]. This

essentially opens up the way to the next generation of

exergaming platforms which may be adaptive in a smart way.

In fact, the augmented effects of the standard physical exercise

may be the cause of the high adherence since the elders

consider using a system if it is useful, reliable and provides

obvious benefits to their lifestyle [60]. Especially, perceived

usefulness and perceived ease of use are considered as the

main predictors of technology acceptance [61]. With this in

mind, the consideration of standard physical exercises during

design and implementation could serve as an additional

guideline for exergaming design. This implies, as also

suggested by our results regarding perception of better health

control, that incorporating standard physical exercises to

exergames augments the observable effect to the physical state

of the seniors. As a consequence, this would increase elderly

acceptance of exergaming as a legitimate intervention for

maintaining a healthy and independent lifestyle, and thus

perceived as useful for them. According to the literature [60],

such an effect could lead to increased adherence and finally to

successful promotion of exercise to the elderly people. This

could be complementary to the initial motivation which stems

from the joyful experience of the “gaming” component of the

exergames [7][8][9][10][11][12], and also could be the cause

for sustaining this motivation.

A. Limitations

Despite the relatively large sample size of this piece of work

and the exploitation of a cohort of validated tests, some

limitations must be outlined too. As mentioned, comparisons

were done against a non-physically active group that engaged

merely in cognitive exercises. A comparison with a physically

active control (conventional physical exercises, like dancing)

would further empower our findings. Additionally, this study

involved intervention groups with the added social factor

possibly influencing the elderly users’ perception regarding

adherence and QOL. Furthermore, even though this study

consists of one of the longest durations in the field of

exergaming studies, adherence would be better supported by

even longer trials (6 months or more). From the technical

viewpoint, the partial implementation of the assessment test

(four out of six tasks) was a hard limitation of the Wii devices

which is going to be alleviated as soon as technology permits.

V. CONCLUSION

This piece of work reports on the design, implementation and

thorough evaluation through a wide pilot deployment of the

FFA exergaming platform for senior users. Formal assessment

was carried out along two main axes, namely, on user and

efficacy levels. On the usability front, we provide strong

evidence that such interventions are feasible and may be

implemented through contemporary IT systems capable of

motivating seniors to engage with a healthy physical activity

program. On the efficacy axis, quite expectedly, our study

provides strong evidence of physical improvement by means

of clinical tests, but more surprisingly, an even more

significant discovery, is the evidence that the platform

improved the general wellness and quality of life of its user

base. Furthermore, the FFA demonstrated a viable architecture

for incorporating a standard of physical exercises as well as a

computerized subset of Fullerton for accomplishing the

physical status formative assessment towards adjustability and

adaptability. On top of this, the mapping of the guidelines and

the architecture concept to the actual implementation of FFA

provides a concrete illustrative proof of application for the

aforementioned design paradigms.

The relatively large sample size used, in tandem with the

exploited assessment battery may serve as a reference/baseline

for assessing similar platforms in the future. Evolving and

improving access to such a database by providing (semantic

web) ways to exploit the underlying big data structures offers

an unprecedented opportunity certainly worth exploiting [62].

Likewise, the multimodal evaluation methodology could

contribute to the evolution of a gold standard for exergames

evaluation methodology and the results could probably serve

as an initial base for future exergames’ evaluation since this

field gains great importance nowadays. Future studies could

also assess the neuropsychological and neuroscientific impact

of the FFA approach [39][63][64]. Last but not least, the

obtained herein qualitative feedback with regards to the likely

marketability of the product has not only been taken seriously

into account, but already lead to a series of business efforts in

Greece and elsewhere. We deem these achievements as key

response elements of the biomedical engineering and health

informatics scientific communities to the call for

technologically supporting active and healthy aging and the

adoption of future mobile/e-health systems.

ACKNOWLEDGMENT

This research was partially funded by the European

Commission Programme CIP-ICTPSP.2008.1.4 as the Long

Lasting memories (LLM) project (Project No.238904)

(www.longlastingmemories.eu). Authors would like to thank

the whole group of pilot facilitators: Evangelia

Romanopoulou; Maria Karagianni; Eirini Grigoriadou; Aristea

Ladas; Athina Kyrillidou; Anthoula Tsolaki; Stavroula

Fasnaki; Anastasia Semertzidou; Fotini Patera; Efstathios

Sidiropoulos.

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Evdokimos I. Konstantinidis received the

Diploma in electronic engineering from the

Technological Educational Institute of

Thessaloniki, in 2004 and the M.Sc. degree in

medical informatics in 2008 from the Aristotle

University of Thessaloniki, Greece. He is

currently working toward his Ph.D. degree in

the Laboratory of Medical Physics of Medicine, School of

Health Sciences, Aristotle University of Thessaloniki, Greece.

His current research interests lie predominately in the area of

Medical Informatics, particularly with respect to people with

special needs and especially elderly. Recent research interests

focus on intervention for elderly in the field of exergaming.

He has authored more than 30 publications in various

international peer-reviewed journals and conferences.

Antonis S. Billis received his diploma in

Electrical and Computer Engineering in 2007

and MSc in Medical Informatics in 2011, both

from Aristotle University of Thessaloniki,

Greece. He also holds a Ptychio in Business

Administration and Management from the

University of Macedonia, Greece. He is currently working

toward the Ph.D. degree in gerontechnology and works with

the Laboratory of Medical Physics, Medical School, AUTH.

His main research interests lie in the areas of medical decision

support systems, AAL technologies, exergaming and cloud

computing. He has been a member of the technical chamber of

Greece since November of 2007.

Christos A. Mouzakidis was born in

Thessaloniki, Hellas. He graduated from

the Department of Physical Education and

Sport Sciences of the Aristotle University

of Thessaloniki. MSc and PhD in designing

and implementing physical exercise

programs for patients with dementia. He

has participated in several research projects and granted by the

European Commission to implement a physical exercise

program in patients with Alzheimer’s disease. He was

included in the 18th edition of Who is Who in the World

(2001) for his research and scientific activity. He was a

teacher of Physical Education in the Department of Primary

Education, Aristotle University of Thessaloniki (1999-2001),

Physical Education and Sport Sciences, University of Thessaly

(2000-2007) and Military School of Officers (2005-06, 2007-

09 & 2010-...). He is author and co-author in several articles

and book chapters in Hellenic and international journals and

books. He is a reviewer of Alzheimer's Association

International Research Grant Program and Alzheimer’s

Association Journal “Alzheimer’s & Dementia”. Dr

Mouzakidis since 1997 gives lectures and runs workshops

about the development and implementation of exercise

programmes in demented patients and has conducted a lot of

announcements in National and International Conferences. He

is currently working at the Hellenic’s Association of

Alzheimer’s Disease and Related Disorders (Alzheimer

Hellas) Day Care Centre.

Vicky I. Zilidou received the Diploma in

the Department of Physical Education and

Sports Science, from the Aristotle

University of Thessaloniki. She is student at

Postgraduate Program of Studies of Medical

Informatics in School of Medicine, Aristotle

University of Thessaloniki. Her current

research interests are mainly in the Medical Informatics,

particularly in relation to elderly people. She is now working

in a program organized by Department of Physical Education

and Sports Science, Aristotle University of Thessaloniki,

entitled "Traditional dance and dementia".

Panagiotis E. Antoniou is a postdoctoral

research associate in the Lab of Medical

Physics, department of Medicine, Aristotle

University of Thessaloniki. He received a

degree in Physics from Aristotle University of

Thessaloniki in 1997, a M.Sc. degree in

Medical Physics in 2001 from the Democritus

University of Thrace and a Ph.D. degree in Medical Physics in

2004 from Democritus University of Thrace. His research

interests are in the area of Medical Informatics, in the fields of

virtual patients in medical education and in the field of the

elderly exergaming interventions. He has authored more than

25 publications in peer reviewed journals and conferences.

Panagiotis D. Bamidis (M’09) received the

Diploma degree in physics from the Aristotle

University of Thessaloniki (AUTH),

Thessaloniki, Greece in 1990, the M.Sc. (with

distinction) degree in medical physics from

the University of Surrey, Guildford, U.K., in

1992, and the Ph.D. degree in

bioelectromagnetism and functional brain analysis and

imaging from the Open University, Milton Keynes, U.K., in

He is currently an Assist. Professor in Medical Education

Informatics within the Laboratory of Medical Physics,

Medical School, AUTH. He has been the co-ordinator of large

European projects (www.meducator.net;

www.longlastingmemories.eu, www.epblnet.eu,

www.childrenhealth.eu) as well as the principal investigator

for a number of national and international funded projects

(more than 30 in total). His research interests are within

assistive technologies (silverscience, silvergaming, mobile

health, decision support, avatars), technology enhanced

learning in Medical Education (web2.0, semantic web, serious

games, virtual patients, PBL, learning analytics) and Affective

and Physiological Computing and HCI, (bio)medical

informatics with emphasis on neurophysiological sensing and

health information management (open health big data), and

Affective Neurosciences. In 2009, he was awarded the Prize of

the AUTH Research Committee for the Best Track Record in

funded research projects among AUTH young academic staff.

He has been the Chairman/Organiser of six international

conferences (iSHIMR2001, iSHIMR2005, MEDICON2010,

GASMA2010, SAN2011, MEI2012) and the Conference

Producer of the Medical Education Informatics Conference

and Spring School Series. He is a member of the Advisory

Board for the Open Knowledge Foundation (OKFN), a

founding member of OKFN Greek chapter, and a Treasurer

for the Greek Biomedical Technology Society.

Design, implementation and wide pilot deployment of FitForAll: an easy to use exergaming platform...

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