Journal of Robotics, Networking and Artificial Life
Vol. 7(3); December (2020), pp. 179–183
DOI: https://doi.org/10.2991/jrnal.k.200909.008; ISSN 2405-9021; eISSN 2352-6386
https://www.atlantis-press.com/journals/jrnal

Research Article

Body and Brain Training for Falls Prevention
Henrik Hautop Lund*, Yan-Xin Liu, Massimiliano Leggieri
Center for Playware, Technical University of Denmark, Building 326, 2800 Kgs., Lyngby, Denmark

ARTICLE INFOABSTRACT

Article History

The paper presents the pilot test of the Moto Tiles Body & Brain Test combined with automatically generated individualized
training protocols. The test is performed with seniors (avg. 80 years old) with mild dementia in senior care centers in Roskilde,Denmark. The seniors performed pre- and post-test on tests correlated with timed-up-and-go, chair-to-stand, and four square
stepping test. During the intervention, the dementia-affected seniors performed their individualized training on the Moto Tiles
games over 3 weeks with an average total of nine sessions of 7 min each. On average, the seniors improve 41%, 31%, 42% and 3%
on the four tests. In terms of cut-points for multiple falls risk, the seniors are at high risk at pre-test, while they are at low risk atpost-test. This indicates that the very short time (1 h over 3 weeks) playful training on Moto Tiles can potentially bring seniors
from high risk of falling to a much lower risk of falling. The present study is a small pilot test, and results should be verified in
randomized controlled trial(s).

Received 25 November 2019
Accepted 27 May 2020
Keywords
Playwaregamingaging
falls prevention© 2020 The Authors. Published by Atlantis Press B.V.
This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).

1. INTRODUCTION
Playful training can have a dramatic and fast effect on the healthof seniors, as has been shown in Lund [1], Lund and Jessen [2],Lund and Jessen [3], Liu et al. [4]. The high effect of play on thesenior health seems to arise as a collateral health effect of the play.
Play acts as an intrinsic motivation, and a playware tool such as theMoto Tiles mediates a playful physical interaction of the seniors.
Play is a free and voluntary activity that we do for no other purpose than play itself. When in play, we can often do more than wewould normally be able to do, because we get into a play dynamics
in which we forget about time and place. In the play dynamics, weforget about our fears and limitations. A play force – such as theplayware tool Moto Tiles – pushes the seniors into the play dynamics, and when fear and limitations are forgotten, the seniors areperforming playful movements that they would otherwise seldom
make. This seems to be the qualitative explanation of the high andfast effects seniors experience on physical functional abilities andcognitive abilities when playing with the Moto Tiles.
It is of high interest to understand within a population, who shouldbe training to increase their abilities. Who is at high health risks?
As described in Lund et al. [5], the play on the Moto Tiles can beused as a valid senior health screening tool, e.g. for falls risks.
Falls is a major concern for senior’s health. In the United States,
about 40% of the population age ≥65 living at home will fall at least
once each year, and the rates are much higher for persons aged
>75 years of age and persons living in long-term care institutions[6]. Previous work [7] has shown that there is a strong correlation
between Moto Tiles game tests and standard health tests such as
Corresponding author. Email: hhl@playware.dtu.dk*

timed up & go [8], chair stand [9], and four square step test [10].
Based on the strong correlation with the standard health tests,
Lund et al. [5] showed that there are validated cut-points formultiple falls risks in the scores on the Moto Tiles games. As mentioned there, “the scoring in the Moto Tiles games Color Race
<19 points, or Special One <13 points, or Final Countdown<20 points indicates a high risk of multiple falls” [5].
Importantly, the screening of seniors health by playing the MotoTiles games not only provides a mapping of the individual physicaland cognitive abilities, but can also provide an automatically generated personalized training protocol to follow after the screening, sothat the right kind of abilities are addressed in the play on the Moto
Tiles for each individual senior.
In this work, we will look at a first pilot test of such screening
and playful Moto Tiles training with automatically generated
personalized training protocols.

2. INTERVENTION
The pilot test was performed with 12 seniors with mild dementia
from Seniorhøjskolen in Roskilde, Denmark. They were average
80 years old. They were pre- and post-tested with the Moto Tiles
Body & Brain Age Test (see [5]), and had an intervention of
3 weeks, during which they played average nine sessions of Moto
Tiles training. The games and duration of games were automatically generated for each individual senior. They performed threecycles of the loop in Figure 1.
Accordingly, first each senior performed the 2 min Moto Tiles Body& Brain Age Test composed of four test games of 30 s each. Thenthe system makes a performance and risk analysis based on the score

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in the four games. The analyses is presented to the senior, and thesystem uses the analysis to provide recommendation and to automatically create a personalized training protocol for the senior (see [5]).
Then the senior performs a number of training sessions with thisprotocol. In the present pilot test, the senior performs three sessions
over the following week. After those sessions, the senior will again
perform the 2 min Moto Tiles Body & Brain Age Test, and a new
personalized training protocol is generated and will be used for thesessions in the following week. And so the cycle continues (Figure 1).
The 2-min Moto Tiles Body & Brain Age Test is based on four MotoTiles games, each evaluating some body or brain abilities. Each ofthese games called Color Race, Special One, Final Countdown, andRemember (Simon Says in a newer version) lasts for 30 s making
the test last for just 2 min in total. The physical layout of the Moto
Tiles is six tiles in a horseshoe shape as shown in Figures 2 and 3.
The performance analysis is based on comparing the users scoreswith the normative scores of the users age. These normative scores
are collected previously with a Big Data approach [5]. The difference from the normative scores is used to calculate the ability

Figure 3 | A lady 80 years of age performing the 2-min Body & Brain Age
Test in her private home.
Table 1 | Score on the test games based on the seven participants whocompleted all the three tests
Color Race

Figure 1 | The intervention loop with the Moto Tiles Body & Brain Age
Test, risk analysis, and automatically personalized training protocol.
Seniors perform the Moto Tiles training for a number of sessions before
they again take the Moto Tiles Body & Brain Age Test.

AverageChanges
Changes (%)

13.6

140.4
3.2

19.1
5.6
41

AverageChanges
Changes (%)

10.6Special One
10.6
00

13.9
3.3
31

AverageChanges
Changes (%)

Final Countdown
13.3
13.4
0.1
1

18.9
5.6
42

AverageChanges
Changes (%)

Remember error rate
0.6
0.5
−0.02
−3

0.5
−0.02
−3

scores (each as a value 0–100) for the users speed, agility, endurance, balance, memory, concentration and orientation.
The personalized training protocol is generated automatically basedon these ability scores of the user. Seven games are chosen for theprotocol: Color Race, Special One, Final Countdown, Reach, Hit theTarget, Simon Says, and Concentration. In order to choose appropriate games for the training protocol, each game is firstly assigned witha weight (see [5] for details) according to the score on the abilities
associated with that particular game. Then the number of games N
and total training time T are defined. In the present, first trial, N = 2and T = 7 min. In later weeks of the training, N is raised to 3. The firstN games with greatest weights are selected for the training protocol.

3. RESULTS
Figure 2 | The Moto Tiles layout for the Body & Brain Age Test.

Table 1 shows the scores of the seven participants who performed
all tests (pre-test, mid-test, post-test). It shows the average score

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on each of the four test games and the percentage change from thepre-test. As can be seen, on average the seniors improve their testscores with 41%, 31%, 42%, and 3% on the four test games.

memory ability. So the new automatically generated personalized
training protocol for the following week puts more focus on speed,
agility and balancing:Also, in terms of the actual score on the test games, it can be seenthat in pre-tests, the seniors score well below the cut-point for
multiple falls risk, i.e. Color Race < 19, Special One < 13, Final
Countdown < 20, so they are at high risk of falling. At the post-test,in both Color Race and Special One, the seniors are scoring above
the cut-point, indicating that they have improved their skills to alevel where they are no longer at the high risk of falling.

Second training protocol: Color Race * 2, Final Countdown * 4,Special One * 1.

In order to better understand how the personalized training
protocol is generated automatically for the individual senior based
upon the score in the 2 min Moto Tiles Body & Brain Age Test, let
us take a look at two examples.
The first example is a male aged 67 years of age. His test scores areshown in Table 2. At the first test, he scores 25, 17, 26 and 0.556 on
the four test games. Based on the performance in the first test, thespider web showing his score on the different physical and cognitive abilities is generated – see the blue dots in Figure 4.
As can be seen, he scores comparably low in the memory ability
and a little low on the speed ability. This results in the automatically generated personalized training protocol being generated to
become as follows for the first week of training:

At the third test, he scores 32, 18, 42, 0.385 (Table 2), and as can beseen on the spider web (Figure 4), he scores very well in all abilities.
As a second example, let us look at a female participant aged 65
years of age. Her test scores are shown in Table 3. In the first test,
she scores low with 13, 10, 4, 0.778 in the four tests. Figure 3 shows
the performance of the first test with the blue dots in the spider
web. As can be seen, the balancing, speed and memory abilities arevery low. So the first training protocol is generated to put focus ongames training these abilities in combination:
First training protocol: Color Race * 4, Special One * 3
In the second test, she scores 12, 9, 5, 0.563, so the memory ability
has improved (Figure 5), and therefore the next automatically generated personalized training protocol puts less emphasis on games
for memory abilities, and more focus on games for balancing, speed
and agility:
Second training protocol: Color Race * 3, Final Countdown * 2,Special One * 2.

First training protocol: Final Countdown * 4, Simon Says * 3.
Indeed, these two games put specific focus on speed and memory,and he would be playing these 4 min Final Countdown and 3 min
Simon Says at each session over the first week of training.

4. DISCUSSION

Then, at the second test he scores 25, 17, 24, 0.333 (Table 2),
and the red dots in Figure 2 shows how he has improved in theAs has been shown, the Moto Tiles games can be used as healthtests for the seniors, and scoring Color Race <19 points, or Special
One <13 points, or Final Countdown <20 points indicates a highTable 2 | Score on the test games for a male participant

Table 3 | Score on the test games for a female participant

Color RaceSpecial One
Final Countdown
Remember

Test 1

Test 2

Test 32517260.556

25
17240.333

32
18420.385

Figure 4 | The performance of a male participant in three tests.

Color RaceSpecial One
Final CountdownRemember

Test 1

Test 2

Test 3131040.778

12950.563

161290.5

Figure 5 | The performance of a female participant in three tests.

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risk of multiple falls. In the case of the pilot tests, the average scoreof the seniors after training with the personalized protocols took
the average from indicating high risk of falling in the Color Raceand Special One scores to a level above the cut-points indicating
lower risk of falling.
In the qualitative evaluation based on interview, the therapist
evaluating the pilot test expressed that “the customized training isperfect because it targets to the individual weakness”.
It is observed that in the Remember game, there were someparticipants who got a higher error rate. This can be because
their memory did not change over the short intervention
period (still cannot remember many colors), but their mobility was improved, so they could have more guesses (but mostwere wrong), and this resulted in a higher error rate. In future,
another memory game (Simon Says) with a different interaction
pattern will be tested for inclusion in the 2-min test to alleviate
this issue.
The high increase, which is noticed (31–42%) may contain sometest–retest effect. Also, the pilot test did not include a control group
to compare. Hence, one should view the present tests merely as apilot test. Randomized controlled trial(s) is needed to confirm theindications of the pilot test.

CONFLICTS OF INTEREST
The authors declare they have no conflicts of interest.

ACKNOWLEDGMENTS
The authors would like to thank all participants of this experiment.
Part of the work was produced as part of the EU Horizon 2020
project REACH under grant agreement no. 690425.

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[2] H.H. Lund, J.D. Jessen, Effects of short-term training ofcommunity-­dwelling elderly with modular interactive tiles,
Games Health J 3 (2014), 277–283.
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randomized controlled trial, Proceedings of 18th International
Symposium on Artificial Life and Robotics (ISAROB), Japan, 2013.
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[5] H.H. Lund, Y.X. Liu, M. Leggieri, Big data and AI approachfor body and brain test for seniors, J. Robot. Netw. Artif. Life 6(2020), 270–273.
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[8] A. Shumway-Cook, S. Brauer, M. Woollacott, Predicting theprobability for falls in community-dwelling older adults using
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AUTHORS INTRODUCTION
Prof. Henrik Hautop Lund
He is at Center for Playware, TechnicalUniver­sity of Denmark, is World Championin RoboCup Humanoids Freestyle 2002,
and has more than 200 scientific publications and 5000 citations. He was awarded
the Most Outstanding Healthcare Innovatorin the World in 2019. Over the last year, he received international awards in Tokyo, Singapore, and London. He has developed shape-shifting modular robots, presented to the emperorof Japan, and has collaborated closely on robotics and AI withcompanies like LEGO, Kompan, BandaiNamco, Microsoft,Mizuno. He is the inventor of the Moto Tiles (www.moto-tiles.
com), which are used by seniors all around the world.

Mr. Yan-Xin Liu
He is a Research Assistant at Technical
University of Denmark. He holds a Masterengineering degree from 2018 fromTechnical University of Denmark. He iscurrently pursuing his PhD at Depart­
ment of Physics, Technical University ofDenmark.

H.H. Lund et al. / Journal of Robotics, Networking and Artificial Life 7(3) 179–183

Mr. Massimiliano Leggieri
He is an Engineering Researcher at Centerfor Playware, Technical University ofDenmark. He is specialized in Software
Engineering and Playware. He has developed apps such as the Music Tiles andMoto Tiles app, and has won severalawards with the Moto Tiles development.

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