Motivating Older Adults to Exercise at Home: Suitability of a

Humanoid Robot

Esther Ruf, Stephanie Lehmann

and Sabina Misoch

Institute for Ageing Research, FHS St. Gallen University of Applied Sciences, Rosenbergstrasse 59,

9001 St. Gallen, Switzerland

Keywords: Robot, Older Adults, Physical Activity, Exercise, Training.

Abstract: Regular physical activity is a central protective factor for health. The promotion of physical activity is an

important issue, especially for ageing societies, to achieve benefits of health and independence in old age.

However, motivation for physical activity decreases with age. Due to staff shortages and high cost of personal

exercise trainers, older adults living at home cannot be permanently motivated and instructed by health

personnel to engage in physical activity. Several studies investigated the use of a humanoid robot as an

exercise coach for older adults in nursing homes and laboratories, promising great potential. This explorative

user study investigated whether a robot is a practical solution for older adults living in their own home and

can motivate for regular physical activity in everyday life. Seven older adults participated in the study. In the

study period of 12-14 weeks, they completed three different training conditions (instructions by a robot, a

video instruction, and written instructions). Results showed that participants accepted and appreciated the

robot, but most participants would not recommend the robot, mainly because several technical and other

problems occurred. The present study showed that this humanoid robot is not suitable for autonomous exercise

training for older adults at home.

1 INTRODUCTION

Due to demographic change, the proportion of older

adults is rising in all industrialized nations (Vaupel,

2000). Health promotion and prevention are central

issues for our society, especially for the older

population, in order to be able to counteract the future

increase in health costs due to illness and care costs.

One of the most important fields of action is the

promotion of physical activity in old age (Weber et

al., 2016). Regular physical activity is regarded as a

central protective factor for health and is the measure

that shows the most stable evidence of benefits in

terms of health and independence in old age (Büla et

al., 2014). However, physical activity is age-

dependent and motivation for physical activity

decreases with age (Scholes and Mindell, 2012).

Therfore, many older adults don’t move enough

(Krug et al., 2013; Weber et al., 2016). The decrease

in physical activity with increasing age (Bornschlegl,

Fischer and Petermann, 2016) inevitably leads to a

reduction in (functional) everyday abilities

https://orcid.org/0000-0002-1086-3075

(Voelcker-Rehage, Godde and Staudinger, 2006), to

losses in health, self-confidence, self-efficacy,

participation in social life, cognitive abilities and to

loneliness (e.g. Bornschlegl et al., 2016; Füzéki and

Banzer, 2017; Gunzelmann, Brähler, Hessel and

Brähler, 1999). There are many studies that show that

targeted physical training can reduce frailty (e.g.

Löllgen and Leyk, 2012) and thus increase quality of

life and independence (e.g. Dorner and Schindler,

2017). Furthermore, regular physical activity reduces

the occurrence of falls (Müller, Lautenschläger and

Voigt-Radloff, 2016; Sherrington et al., 2016) and

has positive effects on other physical complaints

(Gadde, Kharrazi, Patel and MacDorman, 2011).

Therefore, there is a high need for healthcare systems

to develop effective solutions to ensure the physical

wellbeing of older adults (Čaić, Avelino, Mahr,

Odekerken-Schröder and Bernardino, 2019).

Although information campaigns try to make

older adults aware of the benefits of physical activity,

and various exercise programs promoting physical

activity specifically for older adults exist, it cannot be

Ruf, E., Lehmann, S. and Misoch, S.

Motivating Older Adults to Exercise at Home: Suitability of a Humanoid Robot.

DOI: 10.5220/0009341001130120

In Proceedings of the 6th International Conference on Information and Communication Technologies for Ageing Well and e-Health (ICT4AWE 2020), pages 113-120

ISBN: 978-989-758-420-6

113

guaranteed that older adults integrate physical

activity into their daily lives. For this, it is helpful for

physical activities to be prompted and guided

regularly (Lebedeva et al., 2015). Regular guided

training is more effective than unguided training

(Gschwind and Pfenninger, 2016), and exercise

programmes are beneficial only when followed

regularly and over a long period of time (Gadde et al.,

2011).

Due to staff shortages (World Health

Organization, 2015) and the high cost of personal

exercise trainers, older adults living at home cannot

permanently be motivated and instructed by health

personnel. Robot-guided training could enable older

adults to exercise without a human coach and thus

alleviate this situation and increase the motivation of

older adults to carry out movement programmes in

everyday life.

Several studies investigated the use of a robot as

an exercise coach for older adults. Besides

counteracting the future lack of healthcare staff, a

robotic fitness coach could comply with the

preferences of older adults. It has been shown that

socially assistive robots can positively influence

motivation (Torta, Oberzaucher, Werner, Cuijpers

and Juola, 2013) and that a robot can be very

motivating for seniors to perform physical activity

and might be less boring for seniors than just

performing an exercise session on their own (Werner,

Werner and Oberzaucher, 2013b). In their study,

Shen and Wu (2016) found a strong preference for a

robotic instructor for physical exercise over a human

instructor. Regarding motivation, it was shown that a

humanoid robot instructor was experienced as very

motivating and more motivating than a standard

training plan, but not more motivating than a human

trainer (Werner, Krainer, Oberzaucher and Werner,

2013a). For example, older adults of a day care centre

were able to exercise successfully with the help of a

robot (Görer, Salah and Akın, 2017). It was shown

that a humanoid robot assisting in a demonstration,

attracts onlookers and encourages them to participate

in health exercises (Matsusaka, Fujii, Okano and

Hara, 2009). Lewis, Metzler and Cook (2019)

investigated a humanoid robot in a senior living

community with older adults, caregivers and

administrative staff. They focused on technical

components as well as on affective reactions and

opinions recorded in focus groups. Fasola and

Mataric (2013) found that older adults prefer a

physically embodied robot and a robot which creates

a relation for example through praise (2012).

Inpatients in an assisted living facility adjusted their

movements to a humanoid robot used in geriatric

physiotherapy rehabilitation (López Recio, Márquez

Segura, Márquez Segura and Waern, 2013). Although

technical malfunctions can influence acceptance

parameters (Werner et al., 2013b), even incomplete

prototype systems generated very positive responses

(Gadde et al., 2011). It has been shown that

performing exercises with a humanoid robotic partner

exercising along with the participant boosted the

effort compared to performing these exercises alone

(Schneider and Kümmert, 2016).

Taken together, several studies indicate the great

potential of humanoid robots as instructors and

motivators for physical exercise for older adults.

However, the question of the use of a humanoid robot

as a fitness coach in the private households, where

older adults must perform physical exercises

independently with the robot, is still pending.

Our explorative user study investigated whether

the implementation of a robotic training coach is a

practical and motivating solution to promote regular

physical activity of older adults living at home. The

results show problems and motivating effects. This

research can help to determine ways to support

physical activity amongst older adults.

2 METHODS

2.1 Material

For this study, an exercise program was compiled

based on "Walk safely, stand safely", a program

recommended by Pro Senectute Switzerland for older

adults (www.sichergehen.ch). Three strength

exercises and three balance exercises were selected.

The six exercises were presented in three versions

based on the official video of the Swiss campaign.

Firstly, a booklet with written instructions and

pictures of the exercises, secondly, a video tutorial,

and thirdly, a programmed humanoid robot (NAO

V6, 6

version) acting as an autonomous exercise

coach. The duration of the exercise program

including an introduction and six exercises with

verbal instructions was 36 minutes (for details on the

selection process, programming, and pretest see

Brack, 2019).

A self-developed questionnaire was used.

Sociodemographic data collected were age, gender,

marital status, type of housing, former professional

activities, level of education, and residential area.

Health status was measured with a single item “In

general, would you say your health is… (ranging

from “excellent” to “poor”) from the Short Form

Health Survey (SF-36) (Ware, 2000). To collect the

ICT4AWE 2020 - 6th International Conference on Information and Communication Technologies for Ageing Well and e-Health

114

current physical activity of the participants three self-

developed questions were asked “How often a week

do you exercise?”, “How long does such a session

usually last?”, “Do you do the activities in a group or

alone?”.

To measure self-efficacy, the “Allgemeine

Selbstwirksamkeit Kurzskala” (ASKU) (Beierlein,

Kovaleva, Kemper and Rammstedt, 2012) was used

with three items, and a five-point Likert scale from

“not true at all” to “absolutely true”. Participant’s

technical affinity was measured with two adopted

questions (Seifert and Meidert, 2018) to be

comparable within the Swiss population.

To evaluate the suitability of the robot NAO as an

exercise coach in older adults’ homes, eight questions

(see table 2) based on studies that equally evaluated a

robot as an exercise coach (Fasola and Mataric, 2011,

2012, 2013; Torta et al., 2013; Werner et al., 2013a,

2013b), were compiled using an answer format of a

five-point Likert scale from 1 “not at all” to 5 “very

much”. Because of the explorative character of the

study and the limited number of participants,

qualitative methods were used. They make it possible

to identify important issues and help understand

subjective opinions of participants more in-depth

(Misoch, 2015). A qualitative semi-structured

interview was conducted with the following questions

at the end of the study: (1) Were you able to train

regularly (3 times a week) with the robot NAO? (2)

Were there any difficulties during training? What

didn't work? (3) Was it fun to train with the robot? (4)

Was it motivating for you to train with the robot

NAO? (5) How was the operation of the robot for

you? Were there any difficulties? (6) If you look at

your own experiences, do you think the use of NAO

for older adults to activate movement is generally

possible? (7) Would you like to tell us anything else

about your experience with the robot?

2.2 Study Population

Eight older adults were enrolled in the study.

Inclusion criteria were age over 65 years, no physical

or cognitive restrictions which could impair the

movement training, living in Switzerland and

German-speaking, living in private homes. The older

adults were recruited via the network of senior

citizens of the institute.

2.3 Design and Procedure

The entire study period of this explorative user study

was June 2019 to December 2019. In this period, the

individual participants remained under study

condition for 12-14 weeks.

The study started with an individual appointment

for each participant at the study center (I): After

informed consent and a pre-survey (T0), the

participants were extensively introduced to all three

conditions, and participated in a one-time training

with the robot to get used to the handling, commands,

etc. (see figure 1). The participants were instructed

not to place the robot on a table or other elevation due

to its instability in order to avoid a fall and thus

damage to the robot. After this, the participants were

interviewed using a questionnaire and semi-

structured interview questions (T1).

Figure 1: Older adult trains with robot in the study center.

Image source: Brack, 2019.

Independently at home, each participant then

carried out a training including the three versions of

instruction (written (Condition Booklet; C

), video

(Condition Video; C

), robot (Condition Robot; C

))

according to a predetermined schedule. In each

condition, the participants remained one week and

had to perform the six movement exercises three

times under the respective guidance during this

period. For each condition, they fulfilled a study

protocol. Between each training week there was a

break (B) of two weeks in which the participants were

encouraged not to carry out the study exercises (see

figure 2). After training with the robot, a face-to-face

interview was conducted with the participants at

home (T2). Two weeks after finishing the last

training, a final telephone interview was conducted

with each participant (T3) (see table 1).

In order to avoid effects that could occur due to

the order of the three conditions, the sequence in

which the study participants went through the three

conditions varied. As only one robot was available for

the

study,

the

participants

did

not

all

through

the

conditions in parallel but staggered in time. Due to a

technical failure of the robot it was not possible to

realize the same distance between the conditions for

all participants, the repair lasting longer than three

weeks.

Motivating Older Adults to Exercise at Home: Suitability of a Humanoid Robot

115

Figure 2: Course of the study conditions.

2.4 Analyses

Quantitative data from questionnaires were entered in

IBM SPSS 26. Descriptive statistics (mean, standard

deviation, frequencies) were used to characterize the

sample and evaluate frequencies of the questionnaire

answers. The Wilcoxon signed-rank test (Higgins,

2004) was used to compare motivation to train with

the robot at the introduction and after a one-week

training, as non-parametric tests do not require a

normal distribution of data and are applicable to small

sample sizes.

The statements of the participants in the semi-

structured interviews (T2, T3), were collected based

on written protocols and are summarized and

reported. Due to small sample size and the explorative

character of the study, no further qualitative content

analysis (Mayring, 2000) was worked out.

3 RESULTS

3.1 Participants

Seven older adults participated in the study (P1-P4,

P6-P8), five men and two women. One study

participant could not participate in the study due to

acute physical impairments (P5). The average age of

the participants was 74 years (SD=5.63, Range 67-

84). All participants were Swiss coming from three

different cantons. Five participants described their

current residential area as more rural, two as more

urban. One participant described his general state of

health as excellent, four as very good and two as

good. Five participants had received up to tertiary

level education and five participants lived in a

household consisting of two persons. All participants

said that they were very interested in new technical

objects, and four participants considered themselves

to be very interested, three as interested in

technology. Two participants already had contact

with a robot before at home, one at work, one

somewhere else, and three participants never had

contact with a robot before.

3.2 The Robot as a Training Coach

3.2.1 Experiences

• The participants could all perform the exercises

with the robot.

• The appearance of the robot was perceived as

pleasant.

• The joy of technology and the experience of

something interesting and new was emphasized.

3.2.2 Barriers and Difficulties

Several difficulties in using the robot were reported

by the participants:

Technical:

• It took a long time for the robot to get started.

• The participants had to wait too long to

communicate with the robot, as it takes a long

time for the robot to be operational, and the

robot didn’t react to instructions immediately.

• The older adults had to bend down towards the

robot because the robot didn’t recognize them.

• The robot didn't recognize the face of the older

adults very well and was therefore not ready to

take orders.

• The robot fell backwards while showing the

exercises with six participants.

Acoustic communication problems:

• Computer voice was not optimally

understandable.

• Sometimes the voice was perceived as

strenuous.

ICT4AWE 2020 - 6th International Conference on Information and Communication Technologies for Ageing Well and e-Health

116

Table 1: Survey dates and instruments.

Survey date

Duration (approx.)

Instruments, data

I: Introduction at the study centre 60-90 minutes Informed consent, detailed introduction to the

three conditions (booklet, video,

robot

)

(Part of introduction) T0: face-to face

interview and questionnaire at the study

centre

introduction to the conditions

15 minutes Sociodemographic, question about physical

training, state of health, self-efficacy

(Part of introduction) T1: face-to face

interview and questionnaire at the study

centre after introduction and first training

with

the humanoid robot

15 minutes Self-developed scale robot as fitness coach

T2: face-to face interview at participant’s

home after the one-week training with the

robot

30 minutes Self-developed scale NAO as fitness coach,

semi structured interview including questions

of operation of the robot, problems during

training, motivation

T3: final interview by telephone at least two

weeks after the end of all three conditions

15 minutes Semi-structured interview: state of health,

suitability of the robot, problems, questions

about motivation, experience,

recommendations

General:

• There were too many and too long breaks in

between exercises and the older adults didn’t

know whether the robot was not working, or if

it was an intended break.

3.2.3 Motivational Ability

• The older adults found the training interesting,

exercises attractive and the robot motivating for

physical activity.

• Participants suspect that habituation effects occur

when using the robot for a longer time.

• The vocal instructions were too long and should

be individually controllable because it was boring

for the older adults when the robot always gave

the exact same instructions.

A significant influence of the one-week training

with the robot on the evaluation of the robot as an

exercise coach could not be proven using the self-

developed scale. Wilcoxon-tests show no significant

results (see table 2).

3.2.4 Recommendations of the Participants

• After the study the participants recommended the

robot to be individually adaptable and

personalizable.

• It has been mentioned that the social aspect of

activities is missing, and this is very important

especially for older adults.

• Participants wished for a robot bigger in size, so

bending down to talk to it would not be necessary.

• A memory function, and variation in the

programme and sentence structures was also

requested.

• Announcing break durations and correcting false

movements like a gym teacher were also

suggested.

• In addition, the participants wished for the

instructions of the robot to be compatible with

hearing aids of older adults and requested the

communication with the robot be easier and fully

functional.

4 DISCUSSION

The older adults who trained with the robot

considered the use of a robot at home to motivate

them to do more physical activity. However, the used

robot was judged as not suitable because of its

abilities and the strict sequence of the programmed

movement exercises. Further, the participants thought

robot instructed training could be useful for people

who are not yet physically active, but not for already

active people.

Overall, after the study, the participants would not

recommend the robot for exercise for older adults at

home as they tested it, due to the problems mentioned

above. A possible assignment for the robot was rather

seen as the accompaniment of a human coach. In their

study Čaić et al. (2019) conclude that a robotic coach

can be used to motivate seniors to be more active, but

human caregivers should make sure the elderly users

perform the exercises correctly and assist them if

necessary.

Motivating Older Adults to Exercise at Home: Suitability of a Humanoid Robot

117

Table 2: Change in the assessment of the robot.

Question T1

M (SD)

Wilcoxon-test, exact

significance, one-

sided

How much did you enjoy training with NAO? 4.0 (0.82) 4.43 (0.98) Z = -.828, p = .281,

n = 7

Would you recommend NAO as a training coach to your friends? 2.17 (1.60) 2.50 (1.64) Z = .000, p = .750,

n = 6

How much would you like to train with NAO in the future? 3.14 (1.46) 2.29 (1.38) Z = -1.857, p = .063,

n = 7

Do you find NAO a good training coach? 3.43 (1.40) 2.71 (1.60) Z = -1.089, p = .188,

n = 7

How well could NAO motivate you for the training? 4.00 (1.41) 4.00 (1.73) Z = -.378, p = .500,

n = 7

Do you think NAO is more motivating than a human training

coach?

1.43 (0.79) 1.29 (0.49) Z = -1.000, p = .500,

n = 7

Do you think NAO is more motivating than a training plan with

video instructions?

3.57 (1.27) 2.57 (1.40) Z = -1.382, p = .109,

n = 7

Do you think NAO is more motivating than a written training

plan?

4.71 (0.49) 3.57 (1.62) Z = -1.857, p = .063,

n = 7

The written instructions based on the booklet were

by all participants considered to be the least

motivating. The video condition was judged best.

During the one-week training, the participants

experienced the limitations of the robot (technical

problems, inflexibility, rigidity in repetitions, no

personal approach to the participants) as an obstacle

for further use. The participants would not

recommend the robot to other older adults, and if,

then with restrictions. Much would have to be

technically changed and adapted, and the question of

cost-benefit arises.

As stated in the semi-structured interviews, the

robot's motivational factor quickly diminished when

the novelty effect was exhausted. The effect that users

engage easily in interactions with new technologies,

but their interest in continuous usage decreases

rapidly after a novelty effect vanishes is widely

observed (Rosenthal-von der Pütten et al., 2014).

5 CONCLUSIONS

The programmed humanoid robot was accepted and

was appreciated by the study participants. However,

most of the participants would not recommend the

robot for use for older adults at home, and if so, only

with limitations. The pilot study showed that the

programmed robot is not suitable for autonomous

exercise training for older adults at home. These

statements given by older participants who were

highly motivated and interested in technology should

be taken very seriously.

Some limitations of the study should be noted.

The study was explorative in order to find out what

problems can occur when implementing a robot as a

motivator for training. It was not examined whether

the physical fitness of the participants changed. Due

to the high demands on the participants (12-14 weeks

in study condition, several visits at home, etc.) and the

fact that only one robot was available, only seven

participants were included in the study. The sample is

small and therefore has a limited representativeness,

especially the meaningfulness of statistical

evaluations of quantitative data gathered in this study

is restricted.

Real life testing had some challenges: due to

technical problems of the robot and personal

appointments of the participants, not all of them went

through the study in the same time, and variation of

the three conditions could not be balanced in this

group.

It should also be stated that humans, not robots,

were depicted in the booklet and the video

instructions. In addition, the robot praised the

participants at irregular intervals during the training.

The influence of this reinforcer was not examined.

Regarding the positive evaluations, it must be

considered that the participants are a highly selective

group. They were quite interested in technical

solutions and willing to participate in such a study.

Therefore, it must be assumed that it is very likely to

generate positive evaluations. These should not be

transferred to other groups or the general population.

ICT4AWE 2020 - 6th International Conference on Information and Communication Technologies for Ageing Well and e-Health

118

ACKNOWLEDGEMENTS

We thank all study participants who were willing to

try out the robot at home and gave us their feedback.

Especially, we thank Zoe Brack, who programmed

the robot as part of her master thesis.

REFERENCES

Beierlein, C., Kovaleva, A., Kemper, C. and Rammstedt,

B., 2012. Ein Messinstrument zur Erfassung subjektiver

Kompetenzerwartungen: Allgemeine Selbstwirksamkeit

Kurzskala (ASKU). Mannheim: GESIS - Leibniz-

Institut für Sozialwissenschaften.

Bornschlegl, M., Fischer, R. and Petermann, F., 2016.

Erfolgreiches kognitives Altern: Zusammenhang der

kognitiven Leistungen mit Aktivität und Zufriedenheit.

Zeitschrift für Neuropsychologie, 27, 173-187.

Brack, Z. (2019). Programming and evaluating a robotic

exercise coach to promote physical activity among

elderly people. Master Thesis. ETH, Zurich.

Büla, C., Jotterand, S., Martin, B. W., Bize, R., Lenoble-

Hoskovec, C. and Seematter-Bagnoud, L., (2014.

Bewegung im Alter: Dafür ist es nie zu spät! Swiss

Medical Forum, 14, 836–841.

Čaić, M., Avelino, J., Mahr, D., Odekerken-Schröder, G.

and Bernardino, A., 2019. Robotic Versus Human

Coaches for Active Aging: An Automated Social

Presence Perspective. International Journal of Social

Robotics, 1-16. doi:10.1007/s12369-018-0507-2

Dorner, T. E. and Schindler, K., 2017. Gesundheit im Alter:

Selbständigkeit erhalten, Gebrechlichkeit vorbeugen.

Wien: MANZ'sche Verlags- und

Universitätsbuchhandlung GmbH.

Fasola, J. and Mataric, M. J., 2013. A socially assistive

robot exercise coach for the elderly. Journal of Human

Robot Interaction, 2(2), 3-32.

Fasola, J. and Mataric, M. J., 2011. Comparing physical and

virtual embodiment in a socially assistive robot exercise

coach for the elderly. Center for Robotics and

Embedded Systems.

Fasola, J. and Mataric, M. J., 2012. Using socially assistive

human–robot interaction to motivate physical exercise

for older adults. Proceedings of the IEEE, 100(8), 2512-

2526.

Füzéki, E. and Banzer, W. (2017). Bewegung und

Gesundheit im Alter. In Banzer, W. (Ed.), Körperliche

Aktivität und Gesundheit. Präventive und

therapeutische Ansätze der Bewegungs- und

Sportmedizin (pp. 139-155). Berlin: Springer.

Gadde, P., Kharrazi, H., Patel, H. and MacDorman, K. F.,

2011. Toward Monitoring and Increasing Exercise

Adherence in Older Adults by Robotic Intervention: A

Proof of Concept Study. Journal of Robotics.

doi:10.1155/2011/438514

Görer, B., Salah, A. A. and Akın, H. L., 2017., An

autonomous robotic exercise tutor for elderly people.

Autonomous Robots, 41, 657-678.

Gschwind, Y.J. and Pfenninger, B., 2016. Training zur

Sturzprävention. Bfu-Fachdokumentation 2.104. Bern:

Beratungsstelle für Unfallverhütung.

Gunzelmann, T., Brähler, C., Hessel, A. and Brähler, E.,

1999. Körpererleben im Alter. Zeitschrift für

Gerontopsychologie & -psychiatrie, 12(1), 40-54.

Higgins, J. J., 2004. An introduction to modern

nonparametric statistics. Pacific Grove, CA:

Brooks/Cole.

Krug, S., Jordan, S., Mensink, G. B. M., Müters, S., Finger,

J. D. and Lampert, T., 2013. Körperliche Aktivität.

Ergebnisse der Studie zur Gesundheit Erwachsener in

Deutschland (DEGS1). Bundesgesundheitsblatt, 56,

765-771.

Lebedeva, A., Steinert, A., Buchem, I., Merceron, A.,

Kreutel, J. and Haesner, M., 2015. Trainingskonzepte

seniorengerecht und motivational entwickeln –

Handlungsempfehlungen aus Wissenschaft und Praxis.

8. AAL-Kongress in Frankfurt am Main.

Lewis, L., Metzler, T. and Cook, L., 2019. An Autonomous

Robot-to-Group Exercise Coach at a Senior Living

Community: A Study in Human-Robot Interaction. In

Rapid Automation: Concepts, Methodologies, Tools,

and Applications (pp. 1145-1163). IGI Global.

Löllgen, H. and Leyk, D., 2012. Prävention durch

Bewegung. Bedeutung der körperlichen

Leistungsfähigkeit. Der Internist, 53(6), 663-670.

López Recio, D., Márquez Segura, E., Márquez Segura, L.

and Waern, A., 2013. The NAO models for the elderly.

Proceedings of the 8th ACM/IEEE international

conference on Human-robot interaction, 187-188.

Matsusaka, Y., Fujii, H., Okano, T. and Hara, I., 2009.

Health exercise demonstration robot TAIZO and effects

of using voice command in robot-human collaborative

demonstration. 18th IEEE International Symposium on

Robot and Human Interactive Communication, 472-

477.

Mayring, P., 2000. Qualitative Content Analysis. Forum

Qualitative Sozialforschung / Forum: Qualitative

Social Research, 1(2), Art. 20.

Misoch, S., 2015. Qualitative Interviews. Berlin: Walter de

Gruyter GmbH.

Müller, C., Lautenschläger, S. and Voigt-Radloff, S., 2016.

Potential analysis for research on occupational therapy-

led physical exercise programmes and home

environment adaptation programmes to prevent falls for

elderly people living at home. International Journal of

Health Professions, 3, 85- 106.

Rosenthal-von der Pütten, A. M., Schulte, F. P., Eimler, S.

C., Sobieraj, S., Hoffmann, L., Maderwald, S., Brand,

M. and Krämer, N. C., 2014. Investigations on empathy

towards humans and robots using fMRI. Computers in

Human Behavior. 33, 201–212.

Schneider, S. and Kümmert, F., 2016. Exercising with a

humanoid companion is more effective than exercising

alone. 16th IEEE International Conference on

Humanoid Robots, 495-501.

Motivating Older Adults to Exercise at Home: Suitability of a Humanoid Robot

119

Scholes, S. and Mindell, J., 2012. Physical activity in

adults. Health Survey for England, 1(2), 1-49.

Seifert, A. and Meidert, U., 2018. Quantified seniors.

Prävention und Gesundheitsförderung, 13, 353-360.

Shen, Z. and Wu, Y., 2016. Investigation of practical use of

humanoid robots in elderly care centres. Proceedings of

the 4th International Conference on Human Agent

Interaction, 63-66.

Sherrington, C., Michaleff, Z. A., Fairhall, N., Paul, S. S.,

Tiedemann, A., Whitney, J., Cumming, R. G., Herbert,

R. D., Close, J. C. T. and Lord, S. R., 2016. Exercise to

prevent falls in older adults: an updated systematic

review and meta-analysis. British Journal of Sports

Medicine, 51, 1750-1758.

Torta, E., Oberzaucher, J., Werner, F., Cuijpers, R. H.,

Juola, J. F., 2013. Attitudes towards socially assistive

robots in intelligent homes: results from laboratory

studies and field trials. Journal of Human-Robot

Interaction, 1(2), 76-99.

Vaupel, J., 2000. Setting the stage: a generation of

centenarians? The Washington Quarterly, 23(3), 197-

200.

Voelcker-Rehage, C., Godde, B. and Staudinger, U. M.,

2006. Bewegung, körperliche und geistige Mobilität im

Alter. Gesundheitsschutz, 49, 558-566.

Ware, J. E., 2000. SF-36 health survey update. Spine, 25,

3130-3139.

Weber, D., Abel, B., Ackermann, G., Biedermann, A.,

Bürgi, F., Kessler, C., Schneider, J., Steinmann, R. M.

and Widmer Howald, F., 2016. Gesundheit und

Lebensqualität im Alter. Grundlagen für kantonale

Aktionsprogramme «Gesundheitsförderung im Alter»

(Bericht 5) Bern: Gesundheitsförderung Schweiz.

Werner, F., Krainer, D., Oberzaucher,J. and Werner, K.,

2013a. Evaluation of the acceptance of a social assistive

robot for physical training support together with older

users and domain experts. Assistive Technology: From

Research to Practice: AAATE, 33, 137-142. doi:

10.3233/978-1-61499-304-9-137

Werner, F., Werner, K. and Oberzaucher, J., 2013b.

Evaluation of the acceptance of a socially assistive

robot by older users within the project KSERA.

Proceedings: Lebensqualität im Wandel von

Demografie und Technik. Deutscher AAL-Kongress.

World Health Organization, 2015. World report on ageing

and health. Geneva: World Health Organization.

ICT4AWE 2020 - 6th International Conference on Information and Communication Technologies for Ageing Well and e-Health

120