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Monitoring and Supporting Engagement in Skilled Tasks: From Creative Musical Activity to Psychological Wellbeing

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While good physical health receives more attention, psychological wellbeing is an essential component of a happy existence. An everyday source of psychological wellbeing is the voluntary practice of skilled activities one is good at. Taking musical creation as one such skilled activity, in this work we employ an interaction method to monitor varying levels of engagement of musicians improvising on a desk-top robotic musical interface (a network of intelligent sonic agents). The system observes the performer and estimates her/his changing level of engagement during the performance , while learning the musical discourse. When engagement levels drop, the musical instrument makes subtle interventions, coherent with the compositional process, until the performer's engagement levels recover. In a user study, we observed and measured the behaviour of our system as it deals with losses of performer focus provoked by the controlled introduction of external distractors. We also observed that being engaged in our musical creative activity contributed positively to participants' psychological wellbeing. This approach can be extended to other human activities.
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Monitoring and Supporting Engagement in Skilled Tasks: From Creative
Musical Activity to Psychological Wellbeing
Juan Carlos Vasquez, Koray Tahiro˘
glu, Niklas P¨
oll¨
onen
Department of Media
Aalto University
School of ARTS
FI-00076 AALTO Finland
firstname.lastname@aalto.fi
Johan Kildal
IK4-TEKNIKER
I˜
naki Goenaga 5
Eibar 20600
Spain
johan.kildal@tekniker.es
Teemu Ahmaniemi
Nokia Technologies
Espoo, Finland
teemu.ahmaniemi@nokia.com
ABSTRACT
While good physical health receives more attention, psy-
chological wellbeing is an essential component of a happy
existence. An everyday source of psychological wellbeing
is the voluntary practice of skilled activities one is good at.
Taking musical creation as one such skilled activity, in this
work we employ an interaction method to monitor varying
levels of engagement of musicians improvising on a desk-
top robotic musical interface (a network of intelligent sonic
agents). The system observes the performer and estimates
her/his changing level of engagement during the perfor-
mance, while learning the musical discourse. When en-
gagement levels drop, the musical instrument makes sub-
tle interventions, coherent with the compositional process,
until the performer’s engagement levels recover. In a user
study, we observed and measured the behaviour of our sys-
tem as it deals with losses of performer focus provoked by
the controlled introduction of external distractors. We also
observed that being engaged in our musical creative ac-
tivity contributed positively to participants’ psychological
wellbeing. This approach can be extended to other human
activities.
1. INTRODUCTION
Through life, individuals develop skills in activities that
they find interesting and at which they excel. Such skilled
activities often combine intellectual, crafting and creative
dimensions: from cooking and knitting to writing, drawing
or, in this case, performing with a new musical interface.
Practising such activities in an autonomous and voluntary
way can bring great satisfaction and sense of purpose to a
person, who finds the opportunity to challenge the limits of
one’s own acquired mastery. The confluence of these three
characteristics in an occupation - autonomy, mastery and
purpose - has been identified and persuasively proposed as
a popular recipe for personal fulfilment at work [1]. In the
wider scope of life, these three characteristics are also part
Copyright: c
2017 Juan Carlos Vasquez, Koray Tahiro ˘
glu, Niklas P ¨
oll¨
onen et
al. This is an open-access article distributed under the terms of the
Creative Commons Attribution 3.0 Unported License, which permits unrestricted
use, distribution, and reproduction in any medium, provided the original author
and source are credited.
of a set of six ingredients that have been identified as im-
portant for a healthy, actively-positive psychology in adult
life: autonomy, (environmental) mastery, purpose (in life),
self acceptance, positive relations with other people and
personal growth [2]. Psychological wellbeing is an essen-
tial aspect of general wellbeing that traditional medicine
does not take care of as a priority in every case. However,
it is essential for a happy existence, and being engaged in
skilled tasks provides much of such satisfaction and subse-
quent psychological wellbeing [3].
In the work that we present here, we focus on exposing
the centrality of the individual’s engaging experiences in
psychological-wellbeing enhancing musical activities. We
seek to amplify the experience by mediating between the
person and the activity in two complementary ways: (i) by
monitoring the level of engagement of the person during
a musical activity, and (ii) by having the object of the ac-
tivity itself respond in subtle but meaningful ways to the
music composition led by the person, in order to main-
tain consistently high levels of engagement. We build on
work that we developed earlier [4], regarding the machine
recognition and monitoring of the engagement level of an
individual that is immersed in a musical task with digi-
tal environments. The work so far has focused on recog-
nising levels of immersion of musical performers during
creative improvisation with a desktop Network Of Intelli-
gent Sonic Agents (NOISA), the musical instrument itself.
By combining the monitoring of facial expressions, bodily
movements, actions of the hands and the evolution of the
sonic production, an initial setup has been validated to suc-
cessfully estimate levels of engagement at each time of the
creative musical process [5].
As the main technical contribution of this paper, we add
to the engagement monitoring functionality that NOISA
had, a new response module, which preserves high levels
of engagement in a musical activity when these appear to
fade. In this paper, we report a new study conducted in
the new NOISA environment that aimed at evaluating the
functionality of the response module and the music compo-
sition task’s effect on the participant’s psychological well-
being. First, we evaluated the system’s functionality to
identify instances in which we observe a drop in the level
of engagement of the person with the musical activity. Sec-
ondly, we evaluated the response module’s functionality to
intervene in subtle ways in order to “rescue” dropping lev-
Proceedings of the 14th Sound and Music Computing Conference, July 5-8, Espoo, Finland
SMC2017-188
els of engagement back to higher levels that are associated
with a satisfactory creative experience. Lastly, as happi-
ness and wellbeing crucially depend on the activities we
engage in [3], in this user study we aimed at understand-
ing whether a satisfactory musical experience could indeed
contribute towards the preservation of psychological well-
being, as we proposed in the beginning.
2. RELATED WORK
In spite of being a commonly mentioned parameter in mu-
sic research, the mere act of obtaining a unified and con-
sistent definition for ‘engagement’ represents a surprising
challenge. In the field of education, Appleton [6] points
the discussion towards separating engagement from mo-
tivation: the latter [7] provides an answer to the reason-
ing behind a specific behaviour depending on the charac-
teristics of the personal energy invested in said situation,
whereas engagement refers to the level of focused involve-
ment [8], or “energy in action, the connection between per-
son and activity” [9]. When applied to musical activity, en-
gagement may also have a positive connotation, described
as a state of sustained, undivided attention and emotional
connection towards creative musical performance [10] or
sometimes as a neutral parameter prone to be measured
and evaluated in interdependent values for attention, emo-
tion and action [11].
Similarly, there are other studies exploring music as a
creative activity that contributes to the general wellbeing.
An example demonstrates how active music-making im-
proves wellbeing and overall comfort in a large sample of
hospitalised children with cancer [12]. This study draws
upon previous research featuring live music therapy that
promotes interaction through voice and body expressions,
recognising the benefits of interactivity in opposition of lis-
tening passively to music as a therapy [13]. While previous
studies delineate a methodology for therapy rather than the
design of an interactive system, there are examples of in-
teractive tools aimed at positively impacting in wellbeing
through rhythmical movement with music as a central ele-
ment [14, 15]. There is also the precedent of an interactive
application to engage patients with dementia in active mu-
sic making without pre-existing skills [16]. In the same
vein, we found an interactive technology tested in children
with disabilities and aimed to study how music interaction
can “become potentially health promoting” [17].
As a concept, psychological wellbeing is subjective, rel-
ative and prone to change with ease. However, it is pos-
sible to find specific sonic characteristics that have proven
to affect positively an individual’s perception of comfort
and wellbeing. For instance, in the context of music, some
studies indicate that fast and slow tempos are associated
with happiness and sadness, respectively, as are major and
minor modes [18, 19]. Loud music has proven to be in
cross-cultural studies as an universal cue for anger [20].
Timbre is ambivalent, although several studies indicate that
attenuation of high frequencies can be a difference between
anger (unfiltered) and tenderness (attenuation) [19]. Al-
though affective associations of both tempo and mode are
fairly well established, effects of other musical character-
istics are poorly understood. On the cognitive level, David
Huron’s ITPRA (Imagination-Tension-Prediction-Response-
Appraisal) theory studies the relationships between affec-
tive consequences and expectancies in music [21], estab-
lishing clear connections. Evidence also suggests that some
auditory illusions, such as Binaural Auditory Beats, are as-
sociated with less negative mood, notably affecting perfor-
mance in vigilance tasks of sustained concentration, par-
ticularly when they occur in the beta range (16 and 24
hz) [22].
Regarding the concept of musical interaction being per-
ceived as rewarding, the Orff approach states that improvi-
sation with pentatonic scales, with bars and notes removed,
is always satisfactory and encourages freedom from the
fear of making mistakes [23]. The goal is for everybody
to experience success and appreciate the aesthetic in music
almost immediately, rather than having to learn notes and
rhythms before anything satisfying is accomplished. Per-
cussive patterns were important in his theory, as they ap-
peal to a primal essence in human beings and allow tempo
and beat to be experienced rather than learned. We in-
corporated many of these ideas into our work while de-
signing the response module and its implementation in a
music-making creative activity that can link cognitive fea-
tures and physical movements together to pay attention for
immediate responses. This is a generic hypothesis of re-
search in cognitive neuroscience of music and the concept
of music, mind and body couplings that our project takes
into account [2, 24]. The former points out the benefits of
music as a therapeutic tool and it can improve recovery in
the domains of verbal memory and focused attention. The
latter indicates its impact on social and individual develop-
ment through active engagement with music.
3. NOISA
As mentioned, NOISA (Network Of Intelligent Sonic Agents)
is the robotic musical interface that we took into use and
built on for this research work. NOISA consists of three in-
struments for music creation, a Microsoft Kinect 2 camera
and a central computer. The three instruments are phys-
ically identical from each other. Each instrument is built
inside a plastic box. The interface for playing each in-
strument consists of two handles designed to provide an
ergonomic form for grasping them from several directions,
which can also position themselves actively, thanks to DC
motors (the robotic interactions with the physical medium).
The handles are attached to a motorised fader, which served
both as position indicator and as active position controller.
The hardware in each box includes an Arduino, a Rasp-
berry Pi, two motorised faders with extra large motors, two
capacitive touch sensors on the handles, and an embedded
speaker. In each instrument, sound production is largely
based on granular synthesis and phase vocoder algorithms
de-fragmenting radically small fragments of pre-existing
pieces from the classical music repertoire.
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SMC2017-189
3.1 Response Module
Based on Huron’s ITPRA theory, we concluded that work-
ing in a stronger Prediction-Response musical connection
would likely produce an affective response evaluated as
positive [21]. Huron also proposes that recognisable pat-
terns are a common characteristic in music associated to
positive emotional responses. Thus, we decided that for
the current iteration of NOISA, the system would recog-
nise, store and playback musical patterns of 2 seconds of
activity, which the performer could easily identify based
on the data inputted. In order to avoid to solely repro-
duce an exact copy of the gesture performed by the per-
former, we also programmed a set of variations, based on
the music composition technique of motivic-through com-
position, also known as thematic development. This tech-
nique has been used successfully in classical music from
the common practice period (barroque to late XIX cen-
tury), and also in post-millennial music, including main-
stream genres [25].
We defined the gesture by recording a maximum of seven-
second long movements. The data recorded included the
engagement value, device identification, energy (measured
in decibels), spectral centroid (average of most prominent
frequency ranges over time), movement of the handlers and
time-stamps. Recording was initiated when a new move-
ment was detected, and stopped when inactive for longer
than one second. The gesture playback was activated de-
pending on the performer’s engagement in the task, activat-
ing more often when the engagement was low. The play-
back gestures were then chosen from a fifteen-minute inter-
val. Gesture data was measured against weights that were
defined by the energy mean value, spectral centroid, spec-
tral energy and amount of time elapsed since the recording
was made. The result was that, when the engagement was
higher, a larger set of chosen gestures was used. When
lower, newer patterns were chosen matching the readings
from the performers currently playing, to make the pattern
more recognisable.
The first choice of instrument for playback (out of the
three autonomous sonic agents) was the instrument on which
the gesture to be reproduced had been recorded. If that in-
strument was in use at that time, one of the other two in-
struments was randomly selected instead. There were four
variations of response playback: the recording itself, an
inverse (negative), a reverse and an inversed-reversed ver-
sion of the recording. The inverse was mapped into the
right range with the help of the highest and the lowest val-
ues. The engagement level of the performer was the de-
ciding factor for the chosen gesture variation. When less
engaged, the pure recording was the most common choice.
When engagement became higher, the performer experi-
enced a larger set of variations.
3.2 Hardware Design
The new response module required more precision than the
initial NOISA design could handle, so a new inner struc-
ture for the instrument was designed. Most of the hardware
parts were custom made with 3D printing, computer nu-
merical control (CNC) milling and laser cutting (see Fig-
Figure 1. New interface design of the NOISA instrument
ure 1). After a few iterations we reached the current state.
Aluminium tubes were added to make the handles stronger
yet light. The slide-bearings for the aluminium tubes were
CNC-milled for an exact fit. The handles were redesigned
to manipulate the added weight, using additional timing
belts and aluminium pulleys. The benefit of these changes
was lower friction from the handles. For the outer shell
to be strong enough to hold the new structure, we added
supporting layers and attached everything together with
custom-made corner-irons. The handles of the instrument
were also redesigned, with holes for the aluminium rods
and added space for the pressure sensors. To detect the
pressure, two pressure-sensitive conductive sheets were sand-
wiched between layers of copper tape. By reading the
change of the resistance, the amount of pressure could be
detected.
4. USER STUDY
To review our main research goals in this work, we wanted
to observe, first, if participating in the skilled activity of
improvising music with our accompanying robotic instru-
ment showed any signs of being subjectively beneficial for
people. Such outcome would suggest that our improvi-
sation activity might be eligible as one of the many pos-
sible skilled tasks in the scope of this study (see again
our discussion about this in the introduction). Second, we
wanted to observe our interactive system in action, both
monitoring the levels of engagement with the activity (a
functionality already validated for earlier versions of this
instrument), and, more crucially, intervening (i.e., coach-
ing) when the performer’s level of engagement dropped to
low levels. As the main technical contribution, we wanted
to observe if the system was able to refocus the flow of the
performer’s activity until higher engagement levels were
again measured.
To do all of that, we designed and conducted a two-part
user study in which 15 voluntary participants (8 females)
took part. The first part aimed at recording a subjective
measure of wellbeing before and after a performance ses-
sion in which a person could improvise under normal con-
ditions. In the second part, in contrast, we provoked the
loss of focus of the participant in the improvisation activ-
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Figure 2. Users developing the task
ity, and we observed if the system could observe the corre-
sponding drop in engagement, and if the instrument could
intervene collaboratively until engagement was recovered.
After a general description of the whole session and af-
ter obtaining consent, the first part of the user study started
with the participant filling out the PANAS questionnaire
(The Positive and Negative Affect Schedule) [26]. This is a
validated questionnaire that evaluates positive and negative
affects using a psychometric scale, and the change in those
within a specific period of time during which some treat-
ment activity took place (in our case, a performance ses-
sion with our collaborative musical instrument). PANAS
uses 10 descriptors per category of affects, showing rela-
tions between them with personality stats and traits. PANAS
has been successfully applied to measure overall psycho-
logical wellbeing before, and after a musically creative ac-
tivity [27]
The participant was then introduced to the NOISA instru-
ment, with explanations about how it works, followed by
a period of hands-on familiarisation with it (typically for
about three minutes). Once the participant felt confident
enough, the first music performance task was described,
which required performing a piece according to a some-
what restrictive set of rules (we wanted to reduce variabil-
ity in the performing activities at this stage in the study). In
particular, the participant would be asked to start perform-
ing with a specific instrument (Agent 1), then repeat the
given gesture with the middle instrument (Agent 2), finish-
ing with inputting the same repeated movement in the third
instrument (Agent 3), resulting in a piece that lasted for be-
tween three and five minutes. Once this was done, NOISA
would have typically started to make automatic responses.
At this moment, the participant was asked to explore freely
any of the agents, and once the participant was ready to fin-
ish, she/he had to manipulate the handles in Agent 1. The
participant was required to stop any input activity as an in-
dication of the end of the music task.
After finishing the task, the participant was asked to fill
in again the PANAS Questionnaire in order to compare
the impact of the task in the overall sense of psychologi-
cal wellbeing. Following that, the participant was asked to
evaluate the system’s usability by filling in the online ver-
sion of the System Usability Scale (SUS) designed by our
research group to facilitate the data gathering and analy-
sis. SUS has ”provided with that high-level measurement
of subjective usability, and over the years the work done by
other researchers has indicated that it is a valid and reliable
tool” [28].
For the second part of the study (designed to observe
the engagement tracking and recovery functionalities of
our interactive system), we asked the participant to repeat
the same musical task, extending it for a period of four
minutes. This time we tracked and logged the level of
engagement over time. We scheduled two events suffi-
ciently distracting at 1:30 (door opening, person coming
in and loudly manipulating a cardboard box) and a more
sublte event at 3:00 (phone ringing). We drew inspiration
from previous studies measuring the impact of distractions
in psychological wellbeing during a skilled activity [29].
The participant was not aware that such events would take
place, nor he/she was prepared for them. The total duration
of the test was approximately 30 minutes (see Figure 2).
5. RESULTS
The PANAS scores are divided in Positive Affects (PA)
and Negative Affects (NA). According to the PANAS doc-
umentation, the mean PA scores for momentary (immedi-
ate) evaluation are 29.7 (SD = 7.9). Scores can range from
10 to 50, with higher scores representing higher levels of
positive affect. For Negative Affects the mean NA score
for an equally momentary evaluation are 14.8 (SD = 5.4).
Scores can range from 10 to 50, with lower scores repre-
senting lower levels of negative affects.
During our tests, we obtained a PA score mean (Before
the activity) = 30.57 (SD = 3.89) and a PA score mean
(After the activity) = 34.21 (SD = 5.14). In addition, we
collected a NA Score (Before the activity) = 15.57 (SD =
6) and a NA Score (After the activity) = 12.30 (SD = 3.30).
This means an overall improvement of 3.64 PA points and
3.27 NA points. By adding PA and NA scores, we found
that the overall improvement in the reported psychological
wellbeing was of 6,91 points, which in a range of 10 to
50 in the PANAS range represents an overall improvement
of 17.27% after 3 minutes of activity with our system. In
addition, 30% of the participants reported an improvement
of more than 10 points in the PA affect score
In our paired before/after test, for Negative Affects the
two-tailed p value equals 0.0029 (t = 3.5979), a statistically
significant difference (significance level >99%). Regard-
ing the Positive Affects, we obtained a p value of 0.0699
(t = 1.9750), which is also statistically significant (signifi-
cance level >95%).
Regarding usability, the System Usability Scale research
Proceedings of the 14th Sound and Music Computing Conference, July 5-8, Espoo, Finland
SMC2017-191
drew the average of 68 points in the scale (from 0 to 100).
Sauro [30] found that when people rate a system or prod-
uct with a SUS score of 82, they are likely to recommend
a system or product to a friend or colleague (Net Promoter
Score). After evaluating our system, the participants gave
it a SUS mean value of 73.9 (SD = 11.33) which means
5.9 points above average. One third of the participants
gave our system a SUS score of 82 or higher, potentially
becoming a “promoter”.
Finally, our engagement graphs over time showed that
the system was able to identify and measure a distraction
event in 73.33% of the participants, impacting the overall
engagement by 0.2 points or more, in a scale of 0 (total
disengaged) to 1 (full engagement). Our engagement scale
is also divided into categories, where 0 to 0.3 means low
engagement, 0.3 to 0.6 medium engagement and 0.6 to 1
high engagement. Calculating every time a distraction had
an impact in the engagement, there was an overall average
of 0.41 sudden decrease (SD = 1.40). As the NOISA sys-
tem reacts once it detects a drop in the overall engagement,
the level of focus was effectively regained to a stable level
before the distraction event in a mean time of 10.07 sec-
onds (SD = 7.15). Two engagement over time graphs for
the participants 10 and 11 (see Figure 3 and 4) are included
to demonstrate an example of a case where our engage-
ment prediction system detected both distractions (90 and
180 second mark, respectively), managing to regain focus
of the participant through autonomous counteractions.
Figure 3. Engagement over time graph of the participant
10
Figure 4. Engagement over time graph of the participant
11
6. ANALYSIS AND DISCUSSION
The results presented above show that the design of the
response module provided beneficial results for the partic-
ipants. The response module could successfully maintain
and strengthen the level of engagement in a skilled activity
of musical improvisation with NOISA instruments. The
resulting experience of such interaction was also likely to
have contributed positively to the psychological wellbeing
of the participants.
Judging from the quantitative data obtained through the
PANAS questionnaire, the average levels of Positive Af-
fects were higher after finishing the test, and the Nega-
tive Effects were lower after completing the task. In case
of Negative Affects, the difference was found to be very
statistically significant. In the PANAS scale, the Negative
Affects scores decreased from above the mean (15.57) to
below it (12.30). Even though the impact on the Positive
Affects was found to be not quite statistically significant,
we consider the overall improvement of 17.27% positive
considering the short amount of time spent with the system
during our task. The creative activity facilitated by NOISA
system proved to be statistically significant to impact on
the Negative Affects described in PANAS (Distressed, Up-
set, Guilty, Hostile, Irritable, Ashamed, Nervous, Jittery
and Afraid), which shows that the musical task showed
some capabilities during the test that can be successfully
applied to help reducing the subjective perception of worry,
stress and other negative personality traits of the partici-
pants.
The engagement estimation results indicated effective-
ness when detecting and maintaining the focus level of the
participants. In that sense, being able to measure at least
one of the distractions in 73.33% of the participants is sat-
isfactory, considering that while being observed, the par-
ticipant could feel compelled to keep his/her attention to
the task at hand. This situation would avoid us to detect
any distractions in their physical body movements. The
response module was capable of recovering attention and
focus from the participants in an average time of 10.07 sec-
onds after the distractions. We can note here that our cur-
rent contribution to NOISA system provided an engaging
interaction that was gradually and progressively built up by
the participant’s active and continuous involvement in the
musical activity with NOISA instruments.
Similarly, we observed that both our new hardware de-
sign and response module were evaluated by the partici-
pants as easy to use, obtaining consistent above-average
scores in the SUS scale. In addition, a large portion (one
third) of the participants cataloged it above the 82 mark,
which is particularly positive considering that we asked
non-specialist individuals to evaluate a new musical inter-
face. Our sample consisting of 15 participants might be
considered small; however, Tullis and Stetson [31] have
already demonstrated the reliability of SUS in smaller sam-
ples (8-12 participants).
7. CONCLUSIONS
Based on previous literature, it is clear that designing for
wellbeing is strongly linked with the psychological under-
standing of wellbeing, positive experience and physical ac-
tivity [3]. The purpose of our project was to establish a
situated musical activity for the user to be engaged in, at-
tempting to achieve the goal of enhancing psychological
Proceedings of the 14th Sound and Music Computing Conference, July 5-8, Espoo, Finland
SMC2017-192
wellbeing. Our design was grounde in a concrete con-
text (creative musical overall process) and guided by the
functionality (hand-held interface) as well as through sub-
tle interaction (counter-responsive musical actions). We
observed and measured the behaviour of our system as
it deals with losses of performer focus provoked by the
controlled introduction of external distractors. During the
tests, we observed indications that being engaged in our
musical activity contributed positively to participants psy-
chological wellbeing. Encouraged by our initial results, we
plan to continue our research by including in a future study
a comparison with a control group, which will enable us to
draw in a longer term more comprehensive conclusions of
the impact of the activity with NOISA in the pyschological
wellbeing of the user.
We also aim to investigate the application of a similar
engagement-monitoring technique in a broader scope of
skilled, potentially mentally absorbing actions with peo-
ple working in different occupations. A foreseen psycho-
logical wellbeing application scenario that will be imple-
mented in the future phases of the project, could be the
non-intrusive recognition of changes in patterns of engage-
ment that a person presents when carrying out different
creative tasks with digital environments, which could sig-
nal changes in their mood, psychological health or deteri-
oration of their cognitive capacity (early diagnostic goal).
This application requires a new hand-held interface to be
designed and implemented which will be fully integrated
with the engaging monitoring and the new response mod-
ule in NOISA system. Through subtle external actions, the
new interface and the digital environment could assist the
person to regain focus and engagement with the creative
task in hand, which might be beneficial for the success-
ful completion of the task (assistive living goal), and to
do so with an enhanced sense of control, accomplishment
and satisfaction (psychological wellbeing goal) in a cre-
ative process.
Acknowledgments
This project was developed thanks to the support of the
Nokia Research Centre in Finland.
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