There are some bicycle ergometer using chipcard
controlled training, but there is no remote tele-
monitoring yet available. Currently two research
approaches exist: The SAPHIRE-Project (Busch et
al., 2009) - the precursor of the OSAMI-D project -
and the ongoing project HeartCycle
(http://www.heartcycle.eu) that also integrate online
exercise supervision into their platforms. SAPHIRE
did not consider Level 2, Level 3 or mobile training
since the project solely focused on realizing Level 1
training without audio- and video-conferencing. By
performing the user study we have been able to
gather first knowledge about what kind of user
interaction is useful and which parts of the
SAPHIRE interfaces seemed to be usable, which are
improvable and how. For the supervisor side we
already created user interface mockups that are
going to be evaluated and implemented
(Klompmaker et al., 2009). Since supervisors are
often familiar with complex visualizations of
medical data it is expected that it is more difficult to
create usable user interfaces for patients using such a
system.
Gay and Leijdekkers presented an approach on
how sensors for measuring vital data may be used in
mobile setups (Gay and Leijdekkers, 2007). Thereby
the ECG data is analyzed automatically and locally
in order to provide hints to the user or to alert pre
assigned caregivers whenever necessary. Anyway
here the data is not transmitted during or after an
exercise session but monitored permanently by
algorithms. Another project focusing on mobile
applications especially for elderly people is
presented by Oppermann et al. (2008). Here the
application that’s also monitoring vital data may also
only be controlled with the mobile device itself
resulting in small and very simple graphical user
interfaces. We can benefit from these results when
designing the mobile training application but we had
to do a user study for the user interface on the
ergometer screen from scratch.
The concept of the company T2BEAM
Technologies AG, Switzerland just emerged on the
market in January 2009. The product called athlosoft
(http://athlosoft.com) addresses healthy subjects,
who can get online training supervision. This system
is to the knowledge of the authors the most advanced
IT-telemonitoring concept on the market yet but as a
downside compared to OSAMI-D it does not allow
the definition of medical constraints controlling a
training session.
In summary we found out that there are
approaches existing that address the different
technical challenges of the OSAMI-D project and
the different end users. However there’s no system
existing using the different technical approaches of
live supervision on an ergometer, offline training
with predefined medical constraints and mobile
training altogether for patients with cardiac diseases.
We think it is necessary to achieve more insights of
the user’s needs, preferences and habits in this
specific use case. Therefore user centered design is
the best possibility towards developing a successful
and usable system.
4 USER STUDY
In the user study we did in a rehabilitation clinic we
tried to find out what the current situation and the
daily routine of patients looks like in order to use the
results for the system design. We will introduce the
interview lead through and the results here.
4.1 Current Setting
This section explains the current flow of the
ergometer training for patients with cardiac diseases
within a rehabilitation clinic. We carefully figured
out what’s important for patients and supervisors
here and how the several training steps are executed
in order to develop the OSAMI-D system according
to these workflows.
The in situ training in the early rehabilitation
phase is organized in groups of up to 15 patients that
are all exercising simultaneously. Therefore they all
start a warm-up phase simultaneously, reach the
training phase simultaneously and reach and finish
the cool down phase of the training simultaneously.
The focus of the supervisor here lies on visual
control and personal conversations. She
predominantly checks the body language and body
signals of the patients, e.g. skin color, sweating or
pedal regularity, in order to detect critical situations.
Further on she asks the patients about their
wellbeing periodically. The vital data that is
displayed on two large PC displays in a secondary
room is not that important and only considered
secondarily. Beside the proven medical effectiveness
the biggest advantage of an in situ ergometer
training is therefore the personal supervision through
qualified medical staff. Further on many patients
like the training within an exercise group because it
enables social interactions with other patients.
However there are some disadvantages of an in situ
ergometer training. It is described as very
monotonous by the patients because it provides little
variety. Comparing this exercise with an outdoor
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