Using Wearables in the Context of Chronic Disorders
Results of a Pre-Study
Marc Schickler, R¨
udiger Pryss, Manfred Reichert,
Martin Heinzelmann, Johannes Schobel
Ulm University
Institute of Databases and Information Systems
{marc.schickler,ruediger.pryss,manfred.reichert}@uni-ulm.de,
{martin.heinzelmann,johannes.schobel}@uni-ulm.de
Berthold Langguth, Thomas Probst, Winfried Schlee
University of Regensburg
Clinic and Policlinic for Psychiatry and Psychotherapy
thomas.probst@psychologie.uni-regensburg.de,
Abstract—Smart mobile devices are variously used in the
health sector. Some mobile applications empower patients to
better understand their health problems, others guide them
in health behavior. Moreover, smart mobile devices can be
used in clinical research. Mobile crowd sensing has proven
high usefulness for collecting health data with high ecological
validity in this context. As the core idea, individually recorded
health data are evaluated and fed back to individuals to
better control their symptoms. For this purpose, the Track-
YourTinnitus mobile crowd sensing platform was developed to
empower patients to cope better with their tinnitus. So far,
the platform has solely gathered patient data based on mobile
questionnaires. When filling in a questionnaire, however, the
analysis of the heartrate might provide novel information to
medical experts. As monitoring the heartrate with smart mobile
devices is costly, the trend towards wearables offers promising
perspectives. Using smartwatches instead of smartphones in
TrackYourTinnitus, however, requires questionnaire manage-
ment on smartwatches. This work presents results of a pre-
study related to the feasibility of sophisticated questionnaires
on smartwatches. A prototype was developed and evaluated
with 24 subjects. The obtained results are promising regarding
the use of smartwatches for mobile crowd sensing in the context
of chronic disorders.
Keywords-Mobile Data Collection, Smartwatch, Patient Em-
powerment, Mobile Crowd Sensing, Personalized Healthcare
I. INTRODUCTION
The tinnitus disorder (ringing in the ear) is characterized
by the perception of a sound in the absence of a correspond-
ing acoustic stimulus. It is a highly prevalent disorder being
difficult to treat. Recently, mobile crowd sensing emerged as
an approach for collecting large and ecological valid datasets
at rather low costs. By providing mobile crowd sensing
services to huge numbers of patients, large datasets can be
gathered cheaply on a daily basis. In the TrackYourTinnitus
(TYT) project [1], a mobile crowd sensing platform was
developed to reveal new medical aspects on tinnitus and
its treatment. Currently, the platform solely gathers patient
data based on mobile questionnaires processed by patients
on their smart mobile device. When filling a questionnaire
for medical experts, the analysis of the heartrate might be
another promising data source. In this context, the use of
Subjects Smartwatch Smartphone
V1 V2 V3 V4 V5
Avg. completion 203,13 243,27 208,22 223,74 198,63
time (sec.)
Table I
QUESTIONNAIRE VERSIONS AND COMPLETION TIMES
Figure 1. Evaluation of List/Cards and LogScale/ButtonScale
smartwatches and their integrated sensors for measuring the
heartrate seems to be a feasible approach. From a technical
perspective, two issues are crucial regarding their use in
the TYT project. First, mobile questionnaires need to be
deployed to smartwatches. Second, it must be evaluated
whether smartwatches are able to robustly measure the
heartrate while filling in a questionnaire. This work deals
with the first issue and presents results from a pre-study
that revealed promising results in this context.
Section II introduces the setting of the pre-study, whereas
Section III presents results. Section IV discusses related
work and Section V concludes the paper.
II. PRE-STUDY SETTING
The technical equipment used for the pre-study were
a Motorola Moto 360 smartwatch and a LG Nexus 5X
smart mobile device. The technical prototype we realized
addressed the following elements of a digital questionnaire:
navigation (i.e., how to navigate between questions), input
elements (e.g., lists), text appearance (i.e., addressing screen
Figure 2. Questionnaires on Smartwatch and Smartphone
size limitations), and text input (i.e., how to provide text
input). Based on this, a questionnaire consisting of 18
questions addressing fundamental questions related to TYT
was developed in 4 different smartwatch versions (cf. Fig.
2, V1-V4). The latter were required to evaluate the different
input elements. Furthermore, version 5 of the questionnaire
was provided on the smartphone itself. The latter allows
comparing the results obtained for the smartwatch and smart
mobile device respectively. Note that text input can be
provided based on voice input. Further, two additional input
elements were realized (cf. Fig. 2, ButtonScale, LockScale).
III. PRE-STUDY RESULTS
24 subjects processed four questionnaires on the smart-
watch and one on the smartphone. Three selected results
are presented. First, the duration to process questionnaires
depends on the input method (e.g., scales) and the number of
possible answers. Specifically, the scales show an advantage
for questions with a large number of answer categories,
while the cards and lists show an advantage for questions
with a small number of answer categories (cf. Fig. 1).
Second, ButtonScale requires less time than LogScale. More
precisely, 79% of the subjects prefer the ButtonScale over
LockScale. Cards, in turn, require less time than lists.
Furthermore, 54% of the subjects preferred cards, while
42% preferred the list. (cf. Fig. 1). Third, the observed
times to process a questionnaire on the smartwatch and the
smartphone were surprising. The average duration to finish
the questionnaire with the smartwatch was 215.4 seconds,
while the average duration with the smartphone was 198.6
seconds. This, together with observations made for other
recordings, indicate that smartwatches constitute a proper
alternative for smartphones in the context of smart mobile
data collection. Further studies are required to appropriately
evaluate the use of smartwatches in the long run.
IV. RELATED WORK
The assessment of vital parameters in various life situa-
tions has been considered by other approaches as well [2].
Smartwatches have been already proposed as an assessment
tool for movement disorders [3]. To the knowledge of the
authors, their use in combination with mobile crowd sensing
on chronic disorders is still a largely untapped field.
V. SUMMARY AND OUTLOOK
The pre-study revealed that smartwatches may be used as
alternatives in the context of mobile crowd sensing platforms
making use of mobile questionnaires. A specific advantage
are their integrated sensors, which may provide additional
insights about the health state. Further research for their
validation and for the evaluation of their long-term use are
required. Altogether, smartwatches seem to be a valuable
device type for mobile crowd sensing on chronic disorders.
REFERENCES
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Computer Society Press, 2015, pp. 352–359.
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