long-acting types), the patient's body composition,
physical activity, why automatic data collection via a
"bio-bracelet", which such as Smart Band, and
practical visualization of these complex tasks, and
their interactions, both can be helpful for patients and
their advisers or assistants in clinical settings, and
provide information to be analysed at the graduate
level, can provide new information that can be
converted into new clinical counselling. Analyses of
data for glucose levels and insulin doses with details
of HbA1c levels, over time, longitudinally, can
provide both new insights into the relationship
between glucose variability (i.e., frequency and
amplitude of the high and low values) and the level of
HbA1c (and over time relation to the development of
diabetic complications), and in the patterns of glucose
levels, frequency of episodes of hypoglycaemia,
relationships actually taken insulin doses, etc. are not
available today, and not for larger groups of real
patients outside of clinical trials, and put them in the
with bias (s) involved. The complex situation of
diabetes care is a major global challenge (Guariguata
et al., 2014) and is a good example of the area where
the development and utilization of techniques to
facilitate better target fulfilment can spread easily
benefit both individuals and society (Sundström,
2016), (Hu et al., 2015), (Lundberg, et al., 2015),
(Eriksén, 2015).
6 FUTURE WORK
Collaboration between different expert domains are
of interest to battle the challenges related to diabetes.
Closer collaboration between stakeholders, with care
institutions and related partners for a healthy lifestyle
among children are desired.
ACKNOWLEDGEMENTS
To the system-cross organisation at Linnaeus
University giving us this unique opportunity to
initiate a small scale R&D cooperation. Furthermore
to the paediatric clinics, endocrinologists in Växjö
and Kalmar hospitals for support.
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