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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