By José Bravo, Ramón Hervás, Vladimir Villarreal
This booklet constitutes the refereed convention lawsuits of the 1st foreign convention on Ambient Intelligence for healthiness, AmIHEALTH 2015, held in Puerto Varas, Chile, in December 2015.
The 20 revised complete papers and nine brief papers have been reviewed and chosen from 32 submissions and canopy issues on applied sciences for imposing AmIHealth environments; frameworks similar with AmIHealth environments; utilized algorithms in e-Health structures; interactions in the AmIHealth environments; purposes and case stories of AmIHealth environments; and metrics for well-being environments.
Read Online or Download Ambient Intelligence for Health: First International Conference, AmIHEALTH 2015, Puerto Varas, Chile, December 1-4, 2015, Proceedings PDF
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Additional resources for Ambient Intelligence for Health: First International Conference, AmIHEALTH 2015, Puerto Varas, Chile, December 1-4, 2015, Proceedings
More speciﬁcally the validation studies addressed the following aims to: (1) assess the comfort and durability of the insole, (2) evaluate the functionality in collecting gait data, (3) measure the ability to recognize walking patterns, activity and sedentary periods and to identify risky behaviors, (4) assess the users’ feasibility to operate independently at home (donning, dofﬁng, charging, …) and (5) evaluate the usability according to the ability of users to understand the information provided.
4 Conclusions and Further Work This paper proposes a MCSW to support and improve homecare for respiratory diseases. One of the major strengths of the proposed platform is that its design is based around the patient and their support network, rather than a pure medical tool for diagnosis. We propose a MCSW as the best approach to implement this homecare system because workspaces are in tune with the collaborative nature of homecare. Mobile devices make the system ubiquitous, while cloud computing helps overcome the limitations of mobile devices, as well as providing new development opportunities.
In the case that Obesity label was assigned to a record, the reviewer was asked to annotate the record with a label of the second classiﬁcation problem. We also asked the evaluators to provide information about keywords related to obesity, body weight or obesity comorbidities that were not considered in the list of keywords but were present in the records. When all the documents were annotated, we ﬁltered out records that reviewers deemed as possible false positives. g. records mentioning “low molecular weight”).