Ambient Intelligence for Health: First International by José Bravo, Ramón Hervás, Vladimir Villarreal

By José Bravo, Ramón Hervás, Vladimir Villarreal

This publication constitutes the refereed convention court cases of the 1st overseas convention on Ambient Intelligence for future health, 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 themes on applied sciences for imposing AmIHealth environments; frameworks similar with AmIHealth environments; utilized algorithms in e-Health platforms; interactions in the AmIHealth environments; purposes and case reports of AmIHealth environments; and metrics for healthiness environments.

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Extra resources for Ambient Intelligence for Health: First International Conference, AmIHEALTH 2015, Puerto Varas, Chile, December 1-4, 2015, Proceedings

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J. Geriatr. Psychiatry 22(12), 1592–1602 (2014) Extracting Information from Electronic Medical Records to Identify Obesity Status of a Patient Based on Comorbidities and Bodyweight Measures Rosa L. Figueroa and Christopher A. cl Abstract. Obesity is a chronic disease with an increasing impact on the world’s population. In this work, we present a method to identify obesity using text mining techniques and information related to body weight measures and obesity comorbidities. We used a dataset of 2412 de-identified medical records that contains labels for two classification problems.

Cl Abstract. Respiratory diseases are a group of chronic diseases affecting the airways and other structures of the lungs, which cause thousands of breathing problems in Chile. Respiratory Therapy services comprise a variety of interventions that are related to airway management and maintenance of lung health. In Chile, RTs are predominantly carried out in hospitals, especially in high-intensity areas such as intensive care units. However, RTs also work in outpatient settings, for instance, patients can receive treatment at home in pulmonary rehabilitation programs.

A Fall Risk Index based on multiple gait parameter pattern to assess and quantify the risk of fall of elderly population. It is based on single support, double support, acceleration amplitude ML, heel strike force slope. • From a components and related architecture point of view, the system consists of: • A pair of electronic electrically isolated insoles. 0 (or above) device. • A smartphone that stores data locally and sends it to the main server for its management according the desired policy.

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