Get Ambient Intelligence for Health: First International PDF

By José Bravo, Ramón Hervás, Vladimir Villarreal

ISBN-10: 3319265075

ISBN-13: 9783319265070

ISBN-10: 3319265083

ISBN-13: 9783319265087

This booklet constitutes the refereed convention complaints of the 1st overseas convention on Ambient Intelligence for wellbeing and fitness, 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 enforcing AmIHealth environments; frameworks comparable with AmIHealth environments; utilized algorithms in e-Health platforms; interactions in the AmIHealth environments; functions and case experiences 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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WHO, Geneva (2007) 2. Wiisel site. eu/ 3. com/content/ 4. nl/products 5. uk/products/info/fall-detector-wrist-worn/ 6. : Spatio-temporal parameters of gait measured by an ambulatory system using miniature gyroscopes. J. Biomech. 35, 689–699 (2002) 7. : Recognition of gait disturbances in patients with normal pressure hydrocephalus using a computer dynography system. J. Physiol. Pharmacol. 59(Suppl 6), 201–207 (2008) 8. : A wireless sensor insole for collecting gait data. Stud. Health Technol. Inform.

Our web application is targeted towards medical teams and experts for continuous monitoring. This component focuses on displaying three key pieces of information: the most recent oxygen saturation value (the percentage of oxygen-saturated hemoglobin relative to total hemoglobin in the blood), the most recent heart rate (measured in beats per minute), and the patient’s connection to the sensor (connected or disconnected). The web application is built using common web technologies (Javascript, HTML, and CSS) and is presented as a single page application.

L. A. Flores category. The classes for this problem were: super obesity (S), morbid obesity (M), severe obesity (SO), and moderate obesity (MO). To generate a gold standard for classification, we asked two students with biomedical background to revise and annotated a total of 2462 records using an annotation tool designed in QT-designer1 and programmed in Python. This tool allows the annotator to assign a specific label to a record and suggest possible features for classification. For each record, they first assigned a label within the first classification problem.

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Ambient Intelligence for Health: First International Conference, AmIHEALTH 2015, Puerto Varas, Chile, December 1-4, 2015, Proceedings by José Bravo, Ramón Hervás, Vladimir Villarreal


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