Long-term activity recognition from wristwatch accelerometer data

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2014
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Abstract
With the development of wearable devices that have several embedded sensors, it is possible to collect data that can be analyzed in order to understand the user's needs and provide personalized services. Examples of these types of devices are smartphones, fitness-bracelets, smartwatches, just to men …
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Authors Garcia-Ceja E;Brena RF;Carrasco-Jimenez JC;Garrido L;;
Journal sensors
Year 2014
DOI
DOI not found
URL
https://www.pubmed.gov/?cmd=Search&term=Jose%20C.%20Carrasco-Jimenez
Keywords
artificial intelligence Monitoring National Center for Biotechnology Information NCBI NLM MEDLINE humans pubmed abstract nih national institutes of health national library of medicine models statistical reproducibility of results research support non-u.s. gov't algorithms enrique garcia-ceja sensitivity and specificity time factors pmid:25436652 pmc4299024 doi:10.3390/s141222500 ramon f brena leonardo garrido accelerometry / methods* actigraphy / methods* computer simulation data interpretation longitudinal studies markov chains ambulatory / methods* motor activity / physiology* pattern recognition automated / methods*

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