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http://yadda.icm.edu.pl:80/baztech/element/bwmeta1.element.baztech-4146e6fe-53b2-4ca0-b7d6-4cae2a47e23c

Czasopismo

Biocybernetics and Biomedical Engineering

Tytuł artykułu

Physical activity recognition by smartphones, a survey

Autorzy Morales, J.  Akopian, D. 
Treść / Zawartość http://www.ibib.waw.pl/pl/wydawnictwa/biocybernetics-and-biomedical-enginering-bbe/bbe-tomy http://www.journals.elsevier.com/biocybernetics-and-biomedical-engineering/
Warianty tytułu
Języki publikacji EN
Abstrakty
EN Human activity recognition (HAR) from wearable motion sensor data is a promising research field due to its applications in healthcare, athletics, lifestyle monitoring, and computer–human interaction. Smartphones are an obvious platform for the deployment of HAR algorithms. This paper provides an overview of the state-of-the-art when it comes to the following aspects: relevant signals, data capture and preprocessing, ways to deal with unknown on-body locations and orientations, selecting the right features, activity models and classifiers, metrics for quantifying activity execution, and ways to evaluate usability of a HAR system. The survey covers detection of repetitive activities, postures, falls, and inactivity.
Słowa kluczowe
PL akcelerometr   żyroskop   rozpoznawanie aktywności   smartfon  
EN accelerometer   gyroscope   activity recognition   smartphone  
Wydawca Nałęcz Institute of Biocybernetics and Biomedical Engineering of the Polish Academy of Sciences
Elsevier
Czasopismo Biocybernetics and Biomedical Engineering
Rocznik 2017
Tom Vol. 37, no. 3
Strony 388--400
Opis fizyczny Bibliogr. 65 poz., rys., tab., wykr.
Twórcy
autor Morales, J.
  • University of Texas at San Antonio, BSE 1.500, One UTSA Circle, San Antonio, TX 78249, United States, nnf001@my.utsa.edu
autor Akopian, D.
  • University of Texas at San Antonio, BSE 1.500, One UTSA Circle, San Antonio, TX 78249, United States, david.akopian@utsa.edu
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Uwagi
PL Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017).
Kolekcja BazTech
Identyfikator YADDA bwmeta1.element.baztech-4146e6fe-53b2-4ca0-b7d6-4cae2a47e23c
Identyfikatory
DOI 10.1016/j.bbe.2017.04.004