메뉴 건너뛰기




Volumn 14, Issue 5, 2012, Pages

Classification accuracies of physical activities using smartphone motion sensors

Author keywords

Accelerometer; Activity classification; Gyroscope; Machine learning; Smartphone

Indexed keywords

ADULT; ARTICLE; FEMALE; FOURIER ANALYSIS; HUMAN; MALE; MICROCOMPUTER; MIDDLE AGED; MOBILE PHONE; MOVEMENT (PHYSIOLOGY);

EID: 84872463842     PISSN: None     EISSN: 14388871     Source Type: Journal    
DOI: 10.2196/jmir.2208     Document Type: Article
Times cited : (269)

References (20)
  • 1
    • 3242765427 scopus 로고    scopus 로고
    • Updating the evidence that physical activity is good for health: An epidemiological review 2000-2003
    • Apr, [Medline: 15214597]
    • Bauman A. Updating the evidence that physical activity is good for health: an epidemiological review 2000-2003. J Sci Med Sport 2004 Apr;7(1 Suppl):6-19. [Medline: 15214597].
    • (2004) J Sci Med Sport , vol.7 , Issue.1 SUPPL. , pp. 6-19
    • Bauman, A.1
  • 2
    • 41349118958 scopus 로고    scopus 로고
    • Amount of time spent in sedentary behaviors in the United States, 2003-2004
    • Apr 1, [FREE Full text] [doi: 10.1093/aje/kwm390] [Medline: 18303006]
    • Matthews C, Chen K, Freedson P, Buchowski M, Beech B, Pate R, et al. Amount of time spent in sedentary behaviors in the United States, 2003-2004. Am J Epidemiol 2008 Apr 1;167(7):875-881 [FREE Full text] [doi: 10.1093/aje/kwm390] [Medline: 18303006].
    • (2008) Am J Epidemiol , vol.167 , Issue.7 , pp. 875-881
    • Matthews, C.1    Chen, K.2    Freedson, P.3    Buchowski, M.4    Beech, B.5    Pate, R.6
  • 3
    • 38049032926 scopus 로고    scopus 로고
    • Physical activity in the United States measured by accelerometer
    • Jan, [doi: 10.1249/mss.0b013e31815a51b3] [Medline: 18091006]
    • Troiano R, Berrigan D, Dodd K, Mâsse L, Tilert T, McDowell M. Physical activity in the United States measured by accelerometer. Med Sci Sports Exerc 2008 Jan;40(1):181-188. [doi: 10.1249/mss.0b013e31815a51b3] [Medline: 18091006].
    • (2008) Med Sci Sports Exerc , vol.40 , Issue.1 , pp. 181-188
    • Troiano, R.1    Berrigan, D.2    Dodd, K.3    Mâsse, L.4    Tilert, T.5    McDowell, M.6
  • 4
    • 35048842427 scopus 로고    scopus 로고
    • Activity recognition from user-annotated acceleration data
    • doi: 10.1007/978-3-540-24646-6-1
    • Bao L, Intille S. Activity recognition from user-annotated acceleration data. Lect Notes Comput Sci 2004;3001:1-17. [doi: 10.1007/978-3-540-24646-6-1].
    • (2004) Lect Notes Comput Sci , vol.3001 , pp. 1-17
    • Bao, L.1    Intille, S.2
  • 5
    • 84880762436 scopus 로고    scopus 로고
    • A hybrid discriminative/generative approach for modeling human activities
    • Proceedings. Presented at, Jul 30-Aug 5, 2005; Edinburgh, UK URL, [WebCite Cache]
    • Lester J, Choudhury T, Kern N, Borriello G, Hannaford B. A hybrid discriminative/generative approach for modeling human activities. In: Proceedings. 2005 Presented at: International Joint Conference on Artificial Intelligence (IJCAI); Jul 30-Aug 5, 2005; Edinburgh, UK URL: http://ijcai.org/Past%20Proceedings/IJCAI-05/PDF/0888.pdf [WebCite Cache].
    • (2005) International Joint Conference on Artificial Intelligence (IJCAI)
    • Lester, J.1    Choudhury, T.2    Kern, N.3    Borriello, G.4    Hannaford, B.5
  • 6
    • 78650027970 scopus 로고    scopus 로고
    • Using wearable activity type detection to improve physical activity energy expenditure estimation
    • Proceedings. 2010 Presented at, Sep 26-29, Copenhagen, Denmark
    • Albinali F, Intille S, Haskell W, Rosenberger M. Using wearable activity type detection to improve physical activity energy expenditure estimation. In: Proceedings. 2010 Presented at: 12th ACM international conference on Ubiquitous computing (UbiComp '10); Sep 26-29, 2010; Copenhagen, Denmark p. 311-320.
    • (2010) 12th ACM International Conference on Ubiquitous Computing (UbiComp '10) , pp. 311-320
    • Albinali, F.1    Intille, S.2    Haskell, W.3    Rosenberger, M.4
  • 7
    • 78650900690 scopus 로고    scopus 로고
    • Evaluation of neural networks to identify types of activity using accelerometers
    • Jan, [doi: 10.1249/MSS.0b013e3181e5797d] [Medline: 20473226]
    • De Vries S, Garre F, Engbers L, Hildebrandt V, Van Buuren S. Evaluation of neural networks to identify types of activity using accelerometers. Med Sci Sports Exerc 2011 Jan;43(1):101-107. [doi: 10.1249/MSS.0b013e3181e5797d] [Medline: 20473226].
    • (2011) Med Sci Sports Exerc , vol.43 , Issue.1 , pp. 101-107
    • De Vries, S.1    Garre, F.2    Engbers, L.3    Hildebrandt, V.4    Van Buuren, S.5
  • 8
    • 67650383820 scopus 로고    scopus 로고
    • Estimating activity-related energy expenditure under sedentary conditions using a tri-axial seismic accelerometer
    • (Silver Spring), Jun, [FREE Full text] [doi: 10.1038/oby.2009.55] [Medline: 19282829]
    • van Hees V, van Lummel R, Westerterp K. Estimating activity-related energy expenditure under sedentary conditions using a tri-axial seismic accelerometer. Obesity (Silver Spring) 2009 Jun;17(6):1287-1292 [FREE Full text] [doi: 10.1038/oby.2009.55] [Medline: 19282829].
    • (2009) Obesity , vol.17 , Issue.6 , pp. 1287-1292
    • Van Hees, V.1    Van Lummel, R.2    Westerterp, K.3
  • 9
    • 65349117069 scopus 로고    scopus 로고
    • A comparison of feature extraction methods for the classification of dynamic activities from accelerometer data
    • Mar, [doi: 10.1109/TBME.2008.2006190] [Medline: 19272902]
    • Preece S, Goulermas J, Kenney L, Howard D. A comparison of feature extraction methods for the classification of dynamic activities from accelerometer data. IEEE Trans Biomed Eng 2009 Mar;56(3):871-879. [doi: 10.1109/TBME.2008.2006190] [Medline: 19272902].
    • (2009) IEEE Trans Biomed Eng , vol.56 , Issue.3 , pp. 871-879
    • Preece, S.1    Goulermas, J.2    Kenney, L.3    Howard, D.4
  • 12
    • 80054964826 scopus 로고    scopus 로고
    • Activity recognition using cell phone accelerometers
    • [FREE Full text] [WebCite Cache]
    • Kwapisz J, Weiss G, Moore S. Activity recognition using cell phone accelerometers. SIGKDD Explor 2010;12(2):74-82 [FREE Full text] [WebCite Cache].
    • (2010) SIGKDD Explor , vol.12 , Issue.2 , pp. 74-82
    • Kwapisz, J.1    Weiss, G.2    Moore, S.3
  • 13
    • 0028814439 scopus 로고
    • Physical activity and public health. A recommendation from the centers for disease control and prevention and the American college of sports medicine
    • Feb 1, [Medline: 7823386]
    • Pate R, Pratt M, Blair S, Haskell W, Macera C, Bouchard C, et al. Physical activity and public health. A recommendation from the Centers for Disease Control and Prevention and the American College of Sports Medicine. JAMA 1995 Feb 1;273(5):402-407. [Medline: 7823386].
    • (1995) JAMA , vol.273 , Issue.5 , pp. 402-407
    • Pate, R.1    Pratt, M.2    Blair, S.3    Haskell, W.4    MacEra, C.5    Bouchard, C.6
  • 14
    • 84857531989 scopus 로고    scopus 로고
    • URL, [accessed 2012-09-12] [WebCite Cache ID 6AdEecOGW]
    • Dixon-Warren S. MEMS J. 2010. Motion sensing in the iPhone 4: MEMS accelerometer URL: http://www.memsjournal.com/2010/12/motion-sensing-in-the- iphone-4-mems-accelerometer.html [accessed 2012-09-12] [WebCite Cache ID 6AdEecOGW].
    • (2010) Motion Sensing in the IPhone 4: MEMS Accelerometer
    • Dixon-Warren, S.1    Mems, J.2
  • 16
    • 0242592241 scopus 로고    scopus 로고
    • Multi-sensor activity context detection for wearable computing
    • doi: 10.1007/978-3-540-39863-9-17
    • Kern N, Schiele B, Schmidt A. Multi-sensor activity context detection for wearable computing. Lect Notes Comput Sci 2003;2875:220-232. [doi: 10.1007/978-3-540-39863-9-17].
    • (2003) Lect Notes Comput Sci , vol.2875 , pp. 220-232
    • Kern, N.1    Schiele, B.2    Schmidt, A.3
  • 18
    • 41149177155 scopus 로고    scopus 로고
    • Real-time recognition of physical activities and their intensities using wireless accelerometers and a heart rate monitor
    • 2007 Presented at, Sep 28-Oct 1, Boston, MA. USA
    • Tapia E, Intille S, Haskell W, Larson K, Wright J, King A, et al. Real-time recognition of physical activities and their intensities using wireless accelerometers and a heart rate monitor. 2007 Presented at: 11th IEEE International Symposium on Wearable Computers; Sep 28-Oct 1, 2007; Boston, MA. USA.
    • (2007) 11th IEEE International Symposium on Wearable Computers
    • Tapia, E.1    Intille, S.2    Haskell, W.3    Larson, K.4    Wright, J.5    King, A.6
  • 20
    • 84872462359 scopus 로고    scopus 로고
    • San Diego, May 06. URL, [accessed 2012-05-05] [WebCite Cache ID 67S5XRWOx]
    • University of California, San Diego. 2012 May 06. iDash: Integrating Data for Analysis, Anonymization, and Sharing URL: http://idash.ucsd.edu/[accessed 2012-05-05] [WebCite Cache ID 67S5XRWOx].
    • (2012) IDash: Integrating Data for Analysis, Anonymization, and Sharing


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.