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Citing this Article

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Published on 05.10.12 in Vol 14, No 5 (2012): Sep-Oct

This paper is in the following e-collection/theme issue:

Works citing "Classification Accuracies of Physical Activities Using Smartphone Motion Sensors"

According to Crossref, the following articles are citing this article (DOI 10.2196/jmir.2208):

(note that this is only a small subset of citations)

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  38. Zhou X, Yu W, Sullivan WC. Making pervasive sensing possible: Effective travel mode sensing based on smartphones. Computers, Environment and Urban Systems 2016;58:52
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  42. San-Segundo R, Montero JM, Barra-Chicote R, Fernández F, Pardo JM. Feature extraction from smartphone inertial signals for human activity segmentation. Signal Processing 2016;120:359
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  43. Wang Q, Egelandsdal B, Amdam GV, Almli VL, Oostindjer M. Diet and Physical Activity Apps: Perceived Effectiveness by App Users. JMIR mHealth and uHealth 2016;4(2):e33
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  44. Liu C, Chan C. Exercise Performance Measurement with Smartphone Embedded Sensor for Well-Being Management. International Journal of Environmental Research and Public Health 2016;13(10):1001
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  45. Goyal S, Morita P, Lewis GF, Yu C, Seto E, Cafazzo JA. The Systematic Design of a Behavioural Mobile Health Application for the Self-Management of Type 2 Diabetes. Canadian Journal of Diabetes 2016;40(1):95
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  46. Chen J, Tan H, Pan Z. Experimental validation of smartphones for measuring human-induced loads. Smart Structures and Systems 2016;18(3):625
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  47. Ronao CA, Cho S. Human activity recognition with smartphone sensors using deep learning neural networks. Expert Systems with Applications 2016;59:235
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  49. Park S, Kim M, Bae H, Cha Y. The Reliability and Validity of Hip Range of Motion Measurement using a Smart phone Operative Patient. Journal of the Korean Society of Physical Medicine 2015;10(2):1
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  50. Payne HE, Lister C, West JH, Bernhardt JM. Behavioral Functionality of Mobile Apps in Health Interventions: A Systematic Review of the Literature. JMIR mHealth and uHealth 2015;3(1):e20
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  51. Liu C, Chan C. An Accumulated Activity Effective Index for Promoting Physical Activity: A Design and Development Study in a Mobile and Pervasive Health Context. JMIR Research Protocols 2015;4(1):e5
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  52. Mimura K, Kishino H, Karino G, Nitta E, Senoo A, Ikegami K, Kunikata T, Yamanouchi H, Nakamura S, Sato K, Koshiba M. Potential of a smartphone as a stress-free sensor of daily human behaviour. Behavioural Brain Research 2015;276:181
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  53. Pernek I, Kurillo G, Stiglic G, Bajcsy R. Recognizing the intensity of strength training exercises with wearable sensors. Journal of Biomedical Informatics 2015;58:145
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  55. Shoaib M, Bosch S, Incel O, Scholten H, Havinga P. Fusion of Smartphone Motion Sensors for Physical Activity Recognition. Sensors 2014;14(6):10146
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  56. Trowbridge MJ, Pickell SG, Pyke CR, Jutte DP. Building Healthy Communities: Establishing Health And Wellness Metrics For Use Within The Real Estate Industry. Health Affairs 2014;33(11):1923
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  57. Kim K, Lee M. Image Obfuscation in the User-Friendly Sensitive Area with the Use of a Sensor for Smart Devices and Image Processing Techniques. International Journal of Distributed Sensor Networks 2014;10(5):797353
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  58. Bort-Roig J, Gilson ND, Puig-Ribera A, Contreras RS, Trost SG. Measuring and Influencing Physical Activity with Smartphone Technology: A Systematic Review. Sports Medicine 2014;44(5):671
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  59. Stöggl T, Holst A, Jonasson A, Andersson E, Wunsch T, Norström C, Holmberg H. Automatic Classification of the Sub-Techniques (Gears) Used in Cross-Country Ski Skating Employing a Mobile Phone. Sensors 2014;14(11):20589
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  60. Arif M, Bilal M, Kattan A, Ahamed SI. Better Physical Activity Classification using Smartphone Acceleration Sensor. Journal of Medical Systems 2014;38(9)
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  61. Hobert MA, Maetzler W, Aminian K, Chiari L. Technical and clinical view on ambulatory assessment in Parkinson's disease. Acta Neurologica Scandinavica 2014;130(3):139
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  62. Ebrahimi M, Aghagolzadeh P, Shamabadi N, Tahmasebi A, Alsharifi M, Adelson DL, Hemmatzadeh F, Ebrahimie E, Tompkins SM. Understanding the Underlying Mechanism of HA-Subtyping in the Level of Physic-Chemical Characteristics of Protein. PLoS ONE 2014;9(5):e96984
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  63. Smolders R, De Boever P. Perspectives for environment and health research in Horizon 2020: Dark ages or golden era?. International Journal of Hygiene and Environmental Health 2014;217(8):891
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  64. Lister C, West JH, Cannon B, Sax T, Brodegard D. Just a Fad? Gamification in Health and Fitness Apps. JMIR Serious Games 2014;2(2):e9
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  65. Graham D, Suzuki A, Reitz C, Saxena A, Kuo J, Tetsworth K. Measurement of rotational deformity: using a smartphone application is more accurate than conventional methods. ANZ Journal of Surgery 2013;83(12):937
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  66. Gietzelt M, Wolf K, Kohlmann M, Marschollek M, Haux R. Measurement of Accelerometry-based Gait Parameters in People with and without Dementia in the Field. Methods of Information in Medicine 2013;52(04):319
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  67. Donaire-Gonzalez D, de Nazelle A, Seto E, Mendez M, Nieuwenhuijsen MJ, Jerrett M. Comparison of Physical Activity Measures Using Mobile Phone-Based CalFit and Actigraph. Journal of Medical Internet Research 2013;15(6):e111
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  68. Fanning J, Mullen SP, McAuley E. Increasing Physical Activity With Mobile Devices: A Meta-Analysis. Journal of Medical Internet Research 2012;14(6):e161
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According to Crossref, the following books are citing this article (DOI 10.2196/jmir.2208)

:
  1. Sadouk L, Gadi T. Lecture Notes in Real-Time Intelligent Systems. 2019. Chapter 43:485
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  2. Shoaib M, Incel OD, Scholten H, Havinga P. Mobile Computing, Applications, and Services. 2018. Chapter 7:106
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  3. Jiang X, Lu Y, Lu Z, Zhou H. Web and Big Data. 2018. Chapter 10:101
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  4. Cheng X, Fang L, Yang L, Cui S. Mobile Big Data. 2018. Chapter 5:51
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  5. Rovniak LS, King AC. Walking. 2017. :249
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  6. Piwek L, Joinson A. Behavior Change Research and Theory. 2017. :137
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  7. Oneto L, Ortiz JL, Anguita D. Adaptive Mobile Computing. 2017. :127
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  8. Singh D, Merdivan E, Psychoula I, Kropf J, Hanke S, Geist M, Holzinger A. Machine Learning and Knowledge Extraction. 2017. Chapter 18:267
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  9. Lehsan K, Bootkrajang J. Intelligent Data Engineering and Automated Learning – IDEAL 2017. 2017. Chapter 5:36
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  10. Yu Z, Huang L, Guo H, Xu H. Knowledge Science, Engineering and Management. 2016. Chapter 36:453
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  11. Zhao Z, Sun Z, Huang L, Guo H, Wang J, Xu H. Wireless Algorithms, Systems, and Applications. 2016. Chapter 17:186
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  12. Liu B, Koc AB. Encyclopedia of Mobile Phone Behavior. 2015. chapter 35:410
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