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Citing this Article

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Published on 15.07.13 in Vol 1, No 2 (2013): Jul-Dec

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

Works citing "Position and Orientation Tracking in a Ubiquitous Monitoring System for Parkinson Disease Patients With Freezing of Gait Symptom"

According to Crossref, the following articles are citing this article (DOI 10.2196/mhealth.2539):

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

  1. LEMOYNE R, MASTROIANNI T. IMPLEMENTATION OF A SMARTPHONE AS A WIRELESS ACCELEROMETER PLATFORM FOR QUANTIFYING HEMIPLEGIC GAIT DISPARITY IN A FUNCTIONALLY AUTONOMOUS CONTEXT. Journal of Mechanics in Medicine and Biology 2018;18(02):1850005
    CrossRef
  2. VanWye WR, Hoover DL. Management of a patient’s gait abnormality using smartphone technology in-clinic for improved qualitative analysis: A case report. Physiotherapy Theory and Practice 2018;34(5):403
    CrossRef
  3. Rodríguez-Martín D, Samà A, Pérez-López C, Català A, Moreno Arostegui JM, Cabestany J, Bayés , Alcaine S, Mestre B, Prats A, Crespo MC, Counihan TJ, Browne P, Quinlan LR, ÓLaighin G, Sweeney D, Lewy H, Azuri J, Vainstein G, Annicchiarico R, Costa A, Rodríguez-Molinero A, Gómez S. Home detection of freezing of gait using support vector machines through a single waist-worn triaxial accelerometer. PLOS ONE 2017;12(2):e0171764
    CrossRef
  4. Linares-del Rey M, Vela-Desojo L, Cano-de la Cuerda R. Aplicaciones móviles en la enfermedad de Parkinson: una revisión sistemática. Neurología 2017;
    CrossRef
  5. Suppa A, Kita A, Leodori G, Zampogna A, Nicolini E, Lorenzi P, Rao R, Irrera F. l-DOPA and Freezing of Gait in Parkinson’s Disease: Objective Assessment through a Wearable Wireless System. Frontiers in Neurology 2017;8
    CrossRef
  6. Lee CY, Kang SJ, Hong S, Ma H, Lee U, Kim YJ, Lebedev MA. A Validation Study of a Smartphone-Based Finger Tapping Application for Quantitative Assessment of Bradykinesia in Parkinson’s Disease. PLOS ONE 2016;11(7):e0158852
    CrossRef
  7. Del Rosario MB, Lovell NH, Redmond SJ. Quaternion-Based Complementary Filter for Attitude Determination of a Smartphone. IEEE Sensors Journal 2016;16(15):6008
    CrossRef
  8. O'Hara K, Morrison C, Sellen A, Bianchi-Berthouze N, Craig C. Body Tracking in Healthcare. Synthesis Lectures on Assistive, Rehabilitative, and Health-Preserving Technologies 2016;5(1):1
    CrossRef
  9. del Rosario M, Redmond S, Lovell N. Tracking the Evolution of Smartphone Sensing for Monitoring Human Movement. Sensors 2015;15(8):18901
    CrossRef
  10. Morrison C, D'Souza M, Huckvale K, Dorn JF, Burggraaff J, Kamm CP, Steinheimer SM, Kontschieder P, Criminisi A, Uitdehaag B, Dahlke F, Kappos L, Sellen A. Usability and Acceptability of ASSESS MS: Assessment of Motor Dysfunction in Multiple Sclerosis Using Depth-Sensing Computer Vision. JMIR Human Factors 2015;2(1):e11
    CrossRef
  11. Bergamini E, Ligorio G, Summa A, Vannozzi G, Cappozzo A, Sabatini A. Estimating Orientation Using Magnetic and Inertial Sensors and Different Sensor Fusion Approaches: Accuracy Assessment in Manual and Locomotion Tasks. Sensors 2014;14(10):18625
    CrossRef

According to Crossref, the following books are citing this article (DOI 10.2196/mhealth.2539)

:
  1. LeMoyne R, Mastroianni T. Wearable and Wireless Systems for Healthcare I. 2018. Chapter 6:73
    CrossRef
  2. LeMoyne R, Mastroianni T. Wireless MEMS Networks and Applications. 2017. :129
    CrossRef
  3. Kao J, Nguyen M, Nocera L, Shahabi C, Ortega A, Winstein C, Sorkhoh I, Chung Y, Chen Y, Bacon H. Computer Vision – ECCV 2016 Workshops. 2016. Chapter 12:162
    CrossRef