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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"

Boris Takač, Andreu Català, Daniel Rodríguez Martín, Nico van der Aa, Wei Chen, Matthias Rauterberg

JMIR Mhealth Uhealth 2013 (Jul 15); 1(2):e14 

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. del Rosario M, Redmond S, Lovell N. Tracking the Evolution of Smartphone Sensing for Monitoring Human Movement. Sensors 2015;15(8):18901
    CrossRef
  2. 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
  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 2019;34(1):38
    CrossRef
  5. 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
  6. Linares-del Rey M, Vela-Desojo L, Cano-de la Cuerda R. Mobile phone applications in Parkinson's disease: a systematic review. Neurología (English Edition) 2019;34(1):38
    CrossRef
  7. 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
  8. 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
  9. Rudå D, Einarsson G, Matthiassen JB, Correll CU, Jensen KG, Klauber DG, Richard CJ, Andersen ASS, Krøigaard S, Møllegaard Jepsen JR, Fagerlund B, Winge K, Clemmesen LKH, Pagsberg AK, Paulsen RR, Fink‐Jensen A. Measuring movements in adolescents with psychosis using the Microsoft Kinect sensor: a pilot study exploring a new tool for assessing aspects of antipsychotic‐induced parkinsonism. Child and Adolescent Mental Health 2020;25(2):79
    CrossRef
  10. 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
  11. Mazzetta I, Zampogna A, Suppa A, Gumiero A, Pessione M, Irrera F. Wearable Sensors System for an Improved Analysis of Freezing of Gait in Parkinson’s Disease Using Electromyography and Inertial Signals. Sensors 2019;19(4):948
    CrossRef
  12. 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
  13. 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
  14. 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
  15. Zhang H, Song C, Rathore AS, Huang M, Zhang Y, Xu W. mHealth Technologies Towards Parkinson's Disease Detection and Monitoring in Daily Life: A Comprehensive Review. IEEE Reviews in Biomedical Engineering 2021;14:71
    CrossRef
  16. Kour N, Sunanda , Arora S. Computer-Vision Based Diagnosis of Parkinson’s Disease via Gait: A Survey. IEEE Access 2019;7:156620
    CrossRef
  17. Huang T, Li M, Huang J. Recent trends in wearable device used to detect freezing of gait and falls in people with Parkinson’s disease: A systematic review. Frontiers in Aging Neuroscience 2023;15
    CrossRef
  18. Cicirelli G, Impedovo D, Dentamaro V, Marani R, Pirlo G, D'Orazio TR. Human Gait Analysis in Neurodegenerative Diseases: A Review. IEEE Journal of Biomedical and Health Informatics 2022;26(1):229
    CrossRef

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

  1. 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
  2. LeMoyne R, Mastroianni T. Wireless MEMS Networks and Applications. 2017. :129
    CrossRef
  3. . Smartphone-Based Human Activity Recognition. 2015. Chapter 2:9
    CrossRef
  4. LeMoyne R, Mastroianni T. Wearable and Wireless Systems for Healthcare I. 2018. Chapter 6:73
    CrossRef
  5. Senders JT, Maher N, Hulsbergen AFC, Lamba N, Bredenoord AL, Broekman MLD. Ethics of Innovation in Neurosurgery. 2019. Chapter 14:129
    CrossRef