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Published on 26.03.15 in Vol 3, No 1 (2015): Jan-Mar

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

Works citing "A Mobile Cloud-Based Parkinson’s Disease Assessment System for Home-Based Monitoring"

According to Crossref, the following articles are citing this article (DOI 10.2196/mhealth.3956):

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

  1. Devarajan M, Ravi L. Intelligent cyber-physical system for an efficient detection of Parkinson disease using fog computing. Multimedia Tools and Applications 2018;
    CrossRef
  2. Wang E, Zhou L, Chen SK, Hill K, Parmanto B. An mHealth Platform for Supporting Clinical Data Integration into Augmentative and Alternative Communication Service Delivery: User-Centered Design and Usability Evaluation. JMIR Rehabilitation and Assistive Technologies 2018;5(2):e14
    CrossRef
  3. Reinertsen E, Clifford GD. A review of physiological and behavioral monitoring with digital sensors for neuropsychiatric illnesses. Physiological Measurement 2018;39(5):05TR01
    CrossRef
  4. Son H, Park WS, Kim H. Mobility monitoring using smart technologies for Parkinson’s disease in free-living environment. Collegian 2018;25(5):549
    CrossRef
  5. Chib A, Lin SH. Theoretical Advancements in mHealth: A Systematic Review of Mobile Apps. Journal of Health Communication 2018;:1
    CrossRef
  6. 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
  7. Rovini E, Maremmani C, Cavallo F. Automated Systems Based on Wearable Sensors for the Management of Parkinson's Disease at Home: A Systematic Review. Telemedicine and e-Health 2018;
    CrossRef
  8. Stamate C, Magoulas G, Kueppers S, Nomikou E, Daskalopoulos I, Jha A, Pons J, Rothwell J, Luchini M, Moussouri T, Iannone M, Roussos G. The cloudUPDRS app: A medical device for the clinical assessment of Parkinson’s Disease. Pervasive and Mobile Computing 2018;43:146
    CrossRef
  9. Iakovakis D, Hadjidimitriou S, Charisis V, Bostantjopoulou S, Katsarou Z, Klingelhoefer L, Reichmann H, Dias SB, Diniz JA, Trivedi D, Chaudhuri KR, Hadjileontiadis LJ. Motor Impairment Estimates via Touchscreen Typing Dynamics Toward Parkinson's Disease Detection From Data Harvested In-the-Wild. Frontiers in ICT 2018;5
    CrossRef
  10. Ornelas-Vences C, Sánchez-Fernández LP, Sánchez-Pérez LA, Martínez-Hernández JM. Computer model for leg agility quantification and assessment for Parkinson’s disease patients. Medical & Biological Engineering & Computing 2018;
    CrossRef
  11. Almogren A. An automated and intelligent Parkinson disease monitoring system using wearable computing and cloud technology. Cluster Computing 2018;
    CrossRef
  12. Mitsi G, Mendoza EU, Wissel BD, Barbopoulou E, Dwivedi AK, Tsoulos I, Stavrakoudis A, Espay AJ, Papapetropoulos S. Biometric Digital Health Technology for Measuring Motor Function in Parkinson’s Disease: Results from a Feasibility and Patient Satisfaction Study. Frontiers in Neurology 2017;8
    CrossRef
  13. Miocinovic S, Shoeb AH, Wang S, Byrd EA, Swann NC, Pathak A, Ostrem JL. Clinical Tremor Severity Estimation Using an Instrumented Eating Utensil. Journal of Parkinson's Disease 2017;7(4):755
    CrossRef
  14. Jeon H, Lee W, Park H, Lee H, Kim S, Kim H, Jeon B, Park K. Automatic Classification of Tremor Severity in Parkinson’s Disease Using a Wearable Device. Sensors 2017;17(9):2067
    CrossRef
  15. Jeon H, Lee W, Park H, Lee HJ, Kim SK, Kim HB, Jeon B, Park KS. High-accuracy automatic classification of Parkinsonian tremor severity using machine learning method. Physiological Measurement 2017;38(11):1980
    CrossRef
  16. 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
  17. Roh E, Lee H, Kim D, Lee N. A Solution-Processable, Omnidirectionally Stretchable, and High-Pressure-Sensitive Piezoresistive Device. Advanced Materials 2017;29(42):1703004
    CrossRef
  18. Schneider RB, Biglan KM. The promise of telemedicine for chronic neurological disorders: the example of Parkinson's disease. The Lancet Neurology 2017;16(7):541
    CrossRef
  19. Ornelas-Vences C, Sanchez-Fernandez LP, Sanchez-Perez LA, Garza-Rodriguez A, Villegas-Bastida A. Fuzzy inference model evaluating turn for Parkinson’s disease patients. Computers in Biology and Medicine 2017;89:379
    CrossRef
  20. 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
  21. Anderson K, Emmerton LM. Contribution of mobile health applications to self-management by consumers: review of published evidence. Australian Health Review 2016;40(5):591
    CrossRef
  22. Shah N, Aleong R, So I. Novel Use of a Smartphone to Measure Standing Balance. JMIR Rehabilitation and Assistive Technologies 2016;3(1):e4
    CrossRef
  23. Pasluosta CF, Gassner H, Winkler J, Klucken J, Eskofier BM. An Emerging Era in the Management of Parkinson's Disease: Wearable Technologies and the Internet of Things. IEEE Journal of Biomedical and Health Informatics 2015;19(6):1873
    CrossRef
  24. Wiederhold BK. mHealth VR Can Transform Mental Health. Cyberpsychology, Behavior, and Social Networking 2015;18(7):365
    CrossRef
  25. Memedi M, Nyholm D, Johansson A, Palhagen S, Willows T, Widner H, Linder J, Westin J. Validity and Responsiveness of At-Home Touch Screen Assessments in Advanced Parkinson's Disease. IEEE Journal of Biomedical and Health Informatics 2015;19(6):1829
    CrossRef

According to Crossref, the following books are citing this article (DOI 10.2196/mhealth.3956)

:
  1. Gard P, Lalanne L, Ambourg A, Rousseau D, Lesueur F, Frindel C. Internet of Things (IoT) Technologies for HealthCare. 2018. Chapter 1:3
    CrossRef
  2. Madeira RN, Pereira CM, Clipei S, Macedo P. Pervasive Computing Paradigms for Mental Health. 2018. Chapter 2:10
    CrossRef
  3. LeMoyne R, Mastroianni T. Wearable and Wireless Systems for Healthcare I. 2018. Chapter 6:73
    CrossRef
  4. LeMoyne R, Mastroianni T. Wireless MEMS Networks and Applications. 2017. :129
    CrossRef