Analysis of Speech from People with Parkinson's Disease through Nonlinear Dynamics

  title={Analysis of Speech from People with Parkinson's Disease through Nonlinear Dynamics},
  author={J. R. Orozco-Arroyave and J. D. Arias-Londo{\~n}o and J. F. Vargas-Bonilla and E. N{\"o}th},
  • J. R. Orozco-Arroyave, J. D. Arias-Londoño, +1 author E. Nöth
  • Published in NOLISP 2013
  • Computer Science
  • Different characterization approaches, including nonlinear dynamics (NLD), have been addressed for the automatic detection of PD; however, the obtained discrimination capability when only NLD features are considered has not been evaluated yet. 

    Figures and Topics from this paper.

    Explore Further: Topics Discussed in This Paper

    Speech disorders in Parkinson’s disease: early diagnostics and effects of medication and brain stimulation
    • 55
    • Highly Influenced
    Robust and complex approach of pathological speech signal analysis
    • 55
    Assessing progress of Parkinson's disease using acoustic analysis of phonation
    • 23


    Publications referenced by this paper.
    Suitability of Dysphonia Measurements for Telemonitoring of Parkinson's Disease
    • 592
    • PDF
    Learning with kernels
    • 7,408
    • PDF
    Floating search methods in feature selection
    • 2,853
    • PDF
    Multiscale entropy analysis of biological signals.
    • 1,527
    • PDF
    Nonlinear Time Series Analysis
    • 3,883
    • Highly Influential
    • PDF
    Speech treatment for Parkinson's disease.
    • 172
    • PDF
    Exploiting Nonlinear Recurrence and Fractal Scaling Properties for Voice Disorder Detection
    • 210
    The Parkinson larynx: tremor and videostroboscopic findings.
    • 138