Rest tremor quantification based on fuzzy inference systems and wearable sensors.

Journal: International journal of medical informatics
Published Date:

Abstract

BACKGROUND: Currently the most consistent, widely accepted and detailed instrument to rate Parkinson's disease (PD) is the Movement Disorder Society sponsored Unified Parkinson Disease Rating Scale (MDS-UPDRS). However, the motor examination is based upon subjective human interpretation trying to capture a snapshot of PD status. Wearable sensors and machine learning have been broadly used to analyze PD motor disorder, but still most ratings and examinations lay outside MDS-UPDRS standards. Moreover, logical connections between features and output ratings are not clear and complex to derive from the model, thus limiting the understanding of the structure in the data.

Authors

  • Luis A Sanchez-Perez
    Department of Electrical and Computer Engineering, University of Michigan - Dearborn, MI, USA; Instituto Politecnico Nacional, Centro de Investigacion en Computacion, Mexico City, Mexico. Electronic address: alejand@umich.edu.
  • Luis P Sanchez-Fernandez
    Instituto Politecnico Nacional, Centro de Investigacion en Computacion, Mexico City, Mexico. Electronic address: lsanchez@cic.ipn.mx.
  • Adnan Shaout
    Department of Electrical and Computer Engineering, University of Michigan - Dearborn, MI, USA. Electronic address: shaout@umich.edu.
  • Juan M Martinez-Hernandez
    Instituto Politecnico Nacional Escuela Nacional de Medicina y Homeopatia, Mexico City, Mexico. Electronic address: jmmartinezh@ipn.mx.
  • Maria J Alvarez-Noriega
    Instituto Politecnico Nacional Escuela Nacional de Medicina y Homeopatia, Mexico City, Mexico. Electronic address: majoalvarez@qimed.mx.