Login / Signup

Gait Study of Parkinson's Disease Subjects Using Haptic Cues with A Motorized Walker.

Minhua ZhangN Sertac ArtanHuanying GuZiqian DongLyudmila Burina GanatraSuzanna ShermonEly Rabin
Published in: Sensors (Basel, Switzerland) (2018)
Gait abnormalities are one of the distinguishing symptoms of patients with Parkinson's disease (PD) that contribute to fall risk. Our study compares the gait parameters of people with PD when they walk through a predefined course under different haptic speed cue conditions (1) without assistance, (2) pushing a conventional rolling walker, and (3) holding onto a self-navigating motorized walker under different speed cues. Six people with PD were recruited at the New York Institute of Technology College of Osteopathic Medicine to participate in this study. Spatial posture and gait data of the test subjects were collected via a VICON motion capture system. We developed a framework to process and extract gait features and applied statistical analysis on these features to examine the significance of the findings. The results showed that the motorized walker providing a robust haptic cue significantly improved gait symmetry of PD subjects. Specifically, the asymmetry index of the gait cycle time was reduced from 6.7% when walking without assistance to 0.56% and below when using a walker. Furthermore, the double support time of a gait cycle was reduced by 4.88% compared to walking without assistance.
Keyphrases
  • cerebral palsy
  • oxidative stress
  • high resolution
  • mass spectrometry
  • virtual reality
  • deep learning
  • artificial intelligence