Evaluation by Accelerometry of Walking Pattern Before Falls in Hemiplegic Patients

Abstract

Hemiplegic patients often fall because of a lack of balance during walking. They can become bed-ridden, or suffer falling syndrome after falling. The aim of this study was to evaluate the walking pattern just prior to falls among high-risk patients in a rehabilitation setting. A triaxial accelerometer was fixed to the subject's waist, and the triaxial acceleration signals were recorded. Thirty-one subjects walked down a corridor under supervision. The data were digitized at a sampling rate of 200 Hz, and analyzed using a discrete wavelet transform. The variables required to evaluate falls were related to the reconstructed signal at level -3. We classified falls into three types. In Type 1 falls, the impact acceleration signals in the vertical direction were larger in walking just prior to a fall. In Type 2 falls, small impact acceleration signals in the vertical direction were observed. In Type 3 falls, the walking cycle changed irregularly just prior to a fall and the impact acceleration was larger and smaller before the fall. From these results, falls were evaluated. The next step will be predicting falls.

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Document Details

Document Type
Technical Report
Publication Date
Oct 25, 2001
Accession Number
ADA412474

Entities

People

  • F. Horiuchi
  • M. Sekine
  • R. Kadoya
  • T. Fujimoto
  • Y. Higasi

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Assistive Technologies
  • Classification
  • Computers
  • Diseases And Disorders
  • Frequency
  • Frequency Bands
  • Health Services
  • Hospitals
  • Impact Acceleration
  • Lower Extremity
  • Paralysis
  • Patient Care
  • Personal Computers
  • Rehabilitation
  • Test And Evaluation
  • Video Recording
  • Wavelet Transforms

Readers

  • Mathematics or Statistics
  • Neurotrauma and Rehabilitation Medicine.
  • Robotics and Automation.