Recognition of ascending stairs from 2D images for control of powered lower limb prostheses

Nili E. Krausz*, Levi J. Hargrove

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

12 Scopus citations

Abstract

Intent recognition is essential for effective control of powered assistive devices, such as powered lower limb prostheses, exoskeletons, or wheelchairs. Currently, EMG and mechanical sensors are used for intent recognition of powered lower limb prostheses. We propose the addition of vision for improved intent recognition control, with this work focused on determining the best method for recognizing of ascending stair edges from 2D images. In this work different image processing methods were tested to determine which method produces the best line extraction. The best results were obtained using Canny, Sobel, Prewitt, and Roberts Cross edge detectors for four colorspace components. Finally, a convex/concave line decision system was developed to produce preliminary results about the presence or absence of stairs in a given image.

Original languageEnglish (US)
Title of host publication2015 7th International IEEE/EMBS Conference on Neural Engineering, NER 2015
PublisherIEEE Computer Society
Pages615-618
Number of pages4
Volume2015-July
ISBN (Electronic)9781467363891
DOIs
StatePublished - Jan 1 2015
Event7th International IEEE/EMBS Conference on Neural Engineering, NER 2015 - Montpellier, France
Duration: Apr 22 2015Apr 24 2015

Other

Other7th International IEEE/EMBS Conference on Neural Engineering, NER 2015
Country/TerritoryFrance
CityMontpellier
Period4/22/154/24/15

ASJC Scopus subject areas

  • Artificial Intelligence
  • Mechanical Engineering

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