150
Views
6
CrossRef citations to date
0
Altmetric
ORIGINAL ARTICLE

Two persons with multiple disabilities use camera-based microswitch technology to control stimulation with small mouth and eyelid responses

, , , , , & show all
Pages 337-342 | Published online: 01 Oct 2012
 

Abstract

Background A camera-based microswitch technology was recently developed to monitor small facial responses of persons with multiple disabilities and allow those responses to control environmental stimulation. This study assessed such a technology with 2 new participants using slight variations of previous responses.

Method The technology involved a computer with a CPU using a 2GHz clock, a USB video camera with 16-mm lens, and special software. Small colour spots were used under the lower lip of one participant and on the eyelid of the other participant to aid the camera and computer to detect their mouth and eyelid responses. The study involved an ABAB design and included a 3-week post-intervention check.

Results The participants’ mouth and eyelid responses increased during the intervention (B) phases and post-intervention check (i.e., when the technology allowed them to control stimulation).

Conclusions Camera-based microswitch technology can help persons with multiple disabilities control stimulation with small responses.

Declaration of interest: The authors report no conflicts of interest. The authors alone are responsible for the content and writing of the paper.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 65.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 400.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.