A Visual Feedback Supported Intelligent Assistive Technique for Amyotrophic Lateral Sclerosis Patients

Among diverse intelligent assistive systems developed for amyotrophic lateral sclerosis (ALS) patients, headwear eye tracking based ones trigger broad interests due to their merits such as noninvasive, cost effective, and high operation freedom. However, with headwear eye trackers, patients are easy to feel tired during human–machine interactivities (HMIs), and the operation accuracy is not satisfied compared with its counterparts. To address these two issues, herein, a visual feedback technique is developed which allows users to recognize machine's vision by positioning a laser spot to the user watched object, according to the location information interpreted from user's eye movement. Through the visual feedback technique, users not only obtain real‐time feedback, but also can fine‐tune the laser spot to the desired location before performing further operations. Experimental results demonstrate that the presented work can successfully reduce user's fatigue and boost operation accuracy by 25.1% and 27.6%, respectively, therefore, advancing the field of intelligent assistive technologies.

Location
Deutsche Nationalbibliothek Frankfurt am Main
Extent
Online-Ressource
Language
Englisch

Bibliographic citation
A Visual Feedback Supported Intelligent Assistive Technique for Amyotrophic Lateral Sclerosis Patients ; volume:4 ; number:4 ; year:2022 ; extent:12
Advanced intelligent systems ; 4, Heft 4 (2022) (gesamt 12)

Creator
Wang, Zihao
Zhang, Aojie
Xia, Xinyue
Zhang, Sizhe
Li, Haitao
Wang, Jiaqi
Gao, Shuo

DOI
10.1002/aisy.202100097
URN
urn:nbn:de:101:1-2022042215052986605002
Rights
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
Last update
15.08.2025, 7:34 AM CEST

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Associated

  • Wang, Zihao
  • Zhang, Aojie
  • Xia, Xinyue
  • Zhang, Sizhe
  • Li, Haitao
  • Wang, Jiaqi
  • Gao, Shuo

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