Development of an electrooculogram-based eye-computer interface for communication of individuals with amyotrophic lateral sclerosisopen access
- Authors
- Chang, Won-Du; Cha, Ho-Seung; Kim, Do Yeon; Kim, Seung Hyun; Im, Chang-Hwan
- Issue Date
- Sep-2017
- Publisher
- BMC
- Keywords
- Electrooculogram (EOG); Saccade; Eye-writing; Amyotrophic lateral sclerosis (ALS); Human-computer interface (HCI)
- Citation
- JOURNAL OF NEUROENGINEERING AND REHABILITATION, v.14, pp.1 - 13
- Indexed
- SCIE
SCOPUS
- Journal Title
- JOURNAL OF NEUROENGINEERING AND REHABILITATION
- Volume
- 14
- Start Page
- 1
- End Page
- 13
- URI
- https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/19432
- DOI
- 10.1186/s12984-017-0303-5
- ISSN
- 1743-0003
- Abstract
- Background: Electrooculogram (EOG) can be used to continuously track eye movements and can thus be considered as an alternative to conventional camera-based eye trackers. Although many EOG-based eye tracking systems have been studied with the ultimate goal of providing a new way of communication for individuals with amyotrophic lateral sclerosis (ALS), most of them were tested with healthy people only. In this paper, we investigated the feasibility of EOG-based eye-writing as a new mode of communication for individuals with ALS. Methods: We developed an EOG-based eye-writing system and tested this system with 18 healthy participants and three participants with ALS. We also applied a new method for removing crosstalk between horizontal and vertical EOG components. All study participants were asked to eye-write specially designed patterns of 10 Arabic numbers three times after a short practice session. Results: Our system achieved a mean recognition rates of 95.93% for healthy participants and showed recognition rates of 95.00%, 66.67%, and 93.33% for the three participants with ALS. The low recognition rates in one of the participants with ALS was mainly due to miswritten letters, the number of which decreased as the experiment proceeded. Conclusion: Our proposed eye-writing system is a feasible human-computer interface (HCI) tool for enabling practical communication of individuals with ALS.
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