ArticleScientific reports2018
Development of an electrooculogram-based human-computer interface using involuntary eye movement by spatially rotating sound for communication of locked-in patients.
Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Multidisciplinary rehabilitation and eye tracker-assisted communication in locked-in syndrome: a case report and literature review.Frontiers in human neuroscience · 2026Article
- Continuous Biopotential Monitoring via Carbon Nanotubes Paper Composites (CPC) for Sustainable Health Analysis.Sensors (Basel, Switzerland) · 2023Article
- Writing Blindly in Incomplete Locked-In Syndrome with A Custom-Made Switch-Operated Voice-Scanning Communicator-A Case Report.Brain sciences · 2022Article
- [A review on voluntary or involuntary eye movement classification methods based on electro-oculogram and their applications].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2022Review
- EOG-Based Human-Computer Interface: 2000-2020 Review.Sensors (Basel, Switzerland) · 2022Review
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Authors and funding
3 authors.
Funding
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Abstract
Individuals who have lost normal pathways for communication need augmentative and alternative communication (AAC) devices. In this study, we propose a new electrooculogram (EOG)-based human-computer interface (HCI) paradigm for AAC that does not require a user's voluntary eye movement for binary yes/no communication by patients in locked-in state (LIS). The proposed HCI uses a horizontal EOG elicited by involuntary auditory oculogyric reflex, in response to a rotating sound source. In the proposed HCI paradigm, a user was asked to selectively attend to one of two sound sources rotating in directions opposite to each other, based on the user's intention. The user's intentions could then be recognised by quantifying EOGs. To validate its performance, a series of experiments was conducted with ten healthy subjects, and two patients with amyotrophic lateral sclerosis (ALS). The online experimental results exhibited high-classification accuracies of 94% in both healthy subjects and ALS patients in cases where decisions were made every six seconds. The ALS patients also participated in a practical yes/no communication experiment with 26 or 30 questions with known answers. The accuracy of the experiments with questionnaires was 94%, demonstrating that our paradigm could constitute an auxiliary AAC system for some LIS patients.
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