ArticleEntropy (Basel, Switzerland)2020
Consciousness Detection in a Complete Locked-in Syndrome Patient through Multiscale Approach Analysis.
Article in Entropy (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 10 citations in OpenAlex.
- Disorder of consciousness rather than complete Locked-In Syndrome for end stage Amyotrophic Lateral Sclerosis: a case series.Communications medicine · 2025Article
- Theories of consciousness from the perspective of an embedded processes view.Psychological review · 2025Review
- Altered brain dynamics index levels of arousal in complete locked-in syndrome.Communications biology · 2023Article
- State-of-the-Art on Brain-Computer Interface Technology.Sensors (Basel, Switzerland) · 2023Review
- Locked-in syndrome revisited.Therapeutic advances in neurological disorders · 2023Review
- Application of Soft-Clustering to Assess Consciousness in a CLIS Patient.Brain sciences · 2022Article
- Neuroscience of consciousness in the locked-in syndrome: Prognostic and diagnostic review.Ibrain · 2022Article
- Consciousness and complexity: a consilience of evidence.Neuroscience of consciousness · 2021Review
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Completely locked-in state (CLIS) patients are unable to speak and have lost all muscle movement. From the external view, the internal brain activity of such patients cannot be easily perceived, but CLIS patients are considered to still be conscious and cognitively active. Detecting the current state of consciousness of CLIS patients is non-trivial, and it is difficult to ascertain whether CLIS patients are conscious or not. Thus, it is important to find alternative ways to re-establish communication with these patients during periods of awareness, and one such alternative is through a brain-computer interface (BCI). In this study, multiscale-based methods (multiscale sample entropy, multiscale permutation entropy and multiscale Poincaré plots) were applied to analyze electrocorticogram signals from a CLIS patient to detect the underlying consciousness level. Results from these different methods converge to a specific period of awareness of the CLIS patient in question, coinciding with the period during which the CLIS patient is recorded to have communicated with an experimenter. The aim of the investigation is to propose a methodology that could be used to create reliable communication with CLIS patients.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.