How brain-computer interface technology may improve the diagnosis of the disorders of consciousness: A comparative study

Rossella Spataro; Yiyan Xu; Ren Xu; Giorgio Mandalà; Brendan Z Allison; Rupert Ortner; Alexander Heilinger; Vincenzo La Bella; Christoph Guger

doi:10.3389/fnins.2022.959339

How brain-computer interface technology may improve the diagnosis of the disorders of consciousness: A comparative study

Front Neurosci. 2022 Aug 11:16:959339. doi: 10.3389/fnins.2022.959339. eCollection 2022.

Authors

Rossella Spataro^{1

2}, Yiyan Xu², Ren Xu³, Giorgio Mandalà⁴, Brendan Z Allison⁵, Rupert Ortner⁶, Alexander Heilinger³, Vincenzo La Bella², Christoph Guger^{3

6}

Affiliations

¹ IRCCS Centro Neurolesi Bonino Pulejo, Palermo, Italy.
² ALS Clinical Research Center, University of Palermo, Palermo, Italy.
³ g.tec Medical Engineering GmbH, Schiedlberg, Austria.
⁴ Rehabilitation Unit, Ospedale Buccheri La Ferla, Palermo, Italy.
⁵ Cognitive Science Department, University of California, San Diego, San Diego, United States.
⁶ g.tec Medical Engineering Spain S.L., Barcelona, Spain.

Abstract

Objective: Clinical assessment of consciousness relies on behavioural assessments, which have several limitations. Hence, disorder of consciousness (DOC) patients are often misdiagnosed. In this work, we aimed to compare the repetitive assessment of consciousness performed with a clinical behavioural and a Brain-Computer Interface (BCI) approach.

Materials and methods: For 7 weeks, sixteen DOC patients participated in weekly evaluations using both the Coma Recovery Scale-Revised (CRS-R) and a vibrotactile P300 BCI paradigm. To use the BCI, patients had to perform an active mental task that required detecting specific stimuli while ignoring other stimuli. We analysed the reliability and the efficacy in the detection of command following resulting from the two methodologies.

Results: Over repetitive administrations, the BCI paradigm detected command following before the CRS-R in seven patients. Four clinically unresponsive patients consistently showed command following during the BCI assessments.

Conclusion: Brain-Computer Interface active paradigms might contribute to the evaluation of the level of consciousness, increasing the diagnostic precision of the clinical bedside approach.

Significance: The integration of different diagnostic methods leads to a better knowledge and care for the DOC.

Keywords: Coma Recovery Scale-Revised; brain-computer interface; covert consciousness; minimally conscious state; unresponsive wakefulness syndrome; vegetative state.