Detection of response to command using voluntary control of breathing in disorders of consciousness

Vanessa Charland-Verville*, Damien Lesenfants, Lee Sela, Quentin Noirhomme, Erik Ziegler, Camille Chatelle, Anton Plotkin, Noam Sobel, Steven Laureys

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

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Abstract

Detecting signs of consciousness in patients in a vegetative state/unresponsive wakefulness syndrome (UWS/VS) or minimally conscious state (MCS) is known to be very challenging. Plotkin et al. (2010) recently showed the possibility of using a breathing-controlled communication device in patients with locked in syndrome. We here aim to test a breathing-based "sniff controller" that could be used as an alternative diagnostic tool to evaluate response to command in severely brain damaged patients with chronic disorders of consciousness (DOC).Twenty-five DOC patients were included. Patients' resting breathing-amplitude was measured during a 5 min resting condition. Next, they were instructed to end the presentation of a music sequence by sniffing vigorously. An automated detection of changes in breathing amplitude (i.e., >1.5 SD of resting) ended the music and hence provided positive feedback to the patient.None of the 11 UWS/VS patients showed a sniff-based response to command. One out of 14 patients with MCS was able to willfully modulate his breathing pattern to answer the command on 16/19 trials (accuracy 84%). Interestingly, this patient failed to show any other motor response to command.We here illustrate the possible interest of using breathing-dependent response to command in the detection of residual cognition in patients with DOC after severe brain injury.
Original languageEnglish
Article number1020
JournalFrontiers in Human Neuroscience
Volume8
DOIs
Publication statusPublished - 23 Dec 2014

Keywords

  • disorders of consciousness
  • breathing
  • sniffing
  • vegetative state
  • unresponsive wakefulness syndrome
  • minimally conscious state
  • diagnosis
  • brain-computer interface

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