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

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2014

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Frontiers Media S.A.
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Charland-Verville, Vanessa, Damien Lesenfants, Lee Sela, Quentin Noirhomme, Erik Ziegler, Camille Chatelle, Anton Plotkin, Noam Sobel, and Steven Laureys. 2014. “Detection of response to command using voluntary control of breathing in disorders of consciousness.” Frontiers in Human Neuroscience 8 (1): 1020. doi:10.3389/fnhum.2014.01020. http://dx.doi.org/10.3389/fnhum.2014.01020.

Abstract

Background:: 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). Methods:: 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. Results:: 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. Discussion: 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.

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

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