Background: Depth of anaesthesia (DOA) monitors based on the electroencephalogram (EEG) are commonly used in anaesthetic practice. Their technology relies on mathematical analysis of the EEG waveform, generally resulting in a number which corresponds to anaesthetic depth. We have created a novel method of interpreting the EEG, which retains its underlying complexity. This method consists of turning the EEG into a sound: the electroencephalophone (EEP).

Methods: In a pilot study, we recorded awake and anaesthetized EEGs from six patients. We transformed each EEG into an audio signal using a ring buffer with a write frequency of 1 kHz and a read frequency of 48 kHz, thus elevating all output frequencies by a factor of 48. In essence, the listener hears the previous 12 s of EEG data compressed into 250 ms, updated every 250 ms. From these data, we generated a bank of 5 s audio clips, which were then used to train and test a sample of 23 anaesthetists.

Results: After training, 21 of the 23 anaesthetists were able to use the EEP to correctly identify the conscious state of >5 of 10 randomly selected patients (P<0.001). The median score was 8 out of 10, with an inter-quartile range of 7-9.

Conclusions: The EEP shows promise as a DOA monitor. However, extensive validation would be required in a variety of clinical settings before it could be accepted into mainstream clinical practice.

Download full-text PDF

Source
http://dx.doi.org/10.1093/bja/aet067DOI Listing

Publication Analysis

Top Keywords

frequency khz
8
eeg
6
proof concept
4
concept evaluation
4
evaluation electroencephalophone
4
electroencephalophone discriminator
4
discriminator wakefulness
4
wakefulness general
4
general anaesthesia
4
anaesthesia background
4

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!