Abstract
Objective. Patients undergoing general anesthesia may awaken and become aware of the surgical procedure. Due to neuromuscular blocking agents, patients could be conscious yet unable to move. Using brain–computer interface (BCI) technology, it may be possible to detect movement attempts from the EEG. However, it is unknown how an anesthetic influences the brain response to motor tasks. Approach. We tested the offline classification performance of a movement-based BCI in 12 healthy subjects at two effect-site concentrations of propofol. For each subject a second classifier was trained on the subject’s data obtained before sedation, then tested on the data obtained during sedation (‘transfer classification’). Main results. At concentration 0.5 μg ml−1, despite an overall propofol EEG effect, the mean single trial classification accuracy was 85% (95% CI 81%–89%), and 83% (79%–88%) for the transfer classification. At 1.0 μg ml−1, the accuracies were 81% (76%–86%), and 72% (66%–79%), respectively. At the highest propofol concentration for four subjects, unlike the remaining subjects, the movement-related brain response had been largely diminished, and the transfer classification accuracy was not significantly above chance. These subjects showed a slower and more erratic task response, indicating an altered state of consciousness distinct from that of the other subjects. Significance. The results show the potential of using a BCI to detect intra-operative awareness and justify further development of this paradigm. At the same time, the relationship between motor responses and consciousness and its clinical relevance for intraoperative awareness requires further investigation.
Highlights
Brain–computer interfaces (BCIs) are systems directly translating brain signals into useful output, such as control of a device
This study showed that motor responses could be detected from the EEG of volunteers during altered states of consciousness, with an average single trial classification accuracy of 85% at a propofol effect-site concentration of 0.5 μg ml−1 and 81% at a propofol effect-site concentration of 1.0 μg ml−1
Adding this to previous findings showing the possibility of detecting attempted movement during neuromuscular block [13], we conclude that further development of the proposed BCI is justified
Summary
Brain–computer interfaces (BCIs) are systems directly translating brain signals into useful output, such as control of a device. By eliminating the need for muscular control, BCIs can provide a means of interaction with the environment for partially or completely paralysed patients (e.g. in [1]). Patients under general anesthesia are often temporarily paralysed with a neuromuscular blocking agent. If they awake during surgery, they may find themselves in a situation where they have a certain degree of consciousness but are unable to move or speak. This experience, known as ‘unintended awareness with postoperative explicit recall’, has an estimated incidence of 0.1%–0.2% [2]. We propose to extend BCI research into the domain of anesthesia awareness
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