Median Nerve Stimulation Based BCI: A New Approach to Detect Intraoperative Awareness During General Anesthesia

Abstract

Hundreds of millions of general anesthesia are performed each year on patients all over the world. Among these patients, 0.1–0.2% are victims of Accidental Awareness during General Anesthesia (AAGA), i.e., an unexpected awakening during a surgical procedure under general anesthesia. Although anesthesiologists try to closely monitor patients using various techniques to prevent this terrifying phenomenon, there is currently no efficient solution to accurately detect its occurrence. We propose the conception of an innovative passive brain-computer interface (BCI) based on an intention of movement to prevent AAGA. Indeed, patients typically try to move to alert the medical staff during an AAGA, only to discover that they are unable to. First, we examine the challenges of such a BCI, i.e., the lack of a trigger to facilitate when to look for an intention to move, as well as the necessity for a high classification accuracy. Then, we present a solution that incorporates Median Nerve Stimulation (MNS). We investigate the specific modulations that MNS causes in the motor cortex and confirm that they can be altered by an intention of movement. Finally, we perform experiments on 16 healthy participants to assess whether an MI-based BCI using MNS is able to generate high classification accuracies. Our results show that MNS may provide a foundation for an innovative BCI that would allow the detection of AAGA.

Innovative Brain-Computer Interface based on motor cortex activity to detect accidental awareness during general anesthesia

“…We chose the 750 milliseconds of delay according to the reaction time of an average person, in order to stimulate during the ERD corresponding to the start of the imagination. A previous study confirmed that a MNS during the MI would not inhibit the ERD produced by this MI [20].…”

“…Nevertheless, detecting MI, especially asynchronously, is not a trivial task for current MI-based BCI. To answer this issue, we showed in a previous study that a BCI based on the median nerve stimulation (MNS) is a promising approach to detect AAGA without any trigger and with a higher performance [20]. Indeed, our results indicated that a MI significantly modulates the ERDs and ERSs previously generated by a MNS and also that classification based on MNS is more efficient than conventional classification based on MI versus rest.…”

“…At the concentrations of propofol 0.5 µg.ml −1 and 1 µg.ml −1 , very few changes were observable compared to the condition without propofol. Indeed, the ERD phase was very similar while the ERS was more effective in the medium beta (16)(17)(18)(19)(20)(21)(22)(23)(24) band.…”

“…Nowadays, an attempted movement or a Motor Imagery (MI) can be detected by extracting sensorimotor patterns from the EEG signal [17]. These sensorimotor rhythms are characterized i) before and during an imagined movement, by a gradual decrease of power in -mainly-the mu/alpha (7-13 Hz) and beta (15)(16)(17)(18)(19)(20)(21)(22)(23)(24)(25)(26)(27)(28)(29)(30) bands and ii) after the end of the motor imagery, by an increase of power in the beta band. These modulations are respectively known as Event-Related Desynchronization (ERD) and Event-Related Synchronization (ERS) or post-movement beta rebound [18], [19].…”

Accidental awareness while under general anaesthesia

“…However, a study has shown that the BIS protocol was less useful in preventing awareness than end-tidal anesthetic-agent concentration (9). Moreover, innovative techniques, such as passive brain-computer interface (BCI) based on an intention of movement may provide a foundation that would allow to detect awareness (22).…”