Abstract
The decreasing trend in power spectral density (PSD) of electroencephalogram (EEG) has been shown to be related with the depth of anesthesia (DOA). However, conventional DOA indices, which utilize part of EEG frequency band, have a difficulty in quantifying the decreasing trend in the EEG PSD along the frequency axis. This paper proposes a method of effectively quantifying the characteristic change in the EEG PSD to measure the DOA. The method is based on the newly introduced ordinal PSD (O-PSD) which assigns ordinal indices to a series of values in the order of PSD magnitude. The O-PSD can capture the spectral trend along the overall frequency band robust to the EEG variation due to inter-subject dependency and measurement environment. We quantified the O-PSD pattern into a unitless index in the range 0 to 1. We compared the proposed O-PSD based index with the conventional indices for 15 subjects with injection rate of 12 mg/kg/h and 12 subjects with injection rate of 6 mg/kg/h. We evaluated the discriminative performance of the proposed index using prediction probability and Spearman’s correlation coefficient. Also, we evaluated the steadiness and stability of the proposed index using the coefficient of variation. Our proposed index was shown to be superior in distinguishing consciousness and unconsciousness, and a stable and steady measure during unconsciousness. These results indicate that the O-PSD and the proposed index would be a reliable method for quantifying the DOA.
Highlights
General anesthesia (GA) is drug-induced unconsciousness accompanied by analgesia, amnesia, and loss of autonomic reflexes [1]
Various EEG-based depth of anesthesia (DOA) indices, such as relative beta ratio (RBR), spectral edge frequency 95 (SEF95), approximate entropy (ApEn), and synchfastslow (SFS) have been developed to quantify the DOA based on the EEG during the GA process [13]–[17]
We demonstrate that the O-power spectral density (PSD) can be useful for measuring the DOA during the GA process
Summary
General anesthesia (GA) is drug-induced unconsciousness accompanied by analgesia, amnesia, and loss of autonomic reflexes [1]. A patient undergoes stepwise change in consciousness from awakeness to deep hypnosis, known as depth of anesthesia (DOA). Depending on the level of consciousness induced by an anesthetic, the EEG shows systematic changes [8]–[12]. Various EEG-based DOA indices, such as relative beta ratio (RBR), spectral edge frequency 95 (SEF95), approximate entropy (ApEn), and synchfastslow (SFS) have been developed to quantify the DOA based on the EEG during the GA process [13]–[17]. The RBR, SEF95, and SFS are spectral indices that utilize the ratio between the spectral powers of specific frequency bands in the EEG power spectral density (PSD) [13], [14], [16]. The dynamic range of the EEG magnitude and the spectral power varies, depending on subjects, and is sensitive
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