2022
DOI: 10.1186/s12871-022-01864-6
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Novel insights on association and reactivity of Bispectral Index, frontal electromyogram, and autonomic responses in nociception-sedation monitoring of critical care patients

Abstract: Background Assessing nociception and sedation in mechanically ventilated patients in the ICU is challenging, with few reliable methods available for continuous monitoring. Measurable cardiovascular and neurophysiological signals, such as frontal EEG, frontal EMG, heart rate, and blood pressure, have potential in sedation and nociception monitoring. The hypothesis of this explorative study is that derived variables from the aforementioned signals predict the level of sedation, as described by th… Show more

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Cited by 4 publications
(3 citation statements)
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“…Moreover, the accuracy and relevance of these indices in the face of hemodynamic events have been debated, further impeding their universal adoption. [14][15][16][17][18][19][20][21] One notable parameter is the normalized pulse volume (NPV), which represents the ratio of the pulsatile to non-pulsatile component in pulse oximetry. Historically used in polygraphs, 22,23 recent research has shown its potential to reflect mental stress.…”
Section: Introductionmentioning
confidence: 99%
“…Moreover, the accuracy and relevance of these indices in the face of hemodynamic events have been debated, further impeding their universal adoption. [14][15][16][17][18][19][20][21] One notable parameter is the normalized pulse volume (NPV), which represents the ratio of the pulsatile to non-pulsatile component in pulse oximetry. Historically used in polygraphs, 22,23 recent research has shown its potential to reflect mental stress.…”
Section: Introductionmentioning
confidence: 99%
“…The bispectral analysis is a sophisticated signal processing approach that measures quadratic nonlinearities (phase-coupling) between signal components. Due to their interdependencies, it revealed unambiguity in many biomedical signals, such as the electrocardiogram (ECG) and electroencephalogram (EEG) [18][19][20][21][22][23][24]. Note that the features obtained using these methods may enhance the performance of the deep learning algorithm.…”
Section: Introductionmentioning
confidence: 99%
“…The bispectral analysis is an advanced method to process signals that looks at the phase coupling (quadratic nonlinearities) between signal parts that do not behave in a straight line. Numerous biological signals, including the electrocardiogram (ECG) and electroencephalogram (EEG), are unambiguous as a result of their interdependencies [36][37][38][39][40][41][42]. The features gained from these approaches may improve how well the deep learning algorithm works.…”
Section: Introductionmentioning
confidence: 99%