Journal of clinical monitoring and computing
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J Clin Monit Comput · Jun 2022
ReviewPower spectrum and spectrogram of EEG analysis during general anesthesia: Python-based computer programming analysis.
The commonly used principle for measuring the depth of anesthesia involves changes in the frequency components of the electroencephalogram (EEG) under general anesthesia. Therefore, it is essential to construct an effective spectrum and spectrogram to analyze the relationship between the depth of anesthesia and the EEG frequency during general anesthesia. This paper reviews the computer programming techniques for analyzing the spectrum and spectrogram derived from a single-channel EEG recorded during general anesthesia. ⋯ Finally, the multitaper method, which can suppress artifacts caused by the edges of the analysis segments, suppress noise, and probabilistically infer values that are close to the real power spectral density, is explained using practical examples of the analysis. All analyses were performed and all graphs plotted using Python under Jupyter Notebook. The analyses demonstrated the effectiveness of Python-based programming under the integrated development environment Jupyter Notebook for constructing an effective spectrum and spectrogram for analyzing the relationship between the depth of anesthesia and EEG frequency analysis in general anesthesia.
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J Clin Monit Comput · Jun 2022
Reliability assessment of hyperspectral imaging with the HyperView™ system for lower extremity superficial tissue oxygenation in young healthy volunteers.
Hyperspectral imaging (HSI) is a noninvasive spectroscopy technique for determining superficial tissue oxygenation. The HyperView™ system is a hand-held camera that enables perfusion image acquisition. The evaluation of superficial tissue oxygenation is warranted in the evaluation of patients with peripheral arterial disease. The aim was to determine the reliability of repeated HSI measurements. ⋯ This study showed good short term test-retest reliability for HSI measurements, however low intra- and inter-observer reliability was observed for tissue oxygenation measurements with both HSI and TcPO2 performed at separate days in young healthy volunteers. Reliability of HSI can be improved when determined as a mean of two measurements taken on different days.
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J Clin Monit Comput · Jun 2022
Volatile anesthetic gas concentration sensing using flow sensor fusion for use in Austere settings.
Flow sensors are often sensitive to the presence of volatile anesthetics. However, this sensitivity provides a unique opportunity to combine flow sensors of differing technological principles as an alternative to measuring volatile anesthetic gas concentration, particularly for austere settings. To determine the feasibility of flow sensor fusion for volatile anesthetic concentrations monitoring, eight flow sensors were tested with isoflurane, sevoflurane, and desflurane, ranging in concentrations from 0-4.5%, 0-3.5%, and 0-18%, respectively. ⋯ Conclusion: Measuring volatile anesthetic gases using flow sensor fusion is a feasible low-cost, low-maintenance alternative to infrared spectroscopy. In this study, testing was done under steady-state conditions in 100% oxygen. Further testing is necessary to ensure sensor fusion performance under conditions that are more reflective of the clinical use case.
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This paper provides a review of a selection of papers published in the Journal of Clinical Monitoring and Computing in 2020 and 2021 highlighting what is new within the field of respiratory monitoring. Selected papers cover work in pulse oximetry monitoring, acoustic monitoring, respiratory system mechanics, monitoring during surgery, electrical impedance tomography, respiratory rate monitoring, lung ultrasound and detection of patient-ventilator asynchrony.
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J Clin Monit Comput · Jun 2022
Changes in arterial blood pressure characteristics following an extrasystolic beat or a fast 50 ml fluid challenge do not predict fluid responsiveness during cardiac surgery.
Prediction of fluid responsiveness is essential in perioperative goal directed therapy, but dynamic tests of fluid responsiveness are not applicable during open-chest surgery. We hypothesised that two methods could predict fluid responsiveness during cardiac surgery based on their ability to alter preload and thereby induce changes in arterial blood pressure characteristics: (1) the change caused by extrasystolic beats and (2) the change caused by a fast infusion of 50 ml crystalloid (micro-fluid challenge). Arterial blood pressure and electrocardiogram waveforms were collected during surgical preparation of the left internal mammary artery in patients undergoing coronary artery bypass surgery. ⋯ Extrasystoles did not predict fluid responsiveness with convincing accuracy in patients undergoing cardiac surgery and changes in arterial waveform indices following a micro-fluid challenge could not predict fluid responsiveness. Given a low number of fluid responders and inherently reduced statistical power, our data does not support firm conclusions about the utility of the extrasystolic method. CLINICAL TRIAL REGISTRATION: Unique identifier: NCT02903316. https://clinicaltrials.gov/ct2/show/NCT02903316?cond=NCT02903316&rank=1 .