• Transactions on Electrical and Electronic Materials
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• v.14 no.6
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• pp.299-303
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• 2013

Anesthesia, which started being used to remove pain during surgery, has become itself one of the major concerns to be considered during surgery. While actual anesthesia is being performed, patients tend to have unpleasant experiences, due to wakening that accompanies pain, or wakening that does not accompany pain. Since this awakening during anesthesia is a most unpleasant experience in a patient's life, evaluating the depth of anesthesia during surgery is essential for patients to avoid this experience. Although there has been much effort on the understanding and measurement of the depth of anesthesia, while various researches were performed on the need of anesthesia, the development of an indicator that could objectively evaluate the depth of anesthesia, other than by using the patient's vital signs, is still inadequate. Therefore, this study was to develop an objective indicator by using EEG and ECG, which are essentially measured during the surgery, to evaluate the depth of anesthesia. The experiment was performed by taking patients who require a relatively short operation time, and general inhalation anesthetics among surgical patients in obstetrics and gynecology as the subjects of experiment, to measure the EEG and ECG signals of patients under anesthetics. The result showed that SEF using EEG and LF, HF using ECG signal and correlation dimension analysis parameter were valuable parameters that could measure the depth of anesthesia, by the stage of anesthesia.

• Journal of Biomedical Engineering Research
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• v.30 no.4
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• pp.327-332
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• 2009

In this paper, new index was developed to estimate the depth of anesthesia during general anesthesia using EEG. Analysis of the power spectral density(PSD) of EEG was used to develop new parameters because EEG signal tends to have slow wave during anesthesia. Classifier for index creator was developed by using SEF, BDR and BTR parameters, which are calculated by power spectral density. EEG data were obtained from 7 patients (ASA I, II) during general anesthesia with Sevoflurane. The anesthetic depth evaluation indexes ranged from 0 to 100. The average were $86.05{\pm}10.1$, $36.98{\pm}20.2$, $15.33{\pm}13.6$, $50.87{\pm}16.5$ and $87.72{\pm}11.7$ for the states of pre-operation, induction of anesthesia, operation, awaked and post-operation, respectively. The results show that while the depth of anesthesia was evaluated, more accurate information can be provided for anesthetician.

• Journal of Biomedical Engineering Research
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• v.28 no.2
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• pp.287-293
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• 2007

The researchers have studied for a long time about the depth of anesthesia but they don't make criteria for the depth of anesthesia. Anesthetists can't make a prediction about patient's reaction. Therefore, patients have potential risk such as poisonous side effect, late-awake, early-awake and strain reaction. In this study, the distributed characteristics on the bispectrum and bicoherence, the type of nonlinear signal processing, as a result of the coupling of EEG were presented according to depth of anesthesia. These results were consistent with a trend of delta ratio that the index of evaluation for the depth of anesthesia. The higher-order spectrum (HOS), the bispectrum and bicoherence, gives the useful information about depth of anaesthesia than other indexes.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.23 no.2
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• pp.103-117
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• 2010

In this study, the heart rate variability(HRV) signal of operating patient was acquired according to anesthesia progress and identified to evaluation possibility of depth of anesthesia in each anesthesia stage. The HRV signal was analyzed time-frequency domain applied to Wigner-Ville distribution method, the characteristic parameters were extracted for evaluation of depth of anesthesia in each anesthesia stage. The progress of general anesthesia was divided into the states of pre-operation, induction of anesthesia, operation, awaking and post-operation.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.55 no.1
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• pp.35-41
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• 2006

Although reachers have studied for a long time, they don't make criteria for anesthesia depth. anesthetists can't make a prediction about patient's reaction. Therefor, patients have potential risk such as poisonous side effect late-awake, early-awake and strain reaction. EEG are received from twenty-five patients who agreed to investigate themselves during operation with Enflurane-anesthesis in progress of anesthesia. EEG are divided pre-anesthesia, before incision of skin, operation 1, operation 2, awaking, post-anesthesia by anesthesia progress step. EEG is applied pre-processing, base line correct, linear detrend to get more reliable data. EEG data are handled by electronic processing and the EEG data are calculated by bicoherence. During pre-anesthesia and post anesthesia, appearance rate of bicoherence value is observed strong appearance rate in high frequency range($15\~30Hz$). During the anesthesia of patient, a strong appearance rate is revealed the low frequency area(0~10Hz). After bicoherence is calculated by percentage of a appearance rate, that is, Bicpara$\#$1, Bicpara$\#$2, Bicpara$\#$3 and Bicpara$\#$4 parameter are extracted. In result of bicoherence analysis, Bicpara$\#$2 and Bicpara#4 are considered that the best parameter showed progress of anesthesia effectively. And each separated bicoherence are calculated by average bicoherence's numerical value, divide by 2 area, appear by each BicHz$\#$1, BicHz$\#$2, and observed BicHz$\#$1/BicHz$\#$2's change. In result of bicoherence analysis, BicHz$\#$1, BicHz$\#$2 and BicHz$\#$1/BicHz$\#$2 are considered that the best parameter showed progress of anesthesia effectively. In conclusion, I confirmed the anesthesia progress phase, concluded to usefulness of parameter on bispectrum and bicoherence analysis and evaluated the depth of anesthesia. In the future, it is going to use for doctor's diagnosis and apply to protect an medical accident owing to anesthesia.

• Journal of Dental Anesthesia and Pain Medicine
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• v.18 no.4
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• pp.235-244
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• 2018

Background: Patients with intellectual disability (ID) often require general anesthesia during oral procedures. Anesthetic depth monitoring in these patients can be difficult due to their already altered mental state prior to anesthesia. In this study, the utility of electroencephalographic indexes to reflect anesthetic depth was evaluated in pediatric patients with ID. Methods: Seventeen patients (mean age, $9.6{\pm}2.9years$) scheduled for dental procedures were enrolled in this study. After anesthesia induction with propofol or sevoflurane, a bilateral sensor was placed on the patient's forehead and the bispectral index (BIS) was recorded. Anesthesia was maintained with sevoflurane, which was adjusted according to the clinical signs by an anesthesiologist blinded to the BIS value. The index performance was accessed by correlation (with the end-tidal sevoflurane [EtSevo] concentration) and prediction probability (with a clinical scale of anesthesia). The asymmetry of the electroencephalogram between the left and right sides was also analyzed. Results: The BIS had good correlation and prediction probabilities (above 0.5) in the majority of patients; however, BIS was not correlated with EtSevo or the clinical scale of anesthesia in patients with Lennox-Gastaut, West syndrome, cerebral palsy, and epilepsy. BIS showed better correlations than SEF95 and TP. No significant differences were observed between the left- and right-side indexes. Conclusion: BIS may be able to reflect sevoflurane anesthetic depth in patients with some types of ID; however, more research is required to better define the neurological conditions and/or degrees of disability that may allow anesthesiologists to use the BIS.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.9
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• pp.2460-2470
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• 2009

In this study, the parameter extraction for evaluation of the anesthesia depth in each anesthesia stages was conducted. An object of the this experiment study has studied 5 adult patients (mean $\pm$ SD age:$42{\pm}9.13$), ASA classification I and II, undergoing surgery of obstetrics and gynecology. Anaesthesia was maintained with Enflurane. HRV signal was created by R-peak detection algorithm form ECG signal. The HRV data were preprocessing algorithm. It has tried find out the anesthesia parameter which responds the anesthesia events and shows objective anesthesia depth according to anesthesia stage including pre-anesthesia, induction, maintenance, awake and post-anesthesia. In this study, proposed algorithm to analysis the HRV(heart rate variability) signal using wavelet transform in anesthesia stage. Three sorts of wavelet functions applied to PSD. In the result, all of the results were showed similarly. But experiment results of Daubeches 10 is better. Therefore, this parameter is the best parameter in the evaluation of anesthesia stage.

• Journal of Dental Anesthesia and Pain Medicine
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• v.16 no.3
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• pp.217-222
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• 2016

Dental treatment is often performed under general anesthesia or sedation when an intellectually disabled patient has a heightened fear of treatment or has difficulty cooperating. When it is impossible to control the patient due to the severity of intellectual disability, conscious sedation is not a viable option, and only deep sedation should be performed. Deep sedation is usually achieved by propofol infusion using the target controlled infusion (TCI) system, with deep sedation being achieved at a slightly lower concentration of propofol in disabled patients. In such cases, anesthesia depth monitoring using EEG, as with a Bispectral Index (BIS) monitor, can enable dental treatment under appropriate sedation depth. In the present case, we performed deep sedation for dental treatment on a 27-year-old female patient with mental retardation and severe dental phobia. During sedation, we used BIS and a newly developed Anesthetic Depth Monitor for Sedation (ADMS$^{TM}$), in addition to electrocardiography, pulse oximetry, blood pressure monitoring, and capnometry for patient safety. Oxygen was administered via nasal prong to prevent hypoxemia during sedation. The BIS and ADMS$^{TM}$ values were maintained at approximately 70, and dental treatment was successfully performed in approximately 30 min.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.7
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• pp.2491-2496
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• 2010

The DFA(detrended fluctuation analysis) which is included the correlation property of the EEG is used to analysis the depth of anesthesia. We studied ASA I or II adult patients supported by the society of anesthesiologists. Patients with history of dementia and neurological disorder are excluded. Average age is $48.9{\pm}10.9$ old, average weight is $57.1{\pm}8.2$ kg and average hight is $158{\pm}6.6$cm of the patients under the operation. Anesthesia medicine is Sevoflurane and the stages of anesthesia are 6 stages, that is pre-operation, induction, right after induction, stop the medicine and post-operation. Among the scaling exponent ${\alpha}1$, ${\alpha}2$, ${\alpha}3$ we know that ${\alpha}1$, ${\alpha}3$, were well appeared to discriminate pre-operation, induction, right after induction, stop the medicine and post-operation. So we confirmed that the parameters is useful to the depth of anesthesia.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.9
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• pp.2099-2104
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• 2010

In this paper, HRV signal which was appeared RR intervals from ECG was analyzed using return-map during anesthesia. We intended to estimate the depth of anesthesia observing the change of autonomic nervous activity(ANS) because HRV showed change of cardio-vascular system of the body according to state of ANS. Return-map analysis is to reconstruct time series of HRV to phase space after calculating delay time and embedded time. After approximating the signal distribution which was reconstructed in phase space in elliptic, we calculated the lengths of major and minor axises of the elliptic and the values was used to estimate the depth of anesthesia. Stages of the anesthesia were 7 levels to evaluate the depth of anesthesia. At induction stage of strong external stimulation, the length of major and minor axis were statistically high and at the operation stage of non-external stimulation, the values were statistically low. Conclusively, the stages of anesthesia were discriminated by HRV signal mapped in the phase space during operation.