A Study on the Electroencephalographic Characteristics at Each Anesthetic Steps / 대한마취과학회지

BACKGROUND: Bispectrum and bicoherence analysis that is the frequency domain methods of EEG analysis was examined to elucidate the correlation with the depth of anesthesia. METHODS: 25 patients under the gynecological surgery were studied. EEG was surveyed by PhysioLab 400. Analysis of EEG was done according to the progress of anesthesia, normal state before anesthesia, before incision of skin, operation 1, operation 2, awake and post-anesthesia. EEG is applied to filtering of signal, base line correction, linear detrend removal to get more reliable analysis. The appearance rate of bispectrum peaks are calculated by bispectrum operation. And bicoherences are calculated by bispectrum and power spectrum of AR model. RESULTS: In awaking state of patient in pre-anesthesia and post anesthesia, appearance rate of bispectral coupling was observed that a strong appearance rate was represented in all area (0-35 Hz). During the anesthesia, the low frequency area (3-15 Hz) revealed a strong appearance. Also the 2D map of a appearance rate is divided into four sections for more objectivity. Of four sections Bipara#4 is considered that the best parameter which showed progress of anesthesia (P < 0.01). In bicoherence study, in awake state which patient is in pre-anesthesia and post anesthesia, appearance rate of bicoherence value was observed that a strong appearance rate was represented in high frequency range (15-30 Hz). However, under the anesthesia of patients, the low frequency area (0-10 Hz) revealed a strong appearance. And, of four sections Bicpara#2 and Bicpara#4 are considered that the best parameter which showed progress of anesthesia effectively (P < 0.01). CONCLUSIONS: The analysis of the peak appearance of bispectrum and bicoherence is useful monitoring for the depth of anesthesia.

TThe Evaluation of Anesthesia Depth Using Detrended Fluctuation Analysis Parameters / 대한마취과학회지

BACKGROUND: We examined the use of DFA-Detrended fluctuation analysis-of heart rate variability during general anesthesia in order to assess the depth of anesthesia. METHODS: In this study, we observed changes in alpha1, the short range scaling exponent, in alpha2, the long range scaling exponent, and in the alpha2/alpha 1 ratio during enflurane anesthesia. We monitored 7 stages during general anesthesia, i.e., 1) preoperation (awake state), 2) during induction, 3) after induction, 4) during maintenance, 5) before extubation, 6) after extubation, and 7) postoperation (Next day). RESULTS: The alpha 2/alpha 1 ratio increased during the induction and extubation state compared to preoperation (awake state). This may be related to increased sympathetic activity due to stimulation of the autonomic nervous system. In the postoperation (awakened state), the ratio returned to the preoperation value (awake state). These results are similar to low frequency (LF), high frequency (HF) and LF/HF ratio values which reflect activity of autonomic nervous system. CONCLUSIONS: Detrended fluctuation analysis parameters, especially the alpha 2/alpha 1 ratio, would be used for monitoring the depth of anesthesia. Also these parameters are useful indexes with the LF/HF ratio for the evaluation of sympathetic activity during general anesthesia.

Effects of Enflurane on Pulse Transit Time / 대한마취과학회지

BACKGROUND: In Anesthetic state, many hemodynamic parameters including blood pressure, heart rate and arterial compliance are changed. Moreover pulse transit time (PTT) is influenced by heart rate, blood pressure changes, and the compliance of the arteries. METHODS: In this study, we investigated PTT changes in patients under enflurane anesthesia. PTT of the finger was measured by photoplethysmography (PPG) and electrocardiography (ECG). PTT values were calculated as the time interval between the peak of the ECG R wave and the peak of the second derivatived of the PPG in the finger tip. RESULTS: ECG amplitude and heart rate increased reflecting hemodynamic chnages after enflurane anesthesia, and the PTT increased after enflurane anesthesia treatment by 16.68 ms (n = 24). Moreover, PTT was found to be inversely proportion to aging. CONCLUSIONS: The increase of PTT in the finger due to relaxation of the arterial wall muscle after enflurane anesthesia was used as an indicator of sympathetic block on muscle tone. This result suggests that PTT is strongly related with anesthetic state. And PTT may be one of useful surrogative methods for anesthetic monitoring, but PTT is unfortunately only qualitative.

The Study of EEG Spectrum Analysis as a Method of Monitoring the Depth of Anesthesia / 대한마취과학회지

BACKGROUND: Monitoring the "depth of anesthesia" is an ongoing problem. To identify a useful parameter for determining the depth of anesthesia with enflurane, EEG data was obtained using a Physiolab 800. METHODS: Variations in EEG signals were measured and analyzed by the stage of anesthesia. EEG data was obtained from 15 patients during general anesthesia with enflurane. The EEG signal was acquired and analyzed in 5 steps (one day before anesthesia, during induction, during skin incision, at end of anesthesia, and one day after anesthesia). Fp1 electrode and the EEG data mainly from the forehead were used to determine the depth of anesthesia using EEG characteristics during enflurane anesthesia. All data were preprocessed by filtering, baseline correction and using the linear detrend method to reliable analyze of sample data in the surgical environment. Data obtained were transformed to frequency and power spectrum analysis was performed. RESULTS: alpha, beta, delta and theta waves were detected by frequency area separation and the trend of each wave was observed during each anesthesia stage. EEG data was slowed down and the theta wave ratio increased as the depth of anesthesia increased. Accordingly, spectral edge frequency (SEF) and median frequency (MF) were used as parameters to determine the depth of anesthesia. The frequencies of SEF and MF decreased during anesthesia and returned to the preanesthetic level after the cessation of anesthesia. CONCLUSIONS: Our results suggest that SEF and MF can contribute as useful parameters to determine the depth of anesthesia. Anesthetics not only affect the central nervous system, but also affect the autonomic nervous system. If the autonomic nervous system signals such as heart rate variability are taken into account, more reliable evaluations would be possible.

Monitoring System during Enflurane Anesthesia Using Heart Rate Variability / 대한마취과학회지

BACKGROUND:We performed spectral analysis and determined the 1/f noise of heart rate variability during enflurane anaesthesia in order to assess the effect of the activity of the autonomic nervous system. METHODS: Data were acquired from 15 patients (ASA I-II) who received gynecological surgery under general anesthesia using enflurane, nitrous oxide and oxygen. We analyzed the spectral components of heart rate variability (HRV) according to the following five periods: 1) before premedication, 2) after induction, 3) during skin incision, 4) during recovery, and 5) after surgery. For each power spectrum the density and frequency components were identified as follows: (1) low frequency (LF) component (0.04-0.15 Hz) was associated with parasympathetic and sympathetic tone, and was affected by body temperature, the renin-angiotensin system, baroreceptor and vasomotor sympathetic modulation, (2) high frequency (HF) component (0.15-0.5 Hz) was mediated parasympathetic tone and reflected the mechanical influence of the ventilation. In addition the LF/HF ratio, which reflected cardiac sympathovagal balance was monitored. RESULTS: The LF/HF ratio, which reflects the balance of the autonomic nervous system increased remarkably during skin incision and recovery. Also, the beta index, which is related to body activity decreased during skin incision and recovery. CONCLUSIONS: Increased LF/HF was found to be caused by mechanical stimulation, which reflects autonomic nervous system balance, and the beta index was useful for the assessment of body activity.