Abstract: In this paper, algorithm estimating the blood pressure
was proposed using the pulse transit time (PTT) as a more convenient
method of measuring the blood pressure. After measuring ECG and
pressure pulse, and photoplethysmography, the PTT was calculated
from the acquired signals. Thereafter, the system to indirectly measure
the systolic pressure and the diastolic pressure was composed using
the statistic method. In comparison between the blood pressure
indirectly measured by proposed algorithm estimating the blood
pressure and real blood pressure measured by conventional
sphygmomanometer, the systolic pressure indicates the mean error of
±3.24mmHg and the standard deviation of 2.53mmHg, while the
diastolic pressure indicates the satisfactory result, that is, the mean
error of ±1.80mmHg and the standard deviation of 1.39mmHg. These
results are satisfied with the regulation of ANSI/AAMI for
certification of sphygmomanometer that real measurement error value
should be within the mean error of ±5mmHg and the standard
deviation of 8mmHg. These results are suggest the possibility of
applying to portable and long time blood pressure monitoring system
hereafter.
Abstract: The linear SEF (Spectral Edge Frequency) parameter
and spectrum analysis method can not reflect the non-linear of EEG.
This method can not contribute to acquire real time analysis and obtain
a high confidence in the clinic due to low discrimination. To solve the
problems, the development of a new index is carried out using the
bispectrum analyzing the EEG(electroencephalogram) including the
non-linear characteristic. After analyzing the bispectrum of the 2
dimension, the most significant power spectrum density peaks appeared abundantly at the specific area in awakening and anesthesia state. These points are utilized to create the new index since many
peaks appeared at the specific area in the frequency coordinate. The measured range of an index was 0-100. An index is 20-50 at an anesthesia, while the index is 90-60 at the awake. New index could afford to effectively discriminate the awake and anesthesia state.
Abstract: The measurement of anesthetic depth is necessary in
anesthesiology. NN10 is very simple method among the RR intervals
analysis methods. NN10 parameter means the numbers of above the 10
ms intervals of the normal to normal RR intervals.
Bispectrum analysis is defined as 2D FFT. EEG signal reflected the
non-linear peristalsis phenomena according to the change brain
function. After analyzing the bispectrum of the 2 dimension, the most
significant power spectrum density peaks appeared abundantly at the
specific area in awakening and anesthesia state. These points are
utilized to create the new index since many peaks appeared at the
specific area in the frequency coordinate. The measured range of an
index was 0-100. An index is 20-50 at an anesthesia, while the index is
90-60 at the awake.
In this paper, the relation between NN10 parameter using ECG and
bisepctrum index using EEG is observed to estimate the depth of
anesthesia during anesthesia and then we estimated the utility of the
anesthetic.