TWI507174B - Method of detecting blood loss in operation by pulse wave transmission time - Google Patents

Description

Method for detecting blood loss during surgery by pulse wave transit time

The invention relates to a method for detecting blood loss during operation by pulse wave transit time, in particular to a pulse wave transmission time required for blood to flow from the heart to the finger by a basic physiological signal monitoring instrument for providing A method by which a physician can more accurately understand the condition of a patient during surgery.

In the medical process, it is important to ensure patient safety during surgery and to reduce surgical disability and mortality, and to maintain blood circulation stability. However, even under the supervision of medical personnel, unpredictable complications such as bleeding may still occur. The impact of blood loss on the patient depends on the amount of blood loss and how early it is detected. Serious bleeding, if not identified, can lead to misfortune. Early detection of blood loss during surgery is sometimes not easy, especially when the bleeding is not obvious. Traditional signs of life such as heartbeat and blood pressure are not sensitive to the detection of mild and moderate blood loss. Traditional standard blood circulation monitoring includes blood pressure and electrocardiogram (ECG). These monitoring methods are non-invasive, but they are not sensitive to blood loss monitoring. Immediate artery Methods of monitoring blood circulation that are sensitive to blood loss, such as catheterization and central venous catheterization, are invasive and may cause damage.

Several recent studies have found a non-invasive and reliable method for pulse blood oxygen concentration waveforms and electrocardiograms derived from light volume change maps, called pulse wave transit times, to identify changes in blood volume in awake healthy individuals. The pulse transit time is the time interval between the R wave of the electrocardiogram and the peripheral (eg, fingertip) in the same cardiac cycle. The pulse transit time was introduced in the 1950s to explore physiological and psychological studies on anxiety and stress. Since the 1990s, it has been used to measure sympathetic activation during upper airway obstruction during sleep. The practice of monitoring pulse transit time during systemic or local anesthesia is quite novel. Some studies conducted during general anesthesia indicate that pulse wave transit time varies with depth of anesthesia, but other studies conducted during systemic and spinal anesthesia have shown that pulse wave transit time reflects autonomic nervous tension and can therefore be used as An alternative indicator of arterial blood pressure.

In addition, pulse transit time can identify early low blood volume capabilities for clinical practice, especially for those cases that cannot easily identify occult bleeding in the body cavity at an early stage, with potentially significant benefits. Delayed control of abnormalities, pelvic or intrathoracic hemorrhage has been identified as a major contributor to the prevention of traumatic death, often due to delayed assessment of bleeding and delayed diagnosis. It is obviously helpful if such incidents can be detected as quickly as possible based on the information available to the current patient monitoring device. In view of this, the applicant has been researching and experimenting, and Meng Mengsheng has designed a method to detect blood loss during operation by pulse wave transit time, so that the doctor can more accurately understand the patient's condition during the operation.

The main object of the present invention is to provide a method for detecting blood loss during surgery by pulse wave transit time, which is to establish a pulse transit time required for blood to flow from the heart to the finger by a basic physiological signal monitoring instrument. For the doctor to understand the patient's condition more accurately during the operation.

The aforementioned method for detecting blood loss during surgery by pulse wave transit time is to establish a pulse transit time required for blood to flow from the heart to the finger by using a basic physiological signal monitoring instrument. The steps are mainly to capture the electrocardiogram (ECG) and photoplethysmographic (PPG) curves of the patient from the physiological signal monitoring instrument, so as to find each highest point in the ECG curve, and find out the need through two layers of filtering. The value of each, and then find the highest point in the curve of the light volume change curve, calculate the value of the pulse wave transit time, and present it as a pattern, and then filter the noise through two layers of filtering, so that the pattern can be better presented. The curve is for analysis and interpretation, so that the doctor can more accurately understand the patient's condition during the operation.

The pulse wave transit time measured by the interval between the R wave and the pulse volume change of the electrocardiogram signal showing the action potential rise (upstroke) has recently been used to evaluate the cardiovascular response of anesthesia and intubation. The R wave of the electrocardiogram signal is often used as an approximate time point because it is easy to detect and allow motion artifacts. Both electrocardiograms and pulse waves are available from standard monitoring devices. Each measurement of the pulse transit time is obtained in a non-invasive manner. The original concept of pulse transit time is to measure the time interval of the arterial pulse between the lengths of the vessel paths from two selected locations. However, for ease of measurement, the R wave of the electrocardiogram is used as a starting point because it roughly corresponds to the opening of the valve. Advances in technology have made it possible to use light volumetric changes to correctly estimate whether a pulse wave has reached a surrounding location such as a finger or toe.

Using the induction of the electrocardiogram, it is easy to make various pulse transit time measurements that can be replicated by the finger light volume change method. The derivation of SpO2 is based on a peripheral volume pulse waveform called the pulse blood oxygen concentration waveform of the light volume change map, but its clinical significance has not been taken seriously. The possibility of using a finger light volume change map and an electrocardiogram to monitor the central blood volume has been confirmed by the experimenter. This is the difference in time. For a pulse wave as shown in the first figure, the pulse wave transit time is the time required for blood to flow from the heart (ECG) to the light volume change map sensor. The unit used to describe the pulse transit time is seconds.

In order to calculate the pulse transit time, we must first check the consistency of the sampling time. This means that the sampling time of the data of the electrocardiogram and the light volume change map should be checked. If it is not similar, the program will stop immediately. The pulse transit time is the time during which the arterial pulse wave is transmitted between the two arterial sites. The pulse transit time provides beat-to-beat vascular information. Each vascular pulse begins with each contraction of the heart, and ends with a pulse wave that reaches the distal branch of the blood vessel. The start time can be easily obtained from the R wave of the electrocardiogram. The termination time can be obtained from the waveform of the pulse wave volume change map transmitted to the finger. The difference between these two points in time is the pulse transit time. The pulse transit time measured by the R wave and the light volume change map has been used in several studies. Since the electrocardiogram and the pulse wave plethysmogram are inevitable users during various anesthesia, the pulse wave transit time can be conveniently obtained from the electrocardiogram and the pulse wave volume change map. Through these studies, we can use this formula to find the value of the pulse transit time. Later, we began to calculate the highest points of the ECG. In order to obtain each of the highest points of the ECG curve, we use a function that finds each of the highest peaks, called the finite difference method. In this way, we can find each of the highest peaks we want in all the curves. Although all the highest peaks of the ECG have been obtained, it is still necessary to check again whether Some noise peaks. For this type of noise peak, we use a period threshold filter and an amplitude threshold filter. The threshold filter is used to check whether the value obtained in the previous step is higher than 300ms or lower than 1500ms, that is, close to the range of human heartbeat. Therefore, if the period between two values is lower or higher, the program deletes the lowest or highest value based on the amplitude. The amplitude threshold filter removes each value that is too low or high compared to the mean of the first 100 values. Due to that filter, the software only retains the highest or lowest value. From this step, all the ECG peaks that pass through the filter can be calculated, which is what we need. Thereafter, we continue to find the highest point of the light volume change map. By using the electrocardiogram and the position of the light volume change map, the value of the pulse wave transit time can be obtained by using the previous formula. The value of the pulse transit time also needs to be filtered in order to obtain a better pulse transit time curve. Finally, the patient's information can be used to begin analyzing the pulse transit time. Based on a specific stage, we want to calculate the pulse transit time during the procedure. The second figure shows the flow chart of the present invention. In this flow chart, it can be seen how easy it is to calculate the pulse transit time. among them:

Step 1: The consistency of the sampling time, whether the sampling time of the soft core check ECG is similar to the data of the light volume change map. If it is not similar, the program will stop immediately.

Step 2: Find the function of each highest point of the ECG. In order to obtain each highest point of the ECG curve, we use a function that can find each highest peak, called the finite difference method. In this way, we can find each of the highest peaks we want in all the curves.

Step 3: During the period, the threshold filter checks whether the value obtained in the previous step is higher than 300ms. Or less than 1500ms, which is close to the range of human heartbeat. Therefore, if the period between two values is lower or higher, the program deletes the lowest or highest value based on the amplitude.

Step 4: The amplitude threshold filter is compared to the mean of the first 100 values, and the program deletes each value that is too low or high. Due to that filter, the software only retains the highest or lowest value.

Step 5: The highest point method of the light volume change map. Within the interval between the two peaks of the ECG, the program records the highest point of the curve of the light volume change curve from a function called "max" in Matlab.

Step 6: After the window size filter is initially viewed, the pulse transit time values above or below the threshold are deleted according to the threshold determined by the software user. If the value of a pulse transit time is out of range, the previous value is used.

Step 7: Calculating the pulse wave transit time start time can be easily obtained by the R wave of the electrocardiogram. The termination time can be obtained from the waveform of the pulse wave volume change map transmitted to the finger. The difference between these two points in time is the pulse transit time. Its formula is:

Step 8: The third plot shows the original curve of the pulse transit time. The data is smoothed by a median filter to produce an improved pulse transit time curve (as in the fourth figure).

Step 9: Analyze the pulse transit time. The program links the pulse transit time curve based on the following volunteer/patient information.

The present invention is a further experiment for collecting data of 25 control patients and 5 experimental patients. At the hospital we used AS/5 and laptop to collect patient information. The AS/5 is a multi-functional physiological monitor that instantly measures physiological signals such as BP, ECG, respiration and SpO _{2 in} patients. Our experiment was to collect the patient's physiological signals with AS/5 during the operation and store the data in the notebook with RS232 transmission line.

Regarding the control group, we collected patient data from urological surgery. The age of the patients participating in the study was 15 to 65 years old. All patients underwent general anesthesia. As a control experiment, patient data was collected prior to the start of surgery. During the operation, there are three specific stages that must be recorded, including anesthesia time (I), start of surgery (II), and end of surgery (III).

In the experimental group, we want to understand the changes in the trend of pulse wave transit time when the patient loses blood and hydrates. In this case, because the patient must have blood loss and hydration before the heart surgery, this surgery was chosen to experiment. In order to determine the state of the patient during the experiment, the process is divided into three stages, namely the one shown in the left half of the fifth figure, based on the process of grabbing data from the thoracotomy. These three phases (rectangles) include preoperative preparation, experimentation, and surgery, while the transition between adjacent two phases (arrows) is induced. The right half of the fifth graph shows that the experiment begins after induction. In the first sub-phase, the patient suddenly loses blood and then performs a hydration action in the second sub-phase.

The results of the 25 patients in the control group showed pulse wave transmission during urological surgery time. In this operation, the patient has no blood loss and hydration. As shown in Table 1, the average pulse wave transit time before surgery begins is 0.3470 ± 0.0412 s, and during surgery, it is about 0.2463 ± 0.0271 s. We can observe that blood flow during surgery is faster than before surgery (see Figure 6). We compared the two samples by statistical analysis and found that P < 0.0001, indicating that there is a significant difference between the two samples. According to the anesthesiologist's clinical experience, they will first inject a quick-acting anesthetic called propofol (propofol), but this anesthetic will make the patient feel pain. Therefore, the anesthesiologist will always inject another painkiller called alfentanil. This medicine may accelerate the heart and cause an increase in blood flow.

The results of this experiment show changes in pulse transit time during a later phase and two sub-phases: initiation of anesthesia (stage 1), loss of blood (sub-stage 1), and hydration (sub-phase 2). The seventh figure shows the trend of pulse wave transit time. As shown in Table 2, the mean PTT during the initial anesthesia was 0.2895±0.0261s, the period of blood loss was about 0.3148±0.0212s, and the period of hydration was 0.2792±0.00126s. We used statistical analysis to compare these three stages, and we can observe that the first and second stages are P < 0.05. In addition, the second and third stages were also P < 0.05. This result indicates a significant difference between the three phases. We can see that Phase II has the highest pulse transit time, indicating that the patient has the lowest blood flow during blood loss. During this time, the patient will suddenly lose a lot of blood. When this happens, the heart can't stand it, so it can slow the blood flow to balance. When it becomes stage III, the pulse wave transit time is the lowest, indicating that the patient has the fastest blood flow during the hydration process. According to the anesthesiologist's clinical experience, the blood concentration will be diluted during the hydration process. That is why the pulse transit time becomes lower during the hydration period.

The present invention collects some patient data from urological surgery and cardiac surgery. We divide these materials into two groups. One group was treated as a control group with normal procedures, that is, no dangerous steps such as blood loss. The other group was treated as a trial group with special procedures, that is, dangerous steps such as blood loss and hydration during surgery. By comparing the two experiments, the control and the experimental group can be compared. From the results of the control group, the trend of pulse wave transit time is from high to low, which means that the blood flow rate is slow to fast during normal surgery as shown in FIG. In the experimental group, it can be seen that in the case of blood loss and hydration in the operation, the value of the pulse wave transit time is as shown in the ninth figure, first becoming high during blood loss, and then decreasing during hydration.

The foregoing embodiments are merely illustrative of the preferred embodiments of the present invention, and are not intended to limit the scope of the invention.

In summary, the present invention uses a pulse wave transit time to detect blood loss during surgery, and uses a basic physiological signal monitoring instrument to establish a pulse wave transit time required for blood to flow from the heart to the finger for the physician. A more accurate understanding of the patient's condition during surgery. For a practical design, it is a novelty creation. If you apply for a patent in accordance with the law, you will be punished by the Bureau of Public Information, and you will be granted a patent as soon as possible.

The first picture is a pulse wave transit time definition map.

The second drawing is a flow chart of the present invention.

The third graph is the original curve of the pulse wave transit time of the present invention.

The fourth figure is a graph of the pulse wave transit time after smoothing of the present invention.

The fifth figure is a flow chart of the experimental method including the three stages and two sub-stages of the process of grasping data during surgery.

The sixth graph is a pulse transit time diagram during urological surgery of the present invention.

The seventh panel is a pulse transit time diagram during cardiac surgery of the present invention.

The eighth figure is a two-stage diagram in the control experiment of the present invention.

The ninth diagram is a three-stage diagram of the experimental group experiment of the present invention.

Table 1 shows the pulse wave transit time and heart rate statistics in Experiment I of the present invention.

Table 2 shows the pulse wave transit time statistics of Experiment II of the present invention.

Claims (2)

A method for detecting blood loss during surgery by pulse wave transit time is to establish a pulse wave transmission time required for blood to flow from the heart to the finger by using a basic physiological signal monitoring instrument, and the steps are mainly monitoring from the main signal. Simultaneously grab the patient's electrocardiogram (ECG) and photoplethysmographic (PPG) curves to find the highest point in the ECG curve. After two layers of filtering, find the required value and find the light volume. At each of the highest points in the variation map (PPG) curve, the value of the pulse transit time (PTT) is calculated and presented as a pattern, and the noise is filtered through two layers of filtering to make the pattern exhibit a better curve. For analysis and interpretation, the doctor can more accurately understand the patient's condition during the operation; the following steps are included: a: consistency of sampling time, whether the sampling time of the soft body check electrocardiogram and the light volume change map are Similarly, if not similar, the program will stop immediately; b: find the function of each highest point of the ECG, in order to obtain each highest point of the ECG curve, the present invention uses the species to find each The highest peak, called the function of the finite difference method, in which the highest peak we want can be found in all curves; c: the threshold filter checks whether the value obtained in the previous step is higher than 300ms or less, which is close to the range of human heartbeat, so if the period between two values is lower or higher, the program deletes the lowest or high value according to the amplitude; d: amplitude threshold filter, and For the mean comparison of the first 100 values, the program will delete each value that is too low or high, leaving only the highest or lowest value; e: within the interval between the two peaks, the program will be called "max" from Matlab. Function to record the highest point of the PPG curve; f: Calculate the pulse wave transit time, the start time can be easily obtained by the R wave of the electrocardiogram, and the end time can be obtained by the pulse wave volume change map waveform transmitted to the finger. The difference between the two time points is the pulse wave transit time; g: After the window size filter is initially viewed, the pulse wave transit time values above or below the threshold are deleted according to the threshold determined by the software user. If the pulse transit time value is out of range , that is, the previous value is used; h: the data is smoothed by the median filter to prepare an improved pulse transit time curve; i: the pulse transit time program is analyzed, and the pulse wave is connected according to the volunteer/patient information. Pass the time curve. The method for detecting blood loss during surgery by pulse wave transit time as described in claim 1 is further provided with a period threshold filter and an amplitude threshold filter. To filter out the noise of the ECG.