CN112006659A - Anesthesia state monitoring method and device - Google Patents
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Abstract
The invention discloses a method and a device for monitoring an anesthesia state, which relate to the field of anesthesia monitoring and comprise the following steps: a signal acquisition step: acquiring a heartbeat signal and a respiration signal; and (3) analyzing and processing steps: obtaining a cardiopulmonary index and a nociceptive index by processing the heartbeat signal and the respiratory signal; and a result evaluation step: the anesthetic state is determined based on the cardiopulmonary index and the nociceptive index. The anesthesia state monitoring method and device provided by the invention can realize simultaneous monitoring of comprehensive anesthesia depth, realize identification of variation of sedation degree and analgesia degree, meet the requirement of clinical anesthesia, provide reference for anesthesia administration infusion, further provide the most suitable anesthesia state for anesthesia patients and avoid over-deep or over-shallow anesthesia.
Description
Technical Field
The invention relates to the field of anesthesia monitoring, in particular to an anesthesia state monitoring method and device.
Background
General anesthesia means that a patient temporarily loses the feeling of the whole body by using a medicine or other methods so as to achieve the purpose of painless operation treatment, and the general anesthesia is realized by the following requirements: loss of consciousness (sedation) of the patient; pain relief (analgesia); resulting in immobility (muscle relaxation); and elimination of unwanted reflexes such as pharyngeal spasms and arrhythmias (reflex suppression). According to clinical statistics, only about two-thirds of patients receive quality anesthesia service, with about 14% of patients being over-anesthetized, 16% being over-anesthetized, and 10% being under-anesthetized. When the sedation and anesthesia is too deep, the excessive medicine can cause the respiration to slow down, even the respiration stops, and the brain is anoxic, thereby causing the danger of the cardiac arrest of the patient; if the anesthesia is too shallow, the patient can know the anesthesia in the operation, and the patient can have memory or even feel pain in the operation. However, it is difficult to satisfy all of the above conditions using a single anesthetic, and furthermore, it is necessary to adjust the dose, administer sedatives, analgesics, muscle relaxants, etc., depending on the kind of operation and each patient, and this method is called "balanced anesthesia".
Currently, anesthesia research centers in the clinic have the most monitoring studies on sedation, with control of different anesthesia depths being most common intraoperatively guided by BIS monitoring. In the aspect of muscle relaxation monitoring, the blocking degree and the recovery condition of the body neuromuscular transmission function after the muscle relaxation medicine is applied are known through related muscle relaxation monitoring equipment, and the safety and the rationality of the clinical application of the muscle relaxation medicine are improved. In the aspect of analgesia, the indicators concerned by the anesthesiologist include the heart rate, the mean arterial blood pressure (MAP) and other conventional physiological parameters, but the indicators are mainly judged by the long-term clinical experience of the anesthesiologist, and no objective indicator exists. In recent years, researchers have proposed an injury irritation index (ANI) for determining the degree of analgesia in anesthesia, but clinical studies on ANI are still in the early stage, and there are few reports on related documents, and clinical studies on the relationship between ANI and chronic pain are lacking.
Disclosure of Invention
In order to solve the above problems, the present invention provides an anesthesia state monitoring method and apparatus, which are characterized in that not only can the comprehensive judgment of the anesthesia state be realized, but also the change of the sedation degree can be monitored.
The invention provides an anesthesia state monitoring method, which comprises the following steps:
a signal acquisition step: acquiring a heartbeat signal and a respiration signal;
and (3) analyzing and processing steps: obtaining a cardiopulmonary index and a nociceptive index by processing the heartbeat signal and the respiratory signal;
and a result evaluation step: the anesthetic state is determined based on the cardiopulmonary index and the nociceptive index.
Further, in the signal acquisition step, any one of the following modes is adopted for acquiring the heartbeat signal and the respiration signal: firstly, acquiring a heartbeat signal and a thoracic impedance signal simultaneously by using an electrode, and extracting a respiratory signal from the thoracic impedance signal; secondly, directly acquiring a heartbeat signal by using an electrode, and deriving an ECG-Derivedresipation (EDR) signal from the heartbeat signal; thirdly, collecting thoracic impedance signals, and extracting respiratory signals and heartbeat signals from the thoracic impedance signals.
Further, in the analyzing and processing step, R-waves are detected from the heartbeat signals collected in the signal collecting step, and a cardiac cycle, that is, an RR sequence, is calculated therefrom. The nociceptive index is then obtained by calculating the area under the curve formed by the RR sequence and then by calculating the area under the curve. The resulting nociceptive index allows an assessment of parasympathetic tone, which is used to characterize the degree of analgesia.
Furthermore, the signal acquisition step further comprises denoising processing for filtering interference signals in the acquisition process.
Further, the cardiopulmonary index is obtained by performing similarity analysis on the heartbeat signal and the respiratory signal, and the similarity degree of the heartbeat signal and the respiratory signal in the time domain or the frequency domain or the time-frequency domain is evaluated by performing similarity analysis on the heartbeat signal and the respiratory signal.
Further, the evaluation of the anesthesia status in the result evaluation step includes: and calculating and outputting the anesthesia index by combining the cardiopulmonary index and the nociceptive index, wherein the smaller the anesthesia index is, the deeper the anesthesia index is.
Further, the step of evaluating the result further comprises: comparing the cardiopulmonary index and the nociceptive index obtained at the moment with the values obtained at the last moment respectively and outputting variation values.
Further, the varying values of the cardiopulmonary index and the nociceptive index identify changes in the level of sedation and analgesia.
The anesthesia state monitoring device comprises a signal acquisition unit for acquiring a respiratory signal and a heartbeat signal, a first analysis unit for processing an injury stimulation index, a second analysis unit for processing a cardiopulmonary index and a result evaluation unit for evaluating and obtaining a final anesthesia depth according to data processed by the first analysis unit and the second analysis unit.
By adopting the anesthesia state monitoring method and device provided by the invention, the comprehensive anesthesia depth can be monitored simultaneously, the identification of the variation of the sedation degree and the analgesia degree is realized, the requirement of clinical anesthesia is met, a reference can be provided for the infusion of anesthesia administration, the most suitable anesthesia state is further provided for an anesthesia patient, and over-deep or over-shallow anesthesia is avoided.
Drawings
FIG. 1 is a block diagram of an anesthesia status monitoring device according to the present invention;
FIG. 2 illustrates a result output interface according to an embodiment of the present invention;
FIG. 3 illustrates a result output interface according to an embodiment of the present invention;
FIG. 4 illustrates a result output interface according to an embodiment of the present invention;
FIG. 5 illustrates a result output interface according to an embodiment of the present invention;
FIG. 6 is a graph of raw thoracic impedance signals collected in an embodiment of the present invention;
FIG. 7 is a graph of normalized thoracic impedance signals;
fig. 8 is an electrocardiogram corresponding to fig. 7.
Detailed Description
The embodiment provides a monitoring device for estimating the depth of anesthesia, and the structural block diagram is shown in fig. 1. The signal acquisition module of the monitoring device is divided into a respiratory signal acquisition unit and a heartbeat signal acquisition unit.
Signal acquisition: in this embodiment, the signal collecting unit 10 may also include a plurality of electrodes for collecting thoracic impedance signals, and the electrodes are attached to the main trunk portion for signal collection, for example, 2 electrode pads are attached to the chest of the tester, one electrode pad is attached to the apex of the left chest, and the other electrode pad is attached to the right chest, and then the respiratory signal is obtained from the collected thoracic impedance signals.
The heartbeat signal is obtained by preprocessing the acquired thoracic impedance signal, such as noise removal, normalization and the like; then, dividing the thoracic impedance signal obtained in step S1 into a plurality of signal segments according to 0.8S (in other embodiments, any time period between 0.4 and 2S may be used) as a time window, then performing forward difference operation on each signal segment by segment to obtain a difference array, determining a position where the thoracic impedance signal with the minimum difference array value is located in each signal segment (in other embodiments, a backward array may also be used, and the maximum difference array value is used as a center), and finding a peak forward and backward respectively with 0.05S as a time window, where the peak is used to represent a heartbeat.
In this embodiment, fig. 6 is an example of the acquired original thoracic impedance signal, and fig. 7 can be obtained after identification, denoising and normalization, as shown in fig. 7, a thoracic impedance signal graph selected in this embodiment is obtained, a range of the heartbeat signal in fig. 7 is marked, a peak of the heartbeat signal is determined, and by comparing with the R wave in the heartbeat signal of fig. 8, it can be found that the peak of the heartbeat signal identified in this embodiment and the peak of the R wave (fig. 8) are substantially overlapped.
In other embodiments, the signal collecting unit 10 may include a plurality of electrodes, and the direct collection of the heartbeat signal and the thoracic impedance signal is performed through the electrodes, and the respiratory signal is extracted from the thoracic impedance signal.
In other embodiments, the signal acquisition unit 10 may also be one or more electrodes that only acquire heartbeat signals, and then derive the respiration signal (ECG-respiratory rate, EDR) from the heartbeat signals.
The signal acquisition units 10 are all provided with a denoising module for filtering interference signals, which include physiological interference signals such as myoelectric signals and interference signals caused by non-physiological factors.
And (3) analyzing and processing steps: the first analysis unit 21 starts to analyze the nociceptive stimulation index after receiving the heartbeat signal, detects an R wave from the heartbeat signal collected in the signal collection step, and calculates a cardiac cycle, that is, an RR sequence. Parasympathetic tone was then assessed by calculating the area under the curve (AUC) formed by the RR sequences, and by calculating the nociceptive index (ANI) from the AUC. Where ANI is 100 × [ α × [ AUC min + β ]/12.8, the proportion of the area of the obtained ANI value expression performance to the entire sampling window area was calculated. The value range of ANI is 0-100, and the larger the ANI value is, the lower the pain degree is, and analgesia is not needed; smaller ANI indicates more intense pain and requires analgesia.
The second analysis unit 22 performs similarity analysis on the received heartbeat signal and the received respiration signal, and performs analysis to obtain the cardiopulmonary index. In the embodiment, the similarity analysis is completed by adopting a wavelet coherence function, and a coherence coefficient for representing the similarity is calculated. In other embodiments, the similarity analysis for the heartbeat signal and the respiration signal can also be performed by identifying the degree of similarity of the characteristic frequencies in the frequency domain, or by a cross-correlation function in the time domain.
Specifically, in the present embodiment, since the respiration signal and the heartbeat signal directly acquired are discrete time series, the respiration and heartbeat signals in the time domain are first transformed into frequency domain signals by wavelet transform, and only the real part of the wavelet transform is considered in the present embodiment. Then, the respiratory signal and the heartbeat signal are subjected to coherence analysis in a time-frequency domain. The coherence analysis is calculated as shown in equation (r):
where T is the respiration signal, C is the heartbeat signal, WCT(t，f)2Wavelet cross-power spectra, W, for the heartbeat signal C and the respiration signal TCC(t, f) and WTT(T, f) wavelet self-power spectra of the heartbeat signal C and the respiration signal T, respectively, Co (T, f)2Is the coherence factor. In this embodiment, the similarity may be characterized by a coherence coefficient.
The cardiopulmonary index is positively correlated with the similarity obtained, and the value range is 0 to 100. In this embodiment, the cardiopulmonary index is obtained by similarity segmentation normalization, for example, the data with a coherence coefficient ranging from 0 to 0.03 is normalized to a [0,20] interval, which represents that the cardiopulmonary index ranges from 0 to 20. Other specific numerical range treatments are not disclosed. When the cardiopulmonary index is changed from small to large, the anesthesia degree of the patient is increased; when the cardiopulmonary index is decreased, it indicates that the patient's level of anesthesia is decreased. In this embodiment, the window duration is 30 seconds, i.e. a cardiothoracic result is calculated according to the heartbeat signal and the respiration signal of 30 seconds.
The result evaluation unit 30 determines the anesthesia state including the judgment of the sedation level and the analgesia level based on the index of the noxious stimulus index obtained by the first analysis unit 21 and the index of the heart and lung obtained by the second analysis unit 22, and outputs the judgment result.
The following steps are included in the result evaluation unit 30:
(1) and (3) giving an anesthesia index by combining the nociceptive index and the cardiopulmonary index, evaluating the depth of anesthesia, and outputting a result by taking 30 seconds as a unit, wherein the larger the anesthesia index is, the deeper the depth of anesthesia is, and the corresponding state of specific numerical values is shown in table 1. For example, an increase in the index of anesthesia from 10 to 60 means that the subject goes from awake to deep anesthesia after administration of the anesthetic. In other embodiments, the index of anesthesia may be calculated by multiplying the index of cardiopulmonary index and the index of nociceptive activity by different coefficients.
TABLE 1 anesthesia index and anesthesia depth status corresponding table
| Range of index of |
0～10 | 10～40 | 40～70 | 70～100 |
| State of depth of anesthesia | Sobering up | Superficial anesthesia | Deep anesthesia | Over-anaesthesia |
(2) Comparing changes in the cardiopulmonary index and the nociceptive index: comparing the obtained cardiopulmonary index and the injury stimulation index with the values obtained at the last moment respectively and outputting variation values.
(3) And (3) determining the change of the sedation degree and the change of the analgesia degree according to the change value of (2). When the change of the cardiopulmonary index is consistent with the change of the nociceptive index, the result evaluation unit judges that the degree of analgesia is changed; when the cardiopulmonary index and the nociceptive index are changed inconsistently, the change of the sedation and analgesia degree is identified according to the change value of the index, wherein the change of the analgesia degree is judged from the change value of the nociceptive index, the change of the sedation degree is judged from the difference value of the cardiopulmonary index and the nociceptive index, and the intensity of the surgical stimulation at the moment can be further represented by the difference value. In the embodiment, whether the change is consistent or not is judged by setting a threshold of the difference value of the two change values, the threshold is set as '30', and when the difference value of the two change values is within '30', the cardiopulmonary index and the noxious stimulus index are considered to be consistent; when the difference between the two changes is larger than 30%, the cardiopulmonary index and the nociceptive index are considered to have changed in a inconsistent way. Furthermore, the result evaluation unit only identifies changes in the degree of sedation and analgesia if the absolute magnitude of the change in the index exceeds the value of "15".
Fig. 2 is an output interface of the result evaluation unit 30 during the anesthesia induction phase, and the content of the output interface includes the anesthesia index at this moment and the anesthesia index at the previous moment, which is 30 seconds before the previous moment in this embodiment; change values of cardiopulmonary index, nociceptive index; changes in sedation (Sed) analgesia (Ana) at this time and a profile of anesthesia index for approximately 20 minutes. Wherein the t, the t-1, the t-2 and the t-3 respectively correspond to the moment, the first 30 seconds, the first 60 seconds and the first 90 seconds; "+", "-" represent the increase, decrease of the index, respectively; the arrow points upwards to increase sedation or analgesia, the arrow points downwards to decrease sedation or analgesia, and the horizontal arrow points to no change in sedation or analgesia. The index of anesthesia at this point is "28", and the index of anesthesia at t-1, i.e., 30 seconds ago, is "6" in the state of anesthesia from waking to superficial anesthesia. The change values of the cardiopulmonary index and the nociceptive index at the current time t are "+ 20", "+ 17", respectively, and t-1, t-2, and t-3 are not recorded. Because the difference value of the change values of the cardiopulmonary index and the electroencephalogram index is less than 30, the cardiopulmonary index and the electroencephalogram index are changed consistently, and the change value of the index of the cardiopulmonary index and the electroencephalogram index exceeds 15, the analgesia degree is judged to be increased, and the sedation degree is unchanged.
As shown in fig. 3, this moment is an interface schematic diagram of the result output unit 30 during the second skin incision under anesthesia, at this moment, the change value of the nociceptive index is "+ 4", while the change value of the cardiopulmonary index is "-28", the difference between the two change values is 32 larger than 30, and the changes are inconsistent; and only if the change value of the cardiopulmonary index exceeds 15, the anesthesia index is changed from 64 at the previous moment (t-1) to 36 at the current moment (t), which shows that the sedation degree is reduced, the analgesia degree is changed step by step, and the anesthesia depth is reduced due to the sedation change, so that the anaesthetist can add sedation drugs according to the condition. At the previous time t-1, t-2 and t-3, the index is basically unchanged, and the anesthesia is maintained in a stable state. The change of the anesthesia index before and after the first skin-cutting time can be observed from the curve window, the inverted triangle index shows that the change of the anesthesia index is caused by the change of analgesia, and the change of the curve at other moments is caused by the change of sedation. In this example, no sedative was administered after the first skin incision, and a sedative was added immediately after the second skin incision.
Fig. 4 shows the output interface of the third skin incision, the anesthesia index is not changed basically, the change values of the cardiopulmonary index and the nociceptive index are both less than 15, so that the analgesia and the sedation degree are not changed although the subject experiences skin incision at the moment, which indicates that the previous analgesia level is sufficient and no additional medicine is needed.
Fig. 5 shows the result output interface at the moment when the anaesthetized patient is woken up by tapping. The anesthesia index profile decreased from 32 to 8 at the previous time, indicating that the anesthesia changed from light anesthesia to wakefulness. The nociceptive index is consistent with changes in the cardiopulmonary index, thus indicating a decrease in sedation and a return of consciousness in the patient.
While the invention has been specifically described above in connection with the drawings and examples, it will be understood that the above description is not intended to limit the invention in any way. Those skilled in the art can make modifications and variations to the present invention as needed without departing from the true spirit and scope of the invention, and such modifications and variations are within the scope of the invention.
Claims (9)
1. An anesthesia state monitoring method is characterized by comprising the following steps:
a signal acquisition step: acquiring a heartbeat signal and a respiration signal;
and (3) analyzing and processing steps: obtaining a cardiopulmonary index and a nociceptive index by analyzing the heartbeat signal and the respiratory signal;
and a result evaluation step: the anesthetic state is determined based on the cardiopulmonary index and the nociceptive index.
2. The anesthesia state monitoring method of claim 1, wherein the cardiopulmonary index is obtained by performing a similarity analysis on a heartbeat signal and a respiratory signal.
3. The anesthesia state monitoring method of claim 2, wherein the similarity analysis is performed by wavelet coherence analysis.
4. The anesthesia state monitoring method of claim 1, wherein the nociceptive index is obtained by extracting RR sequences from heartbeat signals and calculating the area under the curve formed by the RR sequences for representing the degree of analgesia.
5. The anesthesia state monitoring method of any of claims 1 to 4, wherein the result evaluation step comprises: and calculating and outputting an anesthesia index by integrating the cardiopulmonary index and the nociceptive index, wherein the anesthesia index is used for representing the anesthesia state.
6. The anesthesia state monitoring method of claim 5, wherein the result evaluation step further comprises: and respectively calculating the change values of the cardiopulmonary index and the nociceptive index at adjacent moments, and judging the sedation change and the analgesia change according to the change values of the cardiopulmonary index and the nociceptive index.
7. The anesthesia state monitoring method of claim 6, wherein the signal acquisition step further comprises a denoising process for filtering the interference signals during the acquisition process.
8. The anesthesia state monitoring device is characterized by comprising a signal acquisition unit for acquiring a respiratory signal and a heartbeat signal, a first analysis unit for processing an injury stimulation index, a second analysis unit for processing a cardiopulmonary index and a result evaluation unit for evaluating and obtaining a final anesthesia depth according to data processed by the first analysis unit and the second analysis unit.
9. The anesthesia state monitoring device of claim 8, wherein the heartbeat signal and respiration signal acquisition unit comprises electrodes for acquiring a thoracic impedance signal and/or a heartbeat signal.
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Cited By (3)
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| CN113456003A (en) * | 2021-06-10 | 2021-10-01 | 武汉大学 | Method and system for monitoring sedation and anesthesia in gastrointestinal endoscopy |
| CN115919329A (en) * | 2022-11-11 | 2023-04-07 | 重庆玺德尔医疗器械有限公司 | A comprehensive method for assessing pain nociception in patients undergoing anesthesia |
| CN116616710A (en) * | 2023-05-24 | 2023-08-22 | 中国人民解放军西部战区总医院 | Clinical anesthesia degree of depth monitoring devices that uses of department of anesthesia |
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