JP6647831B2 - Signal processing device, imaging device, and signal processing method - Google Patents

Description

  Embodiments of the present invention relate to a signal processing device, an imaging device, and a signal processing method.

  An electrocardiograph is a device that attaches electrodes to a living body and measures a potential difference between the electrodes. A signal measured by an electrocardiograph is called an ECG (Electrocardiogram) signal, and is widely used in the medical field. The ECG signal has, for example, a waveform called a P-wave (P-wave), an R-wave (R-wave), a QRS complex (QRS complex), or a T-wave (T-wave). Since these waveforms are used not only for diagnosis of various heart diseases but also for synchronization signals of a medical imaging device capable of performing ECG-gated imaging, automatic detection of waveforms is important for industrial applications. For example, in an image diagnosis of a heart using an MRI (Magnetic Resonance Imaging) device, imaging is performed at a timing synchronized with, for example, contraction or expansion of the heart using a synchronization signal (also called a trigger signal) detected from an ECG signal. Done. Such imaging is called electrocardiographic synchronized imaging.

  When performing ECG-gated imaging, a specific waveform in an ECG signal is detected to generate a trigger signal, and the start and end of imaging are controlled at a timing synchronized with the trigger signal. In particular, a trigger signal is often generated by detecting an R wave in an ECG signal. In this case, imaging may be started immediately after the R wave, and the delay time from the detection of the R wave to the generation of the trigger signal is preferably as short as possible.

  When a specific waveform is detected from an ECG signal, it is necessary to detect a trigger signal with high accuracy and low delay not only from a normal waveform of the ECG signal but also from an abnormal waveform of the ECG signal. A subject who is diagnosed with a heart by an MRI apparatus or the like generally has a suspicion of a heart disease in some cases, and an ECG signal from which a trigger signal is to be detected may include an abnormal waveform. Even with such an abnormal waveform, the heart contracts and expands, so in order to perform imaging synchronized with the contraction and dilation, the trigger signal is reliably detected with a short delay time even from the abnormal waveform in the ECG signal. There is a need to.

  On the other hand, imaging with an MRI apparatus involves the application of a pulsed gradient magnetic field or a pulsed RF (Radio Frequency) magnetic field, and large noise that dynamically changes on the ECG signal due to these applications is superimposed. I do. It is necessary to reliably detect a synchronization signal even for an ECG signal on which such noise is superimposed.

JP 2007-301101 A

"ECG-based gating in ultra high field cardiovascular magnetic resonance using an independent component analysis approach" J.W.Krug, et.al., Journal of Cardiovascular Magnetic Resonance, 2013.

  A problem to be solved by the present invention is to provide a signal processing device and an imaging device that can detect a synchronization signal from an abnormal waveform in a biological signal and also reliably detect a synchronization signal from a biological signal on which noise is superimposed. And a signal processing method.

  The signal processing device of the embodiment includes: a generation unit configured to generate a detection parameter for detecting a specific waveform in a biological signal related to a heartbeat based on the waveform of the biological signal; A storage unit that stores one or more detection parameters, and a detection unit that detects the specific waveform using the stored two or more detection parameters and generates a synchronization signal for performing heartbeat synchronous imaging.

The figure which shows an ECG signal typically. The figure which illustrates the ECG signal on which noise etc. are superimposed. FIG. 2 is a diagram illustrating a hardware configuration of an ECG signal processing device. FIG. 1 is a block diagram illustrating a configuration example of an ECG signal processing device according to a first embodiment. 5 is a flowchart illustrating a processing example of the ECG signal processing device according to the first embodiment. FIG. 3 is a diagram schematically illustrating a concept of an ECG signal in which high-frequency emphasis is performed. The figure which shows the concept of template generation. The figure which shows the concept of a template update. The 1st figure which shows the evaluation result of R wave detection. FIG. 9 is a view showing a concept of updating a template in a modification of the first embodiment. FIG. 9 is a block diagram illustrating a configuration example of an ECG signal processing device according to a second embodiment. FIG. 9 is a view for explaining effects of the second embodiment. FIG. 13 is a block diagram illustrating a configuration example of an ECG signal processing device according to a third embodiment. 9 is a flowchart illustrating a processing example of the ECG signal processing device according to the third embodiment. 9 is a timing chart illustrating the operation concept of the third embodiment. FIG. 13 is a block diagram illustrating a configuration example of an ECG signal processing device according to a fourth embodiment. FIG. 13 is a second diagram illustrating evaluation results of R-wave detection. FIG. 2 is a block diagram showing a configuration example of an electrocardiographic synchronous imaging device including an ECG signal processing device. FIG. 13 is a block diagram illustrating a configuration example of an ECG signal processing device according to a fifth embodiment. FIG. 14 is a first diagram illustrating an operation concept of the ECG signal processing device according to the fifth embodiment for a vector cardiogram; FIG. 19 is a second diagram illustrating the operation concept of the ECG signal processing device according to the fifth embodiment for a vector cardiogram; FIG. 19 is a block diagram showing a configuration example of an ECG signal processing device according to a modification of the fifth embodiment.

  An embodiment of an ECG signal processing device, an ECG synchronous imaging device (imaging device), and an ECG signal processing method according to the embodiment will be described with reference to the accompanying drawings. In the following embodiments, portions denoted by the same reference numerals perform the same operation, and duplicate description will be omitted as appropriate.

(First embodiment)
FIG. 1A is a diagram schematically illustrating an ECG signal to be detected by the ECG signal processing device 1 according to the present embodiment. As shown in FIG. 1A, the ECG signal has a specific waveform such as a P wave, an R wave, and a T wave.

  In the following embodiments, an example will be described in which an R wave is detected from a specific waveform. The example of detecting an R wave is an example, and the ECG signal processing device 1 of the embodiment can detect a waveform other than the R wave (for example, a P wave, a T wave, and the like).

  FIG. 1B is an enlarged view of the vicinity of the R wave, and the time from the peak of the R wave to the heartbeat synchronization signal (hereinafter, simply referred to as a synchronization signal) is defined as the delay time. Examples of an electrocardiographic synchronous imaging device (imaging device) 200 capable of imaging in synchronization with a heartbeat include a CT (Computed Tomography) device and an MRI (Magnetic Resonance Imaging) device. For example, the electrocardiographic synchronized imaging apparatus 200 uses an imaging method (electrocardiographically synchronized imaging method) in which the start timing of data collection is determined based on the position where the R wave is generated. The ECG-gated imaging apparatus 200 acquires a synchronization signal corresponding to the position of the R wave, and determines the start timing of data collection based on the acquired synchronization signal. Depending on the purpose of imaging, it is necessary to collect imaging data immediately after the R wave. For this reason, it is necessary to shorten the time required for detecting the arrival of the R wave from the ECG signal and generating the synchronization signal, that is, the delay time.

  For example, the case of an MRI apparatus will be described as an example. In the MRI apparatus, various non-contrast MRAs (Magnetic Resonance Angiography) such as an FBI (Fresh Blood Imaging) method and a Time-SLIP (Time-Spatial Labeling Inversion Pulse) method. ) Is used. In data collection by the FBI method, for example, the MRI apparatus collects diastolic images and systolic images by controlling the timing of data collection based on a synchronization signal, and calculates a difference image between the diastolic images and the systolic images. The drawn blood vessel image can be obtained. In data acquisition by the Time-SLIP method, the MRI apparatus can obtain a blood flow image by controlling, for example, the timing of applying a labeling pulse and the timing of data acquisition based on a synchronization signal. As described above, the MRI apparatus controls the data collection timing and the application timing of various pulses with reference to the synchronization signal generated from the ECG signal. Since these timings are often immediately after the R wave, it is desirable that the delay time be as short as possible. Note that the above is merely an example. Needless to say, the MRI apparatus performs imaging based on the synchronization signal in other imaging, such as various imaging of the heart and the like, imaging using a contrast agent, and the like.

  As is clear from FIG. 1A, among the waveforms included in the ECG signal, the R wave usually has the largest amplitude. However, even this R-wave is greatly affected by noise during the imaging of the MRI apparatus, and is difficult to detect. FIG. 2 illustrates this. In FIG. 2, signals of two channels output from the electrocardiograph are displayed in a superimposed manner.

  FIG. 2A is an example of an ECG signal observed when a subject (for example, a patient) is outside the MRI apparatus, in which the noise is relatively small and the R wave is prominent. FIG. 2B is an example of an ECG signal observed when the subject is inside the bore of the MRI apparatus. However, the MRI apparatus is not operating (a state where no image is captured), and only a static magnetic field is applied to the subject. The T wave behind the R wave is larger than that in FIG. 2A due to the influence of blood flowing in the static magnetic field, but the dynamic noise is not so large.

  On the other hand, FIG. 2C is a diagram illustrating an example of an ECG signal observed during imaging of the subject. It can be seen that large noise is superimposed on the ECG signal due to the influence of a gradient magnetic field, a radio frequency (RF) magnetic field, or the like applied during imaging.

  In the MRI apparatus, data is collected by executing a “pulse sequence” in which the gradient magnetic field, the intensity of the RF pulse, the application timing, and the like are defined. An imaging unit from the start of the execution of the pulse sequence to the repetition of a required number of TRs (Repetition Times) to collect predetermined data is referred to as a “protocol” or the like. In this specification, when the MRI apparatus is described as “operating”, “imaging” or “imaging state”, for example, it is a period during which a pulse sequence is being executed. means. Conversely, in this specification, when the MRI apparatus is described as “non-operation”, “stopped”, or “in a state where no image is captured”, for example, a period during which the pulse sequence is not executed Means For example, before the start of the first protocol included in a series of examinations, between protocols, or the like, corresponds to “non-operation”, “stopping”, or “non-imaging state”. Note that even in one TR included in the pulse sequence, there may be a period during which no gradient magnetic field or RF pulse is applied. Such a period can be treated as “non-operation”, “stopping”, or “imaging is not performed”.

  FIG. 3 is a diagram illustrating a hardware configuration of the ECG signal processing device 1. The ECG signal processing device 1 includes an input / output interface 301, a processing circuit 302, a communication interface 303, and a storage circuit 307. The storage circuit 307 includes a RAM (Random Access Memory) 304, a nonvolatile memory 305, and a disk drive 306.

  The nonvolatile memory 305 of the storage circuit 307 is a storage device such as a hard disk or a flash memory, and stores various programs and data.

  The processing circuit 302 includes, for example, one or a plurality of processors. Here, the term “processor” includes a dedicated or general-purpose processor such as a CPU (Central Processing Unit) or a signal processing processor. The processor of the processing circuit 302 realizes various functions of the ECG signal processing device 1 described later by a process of reading and executing one or a plurality of programs from the nonvolatile memory 305 to the RAM 304, that is, a software process. The processor may read a program stored in a recording medium such as a magnetic disk, an optical disk, or a USB memory in addition to the nonvolatile memory 305 from the disk drive 306 or the input / output interface 301. Alternatively, the program may be downloaded from an external server via the communication interface 303.

  Further, the processing circuit 302 may be configured by hardware such as an ASIC (Application Specific Integration Circuit) or an FPGA (Field-Programmable Gate Array). Various functions of the ECG signal processing device 1 can also be realized by hardware processing using an ASIC, an FPGA, or a dedicated electronic circuit. In addition, the processing circuit 302 may realize various functions of the ECG signal processing device 1 by combining hardware and software processing.

  FIG. 4 is a block diagram illustrating a functional configuration of the ECG signal processing device 1 according to the first embodiment and a configuration of a device connected to the ECG signal processing device 1. The electrocardiograph 100 generates an ECG signal and sends it to the ECG signal processing device 1. The ECG signal processing device 1 generates a synchronization signal from the ECG signal and sends it to the electrocardiographic synchronized imaging device 200.

  The electrocardiograph 100 includes electrodes 101a and 101b, an amplifier 110, and an AD converter 120. The electrodes 101a and 101b are attached to a human body. The amplifier 110 amplifies a weak potential difference between the electrodes 101a and 101b. The AD converter 120 converts the analog signal amplified by the amplifier 110 into a digital signal.

  Although the electrocardiograph 100 exemplifies two electrodes 101a and 101b, the number of electrodes is not limited to two. For example, in order to obtain a 12-lead electrocardiogram, a configuration including four electrodes each attached to a limb and six electrodes attached to a chest may be used. Further, instead of a method of calculating a potential difference between two points on the body, a method of recording a potential difference between a predetermined reference and an electrode attachment point may be used.

  The ECG signal processing device 1 has at least the processing circuit 302 and the storage circuit 50 as described above. The storage circuit 50 is a part of the storage circuit 307. The processing circuit 302 implements the filter processing function 10, the detection function 20, the template generation function unit 30, and the template update function 40 by, for example, the processor of the processing circuit 302 executing a program read from the storage circuit 307. The filter processing function 10 obtains an ECG signal from the electrocardiograph 100 and performs a process of emphasizing the R wave in the ECG signal. Examples of the process of emphasizing the R wave include a process of emphasizing the ECG signal in a high frequency band using a high-pass filter that emphasizes a high-frequency component of the ECG signal and a process of emphasizing the band of the ECG signal using a band-pass filter. Hereinafter, an ECG signal that has been subjected to high-frequency emphasis or band emphasis by the filter processing function 10 is referred to as an enhanced ECG signal.

  The template generation function 30 generates a detection parameter for detecting an R wave from the enhanced ECG signal. Various detection parameters are possible for detecting the R wave. One of the detection parameters is a waveform template. In the present embodiment, a waveform near the R wave is cut out from the ECG waveform sequentially input from the electrocardiograph 100 to generate a waveform template (hereinafter, simply referred to as a template).

  The storage circuit 50 stores the generated template. Here, the storage circuit 50 stores two or more templates. For example, as illustrated in FIG. 3, M (M is 2 or more) different templates (1) to (M) are stored. The storage circuit 50 is configured as a rewritable memory.

  The template update function 40 updates the template stored in the storage circuit 50. The specific method of updating will be described later.

  The detection function 20 detects an R wave from the emphasized ECG signal output in time series from the filter processing function 10, and generates a synchronization signal corresponding to the detection of the R wave. The generated synchronization signal is output to the electrocardiographic synchronized imaging device 200.

  The detection function 20 has an evaluation value calculation function 21 and a determination function 22. The evaluation value calculation function 21 calculates an evaluation value from each of the two or more templates stored in the storage circuit 50 and the enhanced ECG signal. The determination function 22 compares the calculated evaluation value with a predetermined threshold to detect an R wave.

  As a detection parameter for detecting the R wave, in addition to the template, for example, feature values such as a peak value of the R wave, a slope of rising and falling of the R wave, and a half value width of the R wave can be considered. When detecting an R-wave using these features, the template generation function 30 extracts these features from the enhanced ECG signal and generates a detection parameter. Further, the storage circuit 50 stores a plurality of these generated detection parameters. For example, when the detection parameter is a combination of the peak value and the half width of the R wave, the storage circuit 50 stores a plurality of combinations of the peak value and the half width of the R wave. The detection function 20 includes a detection parameter (peak value, half width, etc. of the R wave) stored in the storage circuit 50 and a detection parameter (peak value, half width, etc., of the R wave) extracted from the enhanced ECG signal. Are compared and the R wave is detected. As described above, various feature amounts can be taken as the detection parameters. Hereinafter, the description will be made assuming that the detection parameters are templates.

  FIG. 5 is a flowchart illustrating an outline of processing of the ECG signal processing device 1 according to the first embodiment.

  Steps ST100 and ST101 are steps corresponding to the filter processing function 10 of the processing circuit 302. In step ST100, the processing circuit 302 inputs the ECG signal as a time-series signal. The input ECG signal is, for example, a digital signal sampled at 1000 Hz (1 ms sampling interval) in the AD converter 120 of the electrocardiograph 100. The filter processing function 10 may thin out even-numbered samples or odd-numbered samples and down-sample to 500 Hz, for example, in order to suppress the calculation cost after the filtering as long as the performance such as the delay time is not deteriorated.

  In step ST101, the processing circuit 302 performs, for example, high-frequency emphasis filter processing on the down-sampled ECG signal to generate an enhanced ECG signal.

  FIG. 6 is a diagram schematically illustrating the concept of an ECG signal in which high-frequency emphasis is performed. The upper part of FIG. 6 shows a simplified waveform of an input ECG signal, and the lower part of FIG. 6 shows a simplified ECG waveform after high-frequency emphasis processing. By the high-frequency emphasizing process, the steep rising and falling R waves are emphasized. On the other hand, T waves and P waves whose rising and falling are gradual are suppressed. Note that a low-pass filter may be used together with a high-pass filter to suppress noise.

  Steps ST102 and ST103 are steps corresponding to the template generation function 30 of the processing circuit 302. FIG. 7 shows the concept of template generation processing performed by the template generation function 30.

  In step ST102, the processing circuit 302 detects a peak of the enhanced ECG signal. When the noise or the like is small, the peak of the enhanced ECG signal generally corresponds to the peak of the R wave. The enhanced ECG signal is input to the template generation function 30 of the processing circuit 302 at each sampling interval (for example, every 2 ms), and it is determined whether or not a peak has arrived, that is, the peak detection process is performed at the sampling interval. It is performed every time.

  When a peak is detected (YES in step ST102), in step ST103, the processing circuit 302 generates a template by cutting out a part of the R wave from the input enhanced ECG signal based on the position of the detected peak. I do.

  In FIG. 7, waveforms of the Nth, (N + 1) th and (N + 2) th three R-waves for a predetermined period (W milliseconds) in the past from the respective peaks (for the region indicated by the dashed box) The waveform (waveform) is cut out, and the template (N), the template (N + 1), and the template (N + 2) are generated. As can be seen from FIG. 7, when the peak height of the R wave fluctuates between heartbeats, templates having slightly different shapes are generated.

  There is no particular limitation on how long in the past the waveform is cut out from the peak position of the R wave, but, for example, a template is generated by cutting out the waveform in the past 20 ms from the peak position.

  Note that detecting the peak of the enhanced ECG signal is a process performed only for generating a template, not a process for detecting an R wave.

  Next, steps ST104 and ST105 are steps corresponding to the template update function 40 of the processing circuit 302. In step ST104, the processing circuit 302 determines whether to update the template of the storage circuit 50 using the newly generated template, or determines a method of updating the template. Then, in step ST105, the template of the storage circuit 50 is updated according to the determination.

  As an updating method, for example, of the plurality of templates stored in the storage circuit 50, the oldest template may be discarded, and a newly generated template may be added to the storage circuit 50. For example, as shown in FIG. 8, when M templates from template (N-1) to template (NM) are stored in the storage circuit 50, the oldest template (NM) is discarded. , The newly generated template (N) is added to the storage circuit 50. In this updating method, each time a template is newly generated, the template of the storage circuit 50 is updated.

  Steps ST106 to ST108 are steps corresponding to the detection function 20 of the processing circuit 302. In step ST106, the processing circuit 302 uses the evaluation value calculation function 21 to collate the enhanced ECG signal after the filter processing with each template stored in the storage circuit 50, and calculates an evaluation value for each template.

Specifically, a difference is obtained for each sample at each time from the latest W milliseconds of the enhanced ECG signal and the m-th template stored in the storage circuit 50, and the sum of the absolute values of the differences is evaluated as an evaluation value E _m . Since the evaluation values _Em are calculated for each of the templates stored in the storage circuit 50, if the total number of templates stored in the storage circuit 50 is M, the M evaluation values _Em are calculated as follows. Is calculated.

In step ST 107, the processing circuit 302, the determination function 22 determines the minimum value Emin of the M number of evaluation values _{E m,} performs a threshold processing for the minimum value Emin, for detecting the R-wave. Specifically, when the minimum value Emin is smaller than a predetermined threshold, it is determined that the R wave has been detected.

  When the R wave is detected, the processing circuit 302 generates a synchronization signal and outputs the synchronization signal to the electrocardiographic synchronized imaging apparatus 200 in step ST108. If no R wave is detected, the process returns to step ST100.

In the above processing, the difference between the emphasized ECG signal and the template is used as the evaluation value. Alternatively, a correlation value between the emphasized ECG signal and the template may be used as the evaluation value. In this case, the determination function 22 of the processing circuit 302, the maximum value Emax of the M evaluation values E _m, when the maximum value Emax is greater than a predetermined threshold value, it is judged as the R-wave is detected.

  Step ST109 is a processing end determination, and the processing circuit 302 repeats the processing from step ST100 to step ST108 until a processing end instruction is input from the outside.

  The ECG signal processing device 1 according to the first embodiment described above is configured to store a plurality of different templates in the storage circuit 50. Therefore, even if the R-wave waveform (for example, the peak value of the R-wave) of the enhanced ECG signal input to the detection function 20 fluctuates for each R-wave, the fluctuated R-wave is stored in the storage circuit 50. If it is similar to any of the stored templates, the fluctuating R wave can be detected with high reliability. That is, by detecting an R wave using a plurality of templates, robustness to a fluctuating ECG signal can be improved.

FIG. 9 is a diagram illustrating a result of performing R-wave detection on the ECG signal to confirm the effect of the ECG signal processing device 1 according to the first embodiment. Thirteen volunteers received MRI diagnoses using 1.5 Tesla and 3 Tesla MRI equipment, and accurately detected how many out of the total number of R waves (22,298) contained in the ECG signal collected during that time We evaluated whether we could do it. Of the total number of R-waves, 8006 were collected during MRI operation (imaging), and the others were collected during MRI non-operation. The F value was used as an evaluation index, and this was set as the vertical axis in FIG. The F value can be expressed by the following (Equation 1) to (Equation 3).
F value = (2PR) / (P + R) (Equation 1)
P = TP / (TP + FP) (Equation 2)
R = TP / (TP + FN) (Equation 3)
Here, the case where the R wave was detected within an error of 20 milliseconds before and after the correct R wave position was determined to be successful. In addition, TP (True Positive) was the number of successes, FP (False Positive) was the number of false detections (detected but not correct), and FN (False Negative) could not detect the R wave to be detected ( Missing) number. The F value is an evaluation index that takes into account not only success but also missing and erroneous detection. The higher the F value, the higher the reliability of detection.

  The horizontal axis of the graph in FIG. 9 is the number of templates stored in the storage circuit 50. In particular, during the operation of the MRI apparatus (during imaging), the F value is improved by increasing the number of templates, and the effect of the above-described processing of the ECG signal processing apparatus 1 can be confirmed.

(Modification of First Embodiment)
In the above-described first embodiment, in the template update processing in steps ST104 and ST105 in FIG. 5, the oldest template among the templates stored in the storage circuit 50 is discarded, and a newly generated template is added. (See FIG. 8). On the other hand, in the modification of the first embodiment, the similarity between the newly generated template and each of the templates stored in the storage circuit 50 is obtained, and when the similarity is lower than a predetermined value. When it is determined, the newly generated template is stored in the storage circuit 50, and the template in the storage circuit 50 is updated.

  Specifically, as shown in FIG. 10, when the newly generated template is not similar to any of the templates of the storage circuit 50 (the similarity is low), the template of the storage circuit 50 is updated. . On the other hand, when the newly generated template is similar to any of the templates of the storage circuit 50 (the similarity is high), the template of the storage circuit 50 is not updated. In this case, a newly generated template with a low similarity is added to the storage circuit 50, and the template with a high similarity is discarded.

  By such an updating method, templates having low similarity to each other remain in the storage circuit 50. As a result, when the abnormal waveform is included in the ECG waveform (see FIG. 12A), the template generated corresponding to the abnormal waveform is stored in the storage circuit 50 and is maintained after the storage. Become. Therefore, when an abnormal waveform arrives next time, the abnormal waveform can be detected by the already stored abnormal waveform template.

(Second embodiment)
FIG. 11 is a block diagram illustrating a configuration example of an ECG signal processing device 1a according to the second embodiment. The second embodiment has a configuration in which a second storage circuit 60 is added to the first embodiment.

  The second storage circuit 60 stores one or more, preferably two or more fixed pre-created templates created in advance. “Preliminary creation” means to create the subject before the subject is diagnosed with the ECG-gated imaging apparatus 200. The pre-created template may be created from an enhanced ECG signal obtained by filtering an ECG signal of the same subject, or may be created from an enhanced ECG signal of a different subject. Alternatively, a template created from different subjects may be averaged to create a representative template.

  The second storage circuit 60 stores at least one pre-created template based on the normal waveform of the ECG signal, but preferably stores a plurality of types of pre-generated templates corresponding to the normal waveform and the abnormal waveform.

  The processing of the ECG signal processing device 1a according to the second embodiment is basically the same as that of the first embodiment. However, in the flowchart of FIG. 5, the evaluation value calculation processing of step ST106 and the processing of step ST107 are performed. R wave detection judgment is slightly different.

  When the number of templates stored in the storage circuit 50 is M and the number of pre-created templates stored in the second storage circuit 60 is K, in step ST106, the template of the storage circuit 50 and the second An evaluation value is calculated for each of the pre-created templates in the storage circuit 60 of FIG. That is, the evaluation value calculation function 21 calculates (M + K) evaluation values. Then, in step ST107, if the minimum value Emin of the (M + K) evaluation values is smaller than a predetermined threshold value, it is detected as an R wave.

  FIG. 12 is a diagram illustrating the effect of the ECG signal processing device 1a according to the second embodiment in comparison with a conventional detection method. In particular, as shown in FIG. 12A, a comparison is made for a case where an abnormal waveform is included in the ECG signal. Conventionally, a method of detecting an R wave with one fixed template created in advance (referred to as a conventional method (1)) or a method of detecting only one template that is sequentially updated (referred to as a conventional method (2)) is used. I was

  In the conventional method (1), when a fixed template is created based on a normal waveform, detection of an abnormal waveform fails as shown in FIG. On the other hand, when the fixed template is created based on the abnormal waveform, the detection of the normal waveform fails as shown in FIG.

  In the conventional method (2), as shown in FIG. 12D, the detection failure continues from the start of the acquisition of the ECG signal to the generation of the template to be sequentially updated. Further, since one template is sequentially updated, if an abnormal waveform appears after the template is updated for the normal waveform, the abnormal waveform cannot be detected.

  On the other hand, the second embodiment has a second storage circuit 60 for storing fixed templates in addition to the storage circuit 50 for storing a plurality of templates to be sequentially updated. As a preferred embodiment of the second storage circuit 60, at least a template 1 corresponding to a normal waveform and a template 2 corresponding to an abnormal waveform are stored. With such a configuration, both the abnormal waveform and the normal waveform can be detected by the template 1 and the template 2 of the second storage circuit 60 immediately after the start of the ECG signal acquisition, as shown in FIG. Can be.

  After the template is generated in the storage circuit 50, the R wave can be robustly detected by a plurality of templates that are sequentially updated. Further, as described in the modification of the first embodiment, the template corresponding to the normal waveform and the template corresponding to the abnormal waveform are generated and stored in the storage circuit 50 based on the latest ECG waveform. Therefore, both the abnormal waveform and the normal waveform can be robustly detected.

(Third embodiment)
FIG. 13 is a block diagram illustrating a configuration example of an ECG signal processing device 1b according to the third embodiment. The third embodiment has a configuration in which a template generation determination function 70 is added to the second embodiment. The template generation determination function 70 is also a function realized by the processing circuit 302.

  FIG. 14 is a flowchart illustrating an operation example of the ECG signal processing device 1b according to the third embodiment. The process of step ST200 is added to the flowchart (FIG. 5) of the first and second embodiments.

  In step ST200, the processing circuit 302 monitors the operation state of the ECG-gated imaging apparatus 200 by the template generation determination function 70, and generates a new template by the template generation function 30 in accordance with the operation state of the ECG-gated imaging apparatus 200. Is determined.

  For example, when the electrocardiographic synchronized imaging apparatus 200 is an MRI apparatus, the processing circuit 302 inputs an operation signal from the MRI apparatus indicating whether the MRI apparatus is capturing an image or stopping (not capturing an image). , It is determined whether the MRI apparatus is taking an image. If an image is being captured, the processing circuit 302 skips the processing in steps ST102 and ST103, that is, does not perform processing for generating a new template from the enhanced ECG signal. When the image is being captured, the processing circuit 302 further skips the processing of steps ST104 and ST105 and does not perform the processing of updating the template of the storage circuit 50.

  FIG. 15 is a timing chart illustrating an operation example of the ECG signal processing device 1b according to the third embodiment. As shown in FIGS. 15A and 15B (see also FIGS. 2A to 2C), when the MRI apparatus is not operating, noise superimposed on the ECG signal is small. However, during the imaging period of the MRI apparatus, large noise is superimposed on the ECG signal under the influence of the gradient magnetic field and the RF magnetic field generated by the MRI apparatus. When a template is created from an ECG signal on which such large noise is superimposed, a template having a shape significantly different from the waveform to be detected (R wave) is generated, and correct detection cannot be expected.

  Therefore, in the third embodiment, as shown in FIGS. 15C and 15D, the generation and update of the template are stopped during the imaging, and the template stored in the storage circuit 50 immediately before the imaging period is deleted. Shall be retained. During imaging, the R wave is detected using the template held in the storage circuit 50. Although considerably large noise is superimposed on the ECG signal to be detected during imaging, the R wave can be detected with high reliability because the template itself used for matching is not affected by the noise.

  The MRI apparatus may sequentially execute a plurality of protocols (for example, a plurality of protocols for collecting images of a plurality of imaging types such as a T1-weighted image and a T2-weighted image) according to an imaging condition input by an operator. is there. In such a case, if imaging by one protocol ends, there may be some non-operation period before imaging of the next protocol starts. In this case, the creation and update of the template can be restarted using the non-operation period.

  In FIG. 13, the timing at which the template generating function 30 of the processing circuit 302 cuts out the template from the enhanced ECG signal is determined by comparing the pre-created template stored in the second storage circuit 60 with the enhanced ECG signal. Like that. Specifically, when the R wave is detected by comparing the pre-created template with the enhanced ECG signal, the waveform of the enhanced ECG signal in the period from the detection position of the R wave to the past W milliseconds, for example, 20 milliseconds ago And generate a template. In the third embodiment as well, similarly to the first embodiment, the template generation function 30 may independently detect the peak of the enhanced ECG signal and determine the timing for cutting out the template.

(Fourth embodiment)
FIG. 16 is a block diagram illustrating a configuration example of an ECG signal processing device 1c according to the fourth embodiment. The fourth embodiment has a configuration in which the third embodiment has a configuration in which either one of a high-pass filter and a band-pass filter is provided, whereas the fourth embodiment has a filter processing function having a high-pass filter. The configuration has two filter processing functions of H10a and a filter processing function B10b having a band-pass filter.

  The filter processing function H10a outputs a high-frequency emphasized ECG signal, and the filter processing function B10b outputs a band-enhanced ECG signal. Along with this, the configuration has two template generation functions, two template update functions, and two storage circuits. The high-frequency emphasized ECG signal is processed by the template generation function H30a, the template update function H40a, and the storage circuit H50a, and the band-enhanced ECG signal is processed by the template generation function B30b, the template update function B40b, and the storage circuit 50Bb.

  On the other hand, the detection function 20 also receives two signals, a high-frequency emphasized ECG signal and a band-enhanced ECG signal. The evaluation value calculation function 21 of the detection function 20 calculates the evaluation value (sum of absolute values of the differences) between the high-frequency emphasized ECG signal and the M templates stored in the storage circuit H50a, respectively. The minimum value is set as the high-frequency emphasis evaluation value EHmin. Similarly, the evaluation value calculation function 21 calculates the evaluation value (sum of the absolute values of the differences) between the band emphasized ECG signal and the M templates stored in the storage circuit B50b, and calculates the minimum value of the evaluation value. Is the band emphasis evaluation value EBmin.

  Further, the evaluation value calculation function 21 calculates the composite evaluation value E by weighting and adding the high-frequency emphasis evaluation value EHmin and the band emphasis evaluation value EBmin. Specifically, when the weight is α (0 ≦ α ≦ 1), the composite evaluation value E is calculated by E = αEHmin + (1−α) EBmin.

  The determination function 22 detects an R wave using the calculated composite evaluation value E. Specifically, when the composite evaluation value E is smaller than a predetermined threshold, it is determined to be an R wave.

  Note that the determination function 22 may always determine that the R wave is not the R wave during a predetermined time after the detection of the R wave. When ECG signals of two or more channels are input from the electrocardiograph 100, the composite evaluation value E is calculated for each channel, and the average value is compared with a predetermined threshold to determine whether or not the signal is an R wave. It may be determined.

  FIG. 17 is a diagram illustrating the results of an evaluation test performed to confirm the effect of the ECG signal processing device 1c according to the fourth embodiment. FIG. 17A shows an R-wave detection result using a 1.5 Tesla MRI apparatus, and FIG. 17B shows an R-wave detection result using a 3 Tesla MRI apparatus.

  The data of the ECG signals used for the evaluation are the same as those in FIG. 9, and it was evaluated how many of the total number (22,298) of R waves included in the collected ECG signals could be accurately detected. Of the total number of R-waves, 8006 were collected while the MRI was operating (during imaging), and the others were collected when the MRI was not operating. As in the case of FIG. 9, the F value is used as the evaluation index, and this is set as the vertical axis in FIG.

  When the evaluation target on the horizontal axis is “all periods (during imaging + during stop)”, the total number of R waves (22,298) is evaluated, and when the evaluation target is “only during the imaging period”, The collected R-waves (8006) are evaluated.

  The bar graph corresponding to “Pre-created” on the horizontal axis is an evaluation result when R-wave detection is performed using a fixed template created in advance. The bar graph corresponding to “sequential update” is an evaluation result when the template is sequentially updated and the R-wave detection is performed during both imaging and stopping. Further, a bar graph corresponding to “not updated during imaging” is a result evaluated by the configuration of the ECG signal processing device 1c according to the fourth embodiment, and a method in which the template is updated only during stoppage and not updated during imaging. Is an evaluation result when R wave detection is performed.

  FIG. 17 shows that the ECG signal processing device 1c according to the fourth embodiment has high detection performance. In particular, it was shown that the performance of “non-update during imaging”, which corresponds to the fourth embodiment, in a 3 Tesla MRI apparatus is improved as compared to “pre-production” and “sequential update”.

  FIG. 18 is a diagram illustrating an example in which the electrocardiographic synchronized imaging device 200a includes the ECG signal processing device 1. The ECG synchronous imaging apparatus 200a includes an ECG signal processing apparatus 1 that generates a synchronization signal, a data collection circuit 210 that collects imaging data from a subject in synchronization with the synchronization signal, and an imaging apparatus that performs processing based on the collected imaging data. It has an image generation circuit 220 for generating an image of a specimen and a display 230 for displaying the generated image. The ECG signal processing device 1 included in the ECG synchronous imaging device 200a is not limited to the first embodiment, and may include the ECG signal processing devices 1a, 1b, and 1c of the second to fourth embodiments.

  When the electrocardiographic synchronous imaging apparatus 200a is an MRI apparatus, the above-described data collection circuit is configured by a static magnetic field magnet, a gradient magnetic field coil, an RF coil, a transmission circuit, a reception circuit, and a sequence controller included in the MRI apparatus. Further, a processing circuit such as a processor included in the host computer of the MRI apparatus constitutes the image generation circuit 220 described above.

  In each of the above embodiments, an example has been described in which the ECG signal processing apparatuses 1, 1 a, 1 b, and 1 c are configured separately from the electrocardiograph 100. The electrocardiograph 100 may have an internal configuration of the ECG signal processing devices 1, 1a, 1b, and 1c.

(Fifth embodiment)
In each of the first to fourth embodiments described above, the synchronization signal is generated based on the ECG signal output from the electrocardiograph 100. On the other hand, for example, a 12-lead type electrocardiograph outputs 12 (12-dimensional) ECG signals such as I, II, III, aVR, aVL, aVF, and V1 to V6. For example, in the case of a four-terminal electrocardiograph, two to three ECG signals (two to three dimensions) are output. Also, for example, the vector cardiogram uses two or three ECG signals generated from a plurality of electrode signals.

  The ECG signal processing device 1 according to the fifth embodiment detects an R wave from a vector cardiogram using two or more ECG signals. FIG. 19 is a diagram illustrating a configuration example of an ECG signal processing device 1d according to the fifth embodiment.

  For example, two electrocardiographs 100a and 100b are connected to the ECG signal processing device 1d. The electrocardiographs 100a and 100b have different electrodes (101a and 101b) and electrodes (102a and 102b). The ECG signal output from the electrocardiograph 100a is referred to as an ECG first lead signal (X), and the ECG signal output from the electrocardiograph 100b is referred to as an ECG second lead signal (Y).

  The configuration of the ECG signal processing device 1d is different from the ECG signal processing device 1 of the first embodiment (see FIG. 4) in that a coordinate conversion function 80 is provided. The configuration other than the coordinate conversion function 80 is the same as that of the first embodiment. Note that the coordinate conversion function 80 is also realized by the processing circuit 302.

  FIG. 20 and FIG. 21 are diagrams illustrating the operation concept of the coordinate conversion function 80 by taking, as an example, a vector cardiogram that outputs an ECG first guide signal (X) and an ECG second guide signal (Y).

  The upper and lower diagrams on the left side of FIG. 20A are diagrams illustrating waveform examples of the ECG first induction signal (X) and the ECG second induction signal (Y). The horizontal axis represents time, and the vertical axis represents amplitude. The right side of FIG. 20A shows the amplitude of the ECG first induction signal (X) on the X axis (horizontal axis) and the amplitude of the ECG second induction signal (Y) on the Y axis over time. It is the figure plotted (vertical axis). Hereinafter, the diagram on the right side is referred to as a vector plot diagram.

  FIG. 20A shows a waveform when there is no noise, for example, when the subject is outside the MRI apparatus. In a state without noise, the ECG first guide signal (X) and the ECG second guide signal (Y) have a correlation with each other. Therefore, the R wave at the position P1 has a shape having a strong peak obliquely rightward from the origin on the vector plot diagram. The T wave at the position P2 also tends to have a peak in the same direction as the R wave.

  On the other hand, FIG. 20B illustrates a waveform in a state with noise, for example, in a state in which the subject is placed inside the MRI apparatus and is affected by a strong static magnetic field. In this state, noise is likely to be superimposed on the ECG first induction signal (X) and the ECG second induction signal (Y), as illustrated in the upper and lower left diagrams of FIG. For example, noise is superimposed on the position P3. Usually, the correlation between the ECG first guide signal (X) and the ECG second guide signal (Y) due to such noise is based on the ECG first guide signal (X) and the ECG second guide signal between R waves. The correlation with (Y) is different. For this reason, in the vector plot on the right side of FIG. 20B, the noise corresponding to the position P3 has a peak in a direction different from the peak direction of the R wave at the position P1, for example, a direction separated by 90 degrees. .

  In the fifth embodiment, a specific waveform such as an R wave is more reliably detected by using such a feature of the vector cardiogram. Specifically, the coordinate conversion function 80 converts the coordinates of the ECG first guide signal (X) and the ECG second guide signal (Y), and projects them in the peak direction of the R wave on the vector plot diagram.

  FIG. 21 is a diagram illustrating the concept of the coordinate conversion function 80. It is assumed that the peak direction of the R wave in the absence of noise has a slope θ in the XY coordinate system. The coordinate conversion function 80 rotates this by θ and performs coordinate conversion to the xy coordinate system by the following equation, for example.

x = X · cos (θ) + Y · sin (θ) (Equation 4)
y = −X · sin (θ) + Y · cos (θ) (Equation 5)
As a result, for example, when the peak direction of the noise is orthogonal to the peak direction of the R wave, the signal x after coordinate conversion has a noise-reduced waveform as illustrated on the right side of FIG.

  The gradient θ required for the coordinate transformation is obtained by acquiring the ECG first guide signal (X) and the ECG second guide signal (Y) in a state where there is no noise, for example, when the subject is outside the MRI apparatus, It can be obtained from the peak direction of the R wave on the plot.

  The processing for the ECG signal x after the coordinate conversion is the same as in the first to fourth embodiments. As described above, according to the ECG signal processing device 1d according to the fifth embodiment, the vector cardiogram can be applied to the ECG signal processing devices 1, 1a, 1b, and 1c according to the first to fourth embodiments. In addition, the effect of noise can be further reduced.

(Modification of Fifth Embodiment)
FIG. 22 is a diagram illustrating a configuration example of an ECG signal processing device 1e according to a modification of the fifth embodiment. The configuration shown in FIG. 19 applies the processing of the first to fourth embodiments to one of the signals after the coordinate transformation, that is, to the ECG signal x obtained by (Equation 4). . On the other hand, in the ECG signal processing device 1e according to the modification of the fifth embodiment, a plurality of signals after coordinate conversion, for example, an ECG signal x obtained by (Equation 4) and an ECG signal x obtained by (Equation 5) The processing of the first to fourth embodiments is applied in parallel to both of the ECG signals y to be obtained. In this case, two evaluation values are obtained from the two evaluation value calculation functions 21. These two evaluation values are input to the integration determination function 90. The integration determination function 90 is also realized by the processing circuit 302. The integrated determination function 90 detects, for example, an R wave by weighting and adding two evaluation values and applying a predetermined threshold value to the added value, and generates a synchronization signal.

  As described above, many of the synchronization signals used for synchronous imaging using the MRI apparatus are generated from the ECG signals. The ECG signal is one of the biological signals related to the heartbeat, and the biological signals related to the heartbeat include a pulse wave signal, a heart sound signal, and the like in addition to the ECG signal. In the ECG signal processing device of each of the above-described embodiments, a heartbeat synchronization signal can be generated by converting an input signal into an ECG signal and using a biological signal related to a heartbeat such as a pulse wave signal or a heart sound signal. In this case, in the above description, “ECG signal processing device” is referred to as “signal processing device”, “ECG signal processing method” is referred to as “signal processing device”, and “ECG synchronous imaging device” is referred to as “heart rate synchronous imaging device”. ". Further, in the above description, the “ECG signal” is replaced with “biological signal related to heartbeat”, the “ECG synchronization signal” is replaced with “heartbeat synchronization signal”, and the “ECG synchronized imaging” is replaced with “heartbeat synchronization imaging”. Just read it.

  According to the ECG signal processing device according to at least one embodiment described above, even when a large noise is superimposed on an ECG signal during imaging or the like, the R wave in the EGC signal is more reliably detected. In addition, even when an abnormal waveform is included in the ECG signal, the abnormal waveform can be detected. As a result, a synchronization signal can be supplied stably and reliably to an imaging device that performs ECG-gated imaging.

  Note that the template generation function, the storage circuit, and the detection function in the embodiment are examples of the generation unit, the storage unit, and the detection unit in the claims, respectively. Further, the template updating function, the template generation determining function, the filter processing function, and the second storage circuit in the embodiment respectively include an update unit, a generation determination unit, a filter processing unit, and a second storage unit in the claims. This is an example. Further, the data processing circuit and the image generation circuit in the embodiment are examples of a data collection unit and an image generation unit in the claims, respectively.

  Although several embodiments of the present invention have been described, these embodiments are provided by way of example and are not intended to limit the scope of the invention. These new embodiments can be implemented in other various forms, and various omissions, replacements, and changes can be made without departing from the spirit of the invention. These embodiments and their modifications are included in the scope and gist of the invention, and are also included in the invention described in the claims and their equivalents.

DESCRIPTION OF SYMBOLS 1 ECG signal processing apparatus, signal processing apparatus 10 Filter processing function 20 Detection function 21 Evaluation value calculation function 22 Judgment function 30 Template generation function 40 Template update function 50 Storage circuit 60 Second storage circuit 70 Template generation determination function 100 Electrocardiograph 200 ECG synchronous imaging device, imaging device

Claims (18)

A generation unit that generates a detection parameter for detecting a specific waveform in a biological signal related to a heartbeat based on the waveform of the biological signal,
A storage unit for storing two or more generated detection parameters,
A detection unit that detects the specific waveform using the stored two or more detection parameters and generates a synchronization signal for performing heartbeat synchronous imaging ;
An updating unit that updates the two or more detection parameters stored in the storage unit;
With
The generating unit sequentially generates new detection parameters from the biological signal input in time series,
The updating unit updates the detection parameters stored in the storage unit with the generated new detection parameters, and stores the new detection parameters generated by the generation unit and the storage parameters in the storage unit. Calculating a similarity with each of the two or more detection parameters, and storing the new detection parameter determined to have the similarity lower than a predetermined value in the storage unit;
Signal processing device. A generation unit that generates a detection parameter for detecting a specific waveform in a biological signal related to a heartbeat based on the waveform of the biological signal,
  A storage unit for storing two or more generated detection parameters,
  A detection unit that detects the specific waveform using the stored two or more detection parameters and generates a synchronization signal for performing heartbeat synchronous imaging;
  An updating unit that updates the two or more detection parameters stored in the storage unit;
  A generation determining unit;
With
  The generating unit sequentially generates new detection parameters from the biological signal input in time series,
  The generation determination unit monitors an operation state of an imaging device connected to the outside, and determines whether to generate the new detection parameter in the generation unit according to the operation state of the imaging device,
  The updating unit updates the detection parameters stored in the storage unit with the generated new detection parameters,
Signal processing device. A generation unit that generates a detection parameter for detecting a specific waveform in a biological signal related to a heartbeat based on the waveform of the biological signal,
  A storage unit for storing two or more generated detection parameters,
  A detection unit that detects the specific waveform using the stored two or more detection parameters and generates a synchronization signal for performing heartbeat synchronous imaging;
  An updating unit that updates the two or more detection parameters stored in the storage unit;
  A generation determining unit;
With
  The generating unit sequentially generates new detection parameters from the biological signal input in time series,
  The generation determination unit monitors the operating state of an externally connected MRI apparatus, and determines whether to generate the new detection parameter in the generating unit, according to the operating state of the MRI apparatus,
  The updating unit updates the detection parameter when the MRI apparatus is not imaging, and during the imaging of the MRI apparatus, the detection parameter stored immediately before the start of imaging without updating the detection parameter. Hold the
Signal processing device. The biological signal is an ECG signal, the specific waveform is an R wave, and the detection parameter is a waveform template corresponding to a partial waveform of the R wave.
The signal processing device according to claim 1 . The generating unit cuts out a partial waveform of the R wave from two or more R waves included in the ECG signal to generate two or more waveform templates,
The storage unit stores the generated two or more waveform templates,
The detection unit detects the R wave by comparing the waveform of the ECG signal input in time series with the two or more waveform templates,
The signal processing device according to claim 4 . The detection unit collates the waveform of the ECG signal with the two or more waveform templates, calculates two or more evaluation values corresponding to the two or more waveform templates, and obtains the two or more evaluation values from the two or more evaluation values. Comparing the one integrated evaluation value with a predetermined threshold to detect the R wave;
The signal processing device according to claim 5 . The evaluation value is a difference evaluation value based on a difference between the waveform of the ECG signal and each of the two or more waveform templates, and the integrated evaluation value is the smallest value among the two or more difference evaluation values.
The signal processing device according to claim 6 . A filter processing unit that enhances the R wave in the ECG signal by filtering.
The generating unit generates the two or more waveform templates from the ECG signal in which the R wave is emphasized by the filtering unit.
The signal processing device according to claim 4 . The filter processing unit includes a first filter that emphasizes the ECG signal in a high frequency band, and a second filter that emphasizes the band of the ECG signal,
The generation unit generates two or more first waveform templates generated from the high-frequency-emphasized ECG signal and two or more second waveform templates generated from the band-emphasized ECG signal,
The storage unit stores the two or more first waveform templates and the two or more second waveform templates,
The detection unit calculates a first evaluation value by comparing the waveform of the high-frequency-emphasized ECG signal with the two or more first waveform templates. Comparing the two or more second waveform templates to calculate a second evaluation value, and detecting the R wave based on the first evaluation value and the second evaluation value;
The signal processing device according to claim 8 . A second storage unit that stores one or more fixed templates generated in advance,
The detection unit includes a fixed template evaluation value calculated by comparing the input ECG waveform with the fixed template, the input ECG waveform, and the two or more waveform templates stored in the storage unit. Detecting the R wave based on the evaluation value calculated by comparing
The signal processing device according to claim 8 . The biological signal includes at least one of an ECG signal, a pulse wave signal, and a heart sound signal,
The signal processing device according to claim 1 . The biological signal is a vector cardiogram including two or more ECG signals,
A coordinate conversion unit that performs coordinate conversion on the vector cardiogram,
The detection unit generates the synchronization signal from one or two or more ECG signals after coordinate conversion,
The signal processing device according to claim 1. A generation unit that generates a detection parameter for detecting a specific waveform in a biological signal related to a heartbeat based on the waveform of the biological signal,
A storage unit for storing two or more generated detection parameters,
A detection unit that detects the specific waveform using the stored two or more detection parameters and generates a synchronization signal for performing heartbeat synchronous imaging;
An updating unit that updates the two or more detection parameters stored in the storage unit;
A generation determining unit;
In synchronization with the synchronization signal, a data collection unit that collects data for imaging from the subject,
From the collected data for imaging, an image generating unit that generates an image of the subject,
Equipped with a,
The generating unit sequentially generates new detection parameters from the biological signal input in time series,
The generation determination unit monitors an operation state of an imaging device connected to the outside, and determines whether to generate the new detection parameter in the generation unit according to the operation state of the imaging device,
The updating unit updates the detection parameters stored in the storage unit with the generated new detection parameters,
Imaging device. The imaging device is an MRI device;
The imaging device according to claim 13 . The biological signal includes at least one of an ECG signal, a pulse wave signal, and a heart sound signal,
The imaging device according to claim 13 . The biological signal is a vector cardiogram including two or more ECG signals,
A coordinate conversion unit that performs coordinate conversion on the vector cardiogram,
The detection unit generates the synchronization signal from one or two or more ECG signals after coordinate conversion,
The imaging device according to claim 13 . Generating a detection parameter for detecting a specific waveform in a biological signal related to a heartbeat based on the biological signal ;
Storing two or more of the generated detection parameters ;
Updating the stored two or more detection parameters;
Determining;
Detecting the specific waveform using the stored two or more detection parameters, and generating a synchronization signal for performing ECG-gated imaging ;
Prepared,
In the step of generating the detection parameters, a new detection parameter is sequentially generated from the biological signal input in time series,
In the determining step, monitor the operation state of the imaging device connected to the outside, according to the operation state of the imaging device, determine whether to generate the new detection parameters,
In the updating step, the detection parameter stored in the storage unit is updated by the generated new detection parameter,
Signal processing method. The biological signal is a vector cardiogram including two or more ECG signals,
Transforming the vector cardiogram and generating the synchronization signal from one or more ECG signals after the coordinate transformation;
The signal processing method according to claim 17 .

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