CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a National Stage application under 35 U.S.C. § 371 of International Application No. PCT/JP2019/020321, having an International Filing Date of May 22, 2019, which claims priority to Japanese Application Serial No. 2018-099962, filed on May 24, 2018. The disclosure of the prior application is considered part of the disclosure of this application, and is incorporated in its entirety into this application.

TECHNICAL FIELD

Embodiments of the present invention relate to an instantaneous heartbeat reliability evaluation apparatus, method, and a program.

BACKGROUND ART

Autonomic nerves are divided into two types of nerves, sympathetic nerves and vagus nerves. The sympathetic nerves and the vagus nerves are widely distributed in organs and the like and control involuntary physical functions including circulation and metabolism. In many cases, it is said that the sympathetic nerves and the vagus nerves antagonistically control one organ.

It is known that sympathetic neural activity that is a kind of autonomic neural activity is exacerbated by stress stimuli such as a mental arithmetic load.

Meanwhile, vagus neural activity that is another kind of autonomic neural activity is understood as the same as parasympathetic neural activity in many cases because the vagus nerve mainly takes charge of parasympathetic neural activity in each organ.

In a strict sense, the vagus nerve is the name of the tenth cranial nerve and includes all nerves extending from the brain to organs.

Accordingly, there are cases in which parasympathetic neural activity in an organ that is a control target is indicated by adding the name of the target organ, such as a heart vagus nerve, for example.

The heart may be mentioned as an example of an organ controlled by autonomic nerves. The heart is antagonistically controlled by the sympathetic nerve and the vagus nerve and is said to reflect a static balance between sympathetic neural activity and vagus neural activity.

FIG. 9is a diagram showing an example of instantaneous heartbeat (RRI: R-R interval). It is known that variation in the instantaneous heartbeat that is an interval between two neighboring R waves in a time series (hereinafter simply referred to as “neighboring” in some cases) as shown inFIG. 9changes according to both the sympathetic neural activity and the vagus neural activity.

Meanwhile, an R wave is a kind of electrocardiographic waveform obtained through electrocardiogram (ECG) measurement and reflects the depolarization activity of the heart.

As a method of estimating autonomic neural activity in a real environment, frequency spectrum analysis of instantaneous heartbeat variation is conceivable. According to this method, a low-frequency component (hereinafter, HRVLF) when instantaneous heartbeats that are unequal intervals are analyzed using a frequency spectrum is interpreted as an index reflecting sympathetic neural activity and a heart vagus neural activity.

Furthermore, a high-frequency component (hereinafter, HRVHF) when instantaneous heartbeats are analyzed using a frequency spectrum is interpreted as an index reflecting a heart vagus neural activity.

As means for measuring an ECG, a wearable device such as a Holter electrocardiograph is conceivable. In an ECG acquired using this device, measurement abnormalities occur due to electrode abnormalities including deformation and deviation of electrodes or various factors such as body motion, perspiration, and static electricity.

FIG. 10is a diagram showing an example of measurement abnormalities in an ECG. Measurement abnormalities in an ECG can be confirmed from shapes such as noise W1and artifacts (abnormal measurement state) W2as shown inFIG. 10. Further, durations of the noise and artifacts change according to a duration of measurement abnormalities.

As shown inFIG. 10, waveforms observed as artifacts have frequency characteristics extremely similar to frequency characteristics of R waves, and thus it is very difficult to completely remove these waveforms through normal filtering.

Accordingly, an algorithm for extracting R waves through ECG analysis may erroneously determine artifacts as R waves and unnecessarily extract the artifacts as the R waves.

HRVLFand HRVHFreflect autonomic neural activity only in cases in which all data that is an analysis target represents a normal instantaneous heartbeat. A normal instantaneous heartbeat is an instantaneous heartbeat when both a measurement target and a measuring instrument have no abnormalities.

Abnormalities of a measurement target include the arrhythmia of an examinee, and the like. Abnormalities of a measuring instrument include states in which measurement abnormalities occur in an ECG.

Waveforms that are artifacts erroneously determined as R waves, which are a kind of measurement abnormality (such waveforms will be represented as measurement abnormality R waves below), do not completely reflect the depolarization activity of the heart from the generation mechanism thereof.

Accordingly, when at least one of a plurality of R waves constituting an instantaneous heartbeat that is an analysis target is an R wave erroneously determined from an artifact, it cannot be said that HRVLFor HRVHFreflects autonomic neural activity.

Methods for coping with measurement abnormalities of an ECG are broadly classified into two methods: reduction of the influence of measurement abnormalities according to filtering and the like; and detection of a measurement abnormality generation part.

The latter method of detecting a measurement abnormality generation part is a method which focuses on the fact that former methods of reducing the influence of measurement abnormalities according to filtering and the like could not be appropriately performed particularly when artifacts were generated and attempts to detect a measurement abnormality generation part using statistical information of ECG potential information (hereinafter referred to as conventional method a).

There are methods using a time feature quantity of an instantaneous heartbeat (refer to Non-Patent Literature 1 to 3, for example) (hereinafter referred to as conventional method b) and a method based on a measurement state and a time feature quantity of an instantaneous heartbeat (refer to Non-Patent Literature 4, for example) (hereinafter referred to as conventional method c) as methods of excluding abnormal values of an instantaneous heartbeat.

As a specific example of conventional method b, there is a method of setting threshold values to difference values between a lower limit value and an upper limit value of an instantaneous heartbeat and neighboring instantaneous heartbeat values in a time series and excluding an instantaneous heartbeat departing from the threshold values, and methods of excluding waveforms deviating from a normal distribution of an instantaneous heartbeat.

Among the methods of excluding waveforms deviating from a normal distribution of an instantaneous heartbeat, abnormal value detection according to “average of instantaneous heartbeat±standard deviation” is the simplest method, and a2aor3arule is generally used in many cases.

As a specific example of conventional method c, there is an example of identifying a measurement state of an instantaneous heartbeat on the basis of potential amplitude information of R waves, excluding an instantaneous heartbeat identified as an abnormality, and then sequentially applying exclusion using a lower limit value and an upper limit value which is the conventional method b and3arule. Here, a measurement state of an instantaneous heartbeat is evaluated on the basis of potential amplitudes of R waves constituting the instantaneous heartbeat.

CITATION LIST

Non Patent Literature

[NPL 1] Sakuma Daiki, Kanda Naoko, Yoshimi Masato, Yoshinaga Tutomu, and Irie Hidetugu, “A Real-Time Realization System at Sitting Position using Heart Rate Measurement”, Multimedia, Distributed Coordination and Mobile Symposium 2013 collected papers, pp. 1188-1195, 2013[NPL 2] Yokota Yasunari, Kawamura Yoko, Matsumaru Naoki, and Shirai Kunihito, “Monitoring of sepsis premonitories using time series of heart rate variability”, Fifty-fourth automatic control alliance conference, pp. 1258-1261, 2011[NPL 3] Eguchi Kana, Tsunoda Keisuke, Yabuuchi Tsutomu, Yoshida Kazuhiro, Watanabe Tomoki, and Mizuno Osamu, “Non-filterable noise detection method for wearable ECG devices”, IEICE Technical Report, Vol. 115, No. 345, pp. 27-32, 2015[NPL4] EguchiKana, AokiRyosuke, YoshidaKazuhiro, and Yamada Tomohiro, “Reliability Evaluation of R-R Interval Measurement Status using the Electric Potential Characteristics of QRS Complex for Wearable ECG Devices”, IEICE Technical Report, Vol. 116, No. 412, pp. 171-176, 2017

SUMMARY OF THE INVENTION

Technical Problem

Although the conventional method a is a method focusing on the fact that measurement abnormalities of an ECG occur mainly due to potential differences, it uses ECG statistical information divided into two types of durations, long-term durations and short-term durations. Accordingly, a measurement state of any divided ECG is identified using statistical information of a long-term divided ECG following a long-term divided ECG including the divided ECG in a time series, and thus a time set in a long-term duration is required to identify a measurement state.

In conventional method a, when measurement abnormalities do not occur, comparative evaluation according to statistical information of a certain divided ECG and another divided ECG in a time series is performed with respect to comparison other than comparisons with a plurality of previously determined divided ECGs. Since this comparison is based on whether a potential amplitude of a certain divided ECG is an integer multiple of a potential amplitude of a divided ECG set as reference information, if measurement abnormalities are generated in the corresponding ECG, it may be difficult to reduce the influence of the measurement abnormalities.

It is difficult to dynamically set threshold values because instantaneous heartbeat values change over time. That is, when abnormal values of an instantaneous heartbeat are within a pathologically normal range, the instantaneous heartbeat cannot be generally detected as an abnormality in conventional method b.

In the above-described method of excluding waveforms deviating from a normal distribution of an instantaneous heartbeat, threshold values are set on the basis of various statistics including averages, standard deviations, median values, and quartiles because values deviating from the normal distribution are detected. Although it is necessary to calculate such statistics for a normal instantaneous heartbeat in order to identify abnormal values, a normal instantaneous heartbeat cannot be specified in this step. Accordingly, when an abnormal instantaneous heartbeat increases, the presence of such instantaneous heartbeat is regarded as normal and thus the instantaneous heartbeat cannot be detected as an abnormality.

In conventional method b, abnormalities of a measuring instrument are not considered. That is, when a duration of an instantaneous heartbeat including at least one waveform as an artifact erroneously determined as an R wave is pathologically normal or when a duration is within a normal distribution assumed for a normal instantaneous heartbeat, it is impossible to detect an abnormal instantaneous heartbeat through the conventional method.

In conventional method c, some problems of the conventional method b and problems of general filtering are solved using potential information. However, measurement abnormalities generated in an ECG do not necessarily have potential amplitude characteristics different from those of R waves. Particularly, an instantaneous heartbeat erroneously determined as R waves due to the same potential amplitude characteristics as those of R waves, such as myoelectric artifacts, cannot be detected as an abnormality.

An object of the present invention devised in view of the aforementioned circumstances is to provide an instantaneous heartbeat reliability evaluation apparatus, method, and a program which can appropriately realize identification of abnormalities of biosignals.

Means for Solving the Problem

In a first aspect of an instantaneous heartbeat reliability evaluation apparatus according to an embodiment of the present invention to accomplish the aforementioned object, the instantaneous heartbeat reliability evaluation apparatus includes: extraction means which extracts waveforms having a maximum value corresponding to depolarization of a heart in a biosignal of an examinee on the basis of a signal output from measurement means for measuring the biosignal of the examinee; first calculation means which calculates an interval between two of the waveforms neighboring in a time series and extracted by the extraction means; dividing means which divides a signal output from the measurement means into signals of predetermined periods; second calculation means which calculates feature quantities of a potential of each signal divided by the dividing means; first evaluation means which evaluates whether a measurement state of each signal divided by the dividing means is normal or abnormal on the basis of the feature quantities calculated by the second calculation means; and second evaluation means which evaluates measurement states of the two neighboring waveforms extracted by the extraction means on the basis of an evaluation result obtained by the first evaluation means and evaluates reliability of a measurement state of the interval between the waveforms calculated by the first calculation means depending on a type of the evaluated measurement states of the waveforms.

In a second aspect of the instantaneous heartbeat reliability evaluation apparatus of the present invention, in the first aspect, the second calculation means calculates at least one of a first feature quantity representing a magnitude of a potential of each of the divided signals for the signals divided by the dividing means, a second feature quantity representing variation in the potential of each of the divided signals for the signals divided by the dividing means, and a third feature quantity representing change in a time series in the potential of each of the divided signals for the signals divided by the dividing means, and the first evaluation means evaluates, on the basis of feature quantities calculated by the second calculation means with respect to a signal of an evaluation target that is one of the signals divided by the dividing means, and feature quantities calculated by the second calculation means with respect to another signal belonging to a set of signals successive in a time series including the signal of the evaluation target, whether a measurement state of the signal of the evaluation target is likely to be normal or likely to be abnormal for each of types of the feature quantities calculated by the second calculation means, and evaluates whether measurement states of the signals divided by the dividing means are normal or abnormal on the basis of an evaluation result for each feature quantity type.

In a third aspect of the instantaneous heartbeat reliability evaluation apparatus of the present invention, in the first aspect, the second calculation means calculates at least one of a first feature quantity representing a magnitude of a potential of each of the divided signals for the signals divided by the dividing means, a second feature quantity representing variation in the potential of each of the divided signals for the signals divided by the dividing means, and a third feature quantity representing change in a time series in the potential of each of the divided signals for the signals divided by the dividing means, and the first evaluation means evaluates, on the basis of feature quantities calculated by the second calculation means with respect to a signal of an evaluation target that is one of the signals divided by the dividing means, and feature quantities calculated by the second calculation means with respect to a signal neighboring the signal of the evaluation target in a time series, whether a measurement state of the signal of the evaluation target is likely to be normal or likely to be abnormal for each of types of the feature quantities calculated by the second calculation means, and evaluates whether measurement states of the signals divided by the dividing means are normal or abnormal on the basis of an evaluation result for each feature quantity type.

In a fourth aspect of the instantaneous heartbeat reliability evaluation apparatus of the present invention, in the first aspect, the second calculation means calculates at least one of a first feature quantity representing a magnitude of a potential of each of the divided signals for the signals divided by the dividing means, a second feature quantity representing variation in the potential of each of the divided signals for the signals divided by the dividing means, and a third feature quantity representing change in a time series in the potential of each of the divided signals for the signals divided by the dividing means, and the first evaluation means evaluates, on the basis of feature quantities calculated by the second calculation means with respect to a signal of an evaluation target that is one of the signals divided by the dividing means, and feature quantities calculated by the second calculation means with respect to a signal for which a measurement state has been evaluated as normal in advance among the signals divided by the dividing means, whether a measurement state of the signal of the evaluation target is likely to be normal or likely to be abnormal for each of types of the feature quantities calculated by the second calculation means, and evaluates whether measurement states of the signals divided by the dividing means are normal or abnormal on the basis of an evaluation result for each feature quantity type.

In a fifth aspect of the instantaneous heartbeat reliability evaluation apparatus of the present invention, in the first aspect, the second calculation means calculates at least one of a first feature quantity representing a magnitude of a potential of each of the divided signals for the signals divided by the dividing means, a second feature quantity representing variation in the potential of each of the divided signals for the signals divided by the dividing means, and a third feature quantity representing change in a time series in the potential of each of the divided signals for the signals divided by the dividing means, and the first evaluation means acquires, on the basis of feature quantities calculated by the second calculation means with respect to a signal of an evaluation target that is one of the signals divided by the dividing means, and feature quantities calculated by the second calculation means with respect to another signal belonging to a set of signals successive in a time series including the signal of the evaluation target, a first evaluation result representing whether a measurement state of the signal of the evaluation target is likely to be normal or likely to be abnormal for each of types of the feature quantities calculated by the second calculation means, acquires a second evaluation result representing whether a measurement state of the signal of the evaluation target is likely to be normal or likely to be abnormal for each of types of the feature quantities calculated by the second calculation means on the basis of feature quantities calculated by the second calculation means with respect to the signal of the evaluation target that is one of the signals divided by the dividing mean, and feature quantities calculated by the second calculation means with respect to a signal neighboring the signal of the evaluation target in a time series, acquires a third evaluation result representing whether a measurement state of the signal of the evaluation target is likely to be normal or likely to be abnormal for each of types of the feature quantities calculated by the second calculation means on the basis of feature quantities calculated by the second calculation means with respect to the signal of the evaluation target, and feature quantities calculated by the second calculation means with respect to a signal for which a measurement state has been evaluated as normal in advance, and evaluates the measurement state of the signal of the evaluation target as abnormal when at least one of the first, second and third evaluation results represents that the measurement state of the signal of the evaluation target is likely to be abnormal.

In a sixth aspect of the instantaneous heartbeat reliability evaluation apparatus of the present invention, in the first aspect, the second evaluation means evaluates the measurement states of the waveforms extracted by the extraction means as abnormal from a signal for which a measurement state has been evaluated as abnormal by the first evaluation means, and evaluates the measurement states of the waveforms extracted by the extraction means as normal from a signal for which a measurement state has been evaluated as normal by the first evaluation means.

An aspect of an instantaneous heartbeat reliability evaluation method performed by an instantaneous heartbeat reliability evaluation apparatus according to an embodiment of the present invention includes: extracting waveforms having a maximum value corresponding to depolarization of a heart in a biosignal of an examinee; calculating an interval between two of the extracted waveforms neighboring in a time series; dividing the biosignal into signals of predetermined periods; calculating feature quantities of a potential of each of the divided signals; evaluating whether a measurement state of each of the divided signals is normal or abnormal on the basis of the calculated feature quantities; evaluating measurement states of the two neighboring extracted waveforms on the basis of an evaluation result of a measurement state of each of the divided signals; and evaluating reliability of a measurement state of the calculated interval between the waveforms depending on a type of the evaluated measurement states of the waveforms.

An aspect of an instantaneous heartbeat reliability evaluation processing program according to an embodiment of the present invention causes a processor to function as each means of the instantaneous heartbeat reliability evaluation apparatus according to any one of the first to sixth aspects.

Effects of the Invention

According to the first aspect of the instantaneous heartbeat reliability evaluation apparatus according to an embodiment of the present invention, a measurement state of an interval between waveforms having a maximum value corresponding to depolarization of a heart is evaluated on the basis of evaluation results of measurement states of divided biosignals, and thus it is possible to reduce the influence of a measurement state of a biosignal on evaluation of the measurement state of the interval between the waveforms having the maximum value corresponding to depolarization of the heart.

According to the second aspect of the instantaneous heartbeat reliability evaluation apparatus according to an embodiment of the present invention, it is evaluated whether measurement states of divided signals are likely to be normal or abnormal for each feature quantity type and it is evaluated whether the measurement states of the divided signals are normal or abnormal on the basis of an evaluation result for each feature quantity type, and thus it is possible to improve the accuracy of evaluation of a measurement state of a biosignal.

According to the third to fifth aspects of the instantaneous heartbeat reliability evaluation apparatus according to an embodiment of the present invention, a measurement state of a signal that is an evaluation target is evaluated on the basis of feature quantities of signals positioned before and after the evaluation target signal in a time series or a signal for which a measurement state has been evaluated as normal in advance, and thus it is possible to reduce a time taken to evaluate a measurement state calculated with respect to the evaluation target signal that is one of divided signals.

According to the sixth aspect of the instantaneous heartbeat reliability evaluation apparatus according to an embodiment of the present invention, measurement states of waveforms having a maximum value corresponding to depolarization of a heart are evaluated on the basis of an evaluation result of a measurement state of a biosignal that is an evaluation target, and thus it is possible to appropriately evaluate the measurement states of the waveforms having the maximum value corresponding to depolarization of the heart on the basis of feature quantities of potentials of signals divided from the biosignal.

That is, according to the present invention, it is possible to realize appropriate biosignal abnormality identification.

