A computer is caused to execute an acquisition step of acquiring a plurality of pieces of fibrillation wave electrocardiogram data including a fibrillation wave from overall electrocardiogram data obtained by measuring temporal changes of an activity potential during an electrical activity of cardiac muscle; and an output step of outputting clear electrocardiogram data from the acquired plurality of pieces of fibrillation wave electrocardiogram data, the clear electrocardiogram data being electrocardiogram data in which amplitude of the fibrillation wave is within a predetermined range, a symptom of tachycardia is not observed, and noise in a frequency range which is higher than a frequency range of the fibrillation wave and with amplitude which is equal to or greater than predetermined amplitude is not superimposed.
A61B 5/00 - Measuring for diagnostic purposes Identification of persons
G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
2.
INFORMATION PROCESSING DEVICE, INFORMATION PROCESSING METHOD, AND PROGRAM
The present invention addresses the problem of processing motion information, such as an electrocardiogram, which shows a plurality of repetitive motions of a living organism, and analyzing waveforms that indicate each of the plurality of motions. An information processing device according to the present disclosure includes at least one processor and processes motion information indicating a plurality of repetitive motions of a living organism. The at least one processor is configured to: acquire the motion information; divide the acquired motion information into a plurality of pieces of first waveform information respectively indicating waveforms of the plurality of repetitive motions; cluster the plurality of pieces of first waveform information into a plurality of clusters respectively containing the plurality of pieces of the first waveform information; select, from the first waveform information included in the respective clusters, one or more pieces of second waveform information indicating waveforms that are representative of the waveforms indicated by the first waveform information included in the respective clusters; and execute a process for displaying, on at least one screen, a list of the plurality of pieces of second waveform information indicating the waveforms that are representative of the respective clusters.
This computer is configured to execute an acquisition step for acquiring more than one fibrillation wave electrocardiogram data including fibrillation waves among overall electrocardiogram data obtained by measuring a change of action potential over time associated with electric activities of the cardiac muscle and an output step for outputting, among the acquired more than one fibrillation wave electrocardiogram data, unambiguous electrocardiogram data in which the amplitudes of the fibrillation waves are within a prescribed range, symptoms of tachycardia are not exhibited and no noise of an amplitude at or above a prescribed amplitude is superimposed in a frequency range higher than the frequency range of the fibrillation waves.
An electrocardiogram analyzing apparatus has: an acquiring section acquiring a plurality of electrocardiogram waveforms; a classifying section classifying the plurality of electrocardiogram waveforms into a plurality of groups on a basis of shape similarity; an accepting section accepting a reference position of a predetermined type of wave designated on a representative waveform corresponding to at least one electrocardiogram waveform belonging to a selection group selected from the plurality of groups; and an analyzing section identifying correspondence between a plurality of positions, along a time axis, on the representative waveform of a group to which a subject-of-analysis electrocardiogram waveform belongs, and a plurality of positions on the subject-of-analysis electrocardiogram waveform along a time axis, and decides, as a position of the predetermined type of wave included in the subject-of-analysis electrocardiogram waveform, a position on the subject-of-analysis electrocardiogram waveform corresponding to the reference position on the representative waveform represented by the correspondence.
A display control apparatus includes an acquisition part that acquires a value indicating the electric activity of the heart of a person to be analyzed, and a display control part that causes a display part to display a plurality of points corresponding to a plurality of values measured in a target period, wherein a distance between the predetermined reference point and each of the plurality of points corresponds to the value corresponding to the point, and a direction of a vector from the reference point to each of the plurality of points rotates clockwise or counterclockwise about the reference point in the order of times at which the plurality of values are measured.
G16H 40/63 - ICT specially adapted for the management or administration of healthcare resources or facilitiesICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices for local operation
6.
ELECTROCARDIOGRAPHIC ANALYSIS DEVICE, ELECTROCARDIOGRAPHIC ANALYSIS METHOD, AND PROGRAM
An electrocardiographic analysis device (3) comprises: an acquisition unit (331) that acquires a plurality of electrocardiogram waveforms generated by separating electrocardiogram data beat by beat; a classification unit (332) that classifies the plurality of electrocardiogram waveforms into a plurality of groups on the basis of similarity of shape; a reception unit (333) that receives a reference position of a wave of a predetermined type that has been specified in a representative waveform corresponding to at least one electrocardiogram waveform belonging to a selection group selected from among the plurality of groups; and an analysis unit (335) that identifies a correspondence relationship between a plurality of positions on a time axis of the representative waveform of the group to which the electrocardiogram waveform to be analyzed belongs and a plurality of positions on a time axis of the electrocardiogram waveform to be analyzed, and determines, as the position of a wave of a predetermined type included in the electrocardiogram waveform to be analyzed, a position in the electrocardiogram waveform to be analyzed, the position thereof corresponding to the reference position of the representative waveform and indicated by the correspondence relationship.
A data processing method including the computer-implemented steps of: acquiring one or more pieces of fibrillation wave electrocardiogram data including fibrillation waves included in whole electrocardiogram data obtained by measuring change over time of an action potential due to electric activity of a heart muscle; inputting the one or more pieces of fibrillation wave electrocardiogram data into a first machine learning model that classifies a plurality of pieces of electrocardiogram data including the fibrillation waves into electrocardiogram data in which the fibrillation waves are clear and electrocardiogram data in which the fibrillation waves are unclear, and acquiring clear electrocardiogram data output from the first machine learning model as the electrocardiogram data in which the fibrillation waves are clear; and outputting the clear electrocardiogram data.
A display control device 3 according to an embodiment of the present invention comprises: an acquisition unit 331 that acquires a value indicating electrical activity of the heart of a person being analyzed; and a display control unit 335 that displays, on a display unit, a plurality of points corresponding to a plurality of values measured during a target period. The distances between a prescribed reference point and each of the plurality of points correspond to the values corresponding to said points, and the orientation of vectors from the reference point to each of the plurality of points rotates, about the reference point, in a clockwise or counterclockwise manner in the order of the times at which the plurality of values were measured.
In the present invention, a computer is made to execute: a step for acquiring one or more items of fibrillation wave electrocardiogram data including fibrillation waves, included in whole electrocardiogram data obtained by measuring temporal changes in action potential associated with cardiac muscle electrical activity; a step for inputting the one or more items of fibrillation wave electrocardiogram data into a first machine learning model for categorizing a plurality of items of electrocardiogram data including fibrillation waves into electrocardiogram data in which fibrillation waves are clear and electrocardiogram data in which fibrillation waves are unclear, and acquiring, from the first machine learning model, clear electrocardiogram data outputted as electrocardiogram data in which fibrillation waves are clear; and a step for outputting the clear electrocardiogram data.
An electrocardiogram analysis apparatus includes a machine learning part that has a machine learning model realized by machine learning that uses training electrocardiogram data of a patient with paroxysmal arrhythmia during a non-paroxysmal period during which no episode of paroxysmal arrhythmia occurs; an input processing part that inputs electrocardiogram data of a person to be analyzed, which is a subject of analysis, into the machine learning model; and an output control part that outputs, to an information terminal, abnormality information which is to be output from the machine learning model and is about whether the person to be analyzed has paroxysmal arrhythmia.
A method used for determining at least one of an administration method or a dosage of a drug that can be administered to a patient, the method executed by a processor and including: acquiring electrocardiogram data indicating an electrocardiogram of a patient who is given the drug with the administration method and the dosage; determining, on the basis of the electrocardiogram data, whether a waveform abnormality that can be evaluated with an electrocardiogram may have occurred in the patient; and outputting information about advisability of modifying at least one of the administration method or the dosage on the basis of a result of the determining.
G16H 20/10 - ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients
A61B 5/00 - Measuring for diagnostic purposes Identification of persons
09 - Scientific and electric apparatus and instruments
Goods & Services
Downloadable computer programs for medical use provided via
the Internet; downloadable electrocardiogram analyzing
computer programs for medical use provided via the Internet;
computer programs for medical use recorded in digital form;
electrocardiogram analyzing computer programs for medical
purposes recorded in digital form.
13.
ELECTROCARDIOGRAM DISPLAY APPARATUS, METHOD FOR DISPLAYING ELECTROCARDIOGRAM, AND STORAGE MEDIUM STORING PROGRAM
An electrocardiogram display apparatus includes an input processing part that inputs divided electrocardiogram data, which is obtained by dividing whole electrocardiogram data of a patient that has been measured over a predetermined time period into electrocardiogram data having a predetermined time length shorter than the predetermined time period, into a machine learning model realized by machine learning that uses a plurality of pieces of training electrocardiogram data each having the predetermined time length; a result acquisition part that acquires, from the machine learning model, a determination result indicating whether or not the divided electrocardiogram data includes a waveform portion suspected of indicating heart disease; and a display controlling part that causes a display apparatus to display information based on the determination result.
G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
14.
ELECTROCARDIOGRAPHIC ANALYSIS DEVICE, ELECTROCARDIOGRAPHIC ANALYSIS METHOD, AND PROGRAM
An electrocardiographic analysis device (3) according to an embodiment of the present invention includes: a machine learning unit (33) that has a machine learning model which has machine-learned using electrocardiogram training data taken from a paroxysmal arrhythmia patient during a non-paroxysmal period in which an episode of paroxysmal arrhythmia does not occur; an input processing unit (341) that inputs, into the machine learning model, electrocardiogram data of an analysis subject which is to be analyzed; and an output control unit (343) that outputs, to an information terminal, anomaly information which is output from the machine learning model and which pertains to whether the analysis subject has paroxysmal arrhythmia.
The present invention enables a health care professional to identify more suitably for a patient at least one of the dosage form and dosage of a drug. A method according to the present invention is used to determine at least one of the dosage form and dosage of a drug which can be administered to a patient, the method including the following steps carried out by a processor: a step for acquiring electrocardiogram data showing an electrocardiogram of the patient to whom a drug has been administered according to a dosage and a dosage form and who is going about daily life; and a step for determining, on the basis of the electrocardiogram data, whether waveform anomalies which can be evaluated from the electrocardiogram may be occurring in the patient, and outputting, on the basis of the result of the determination, information pertaining to whether it is possible to change at least one of the dosage and the dosage form.
G16H 20/10 - ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients
16.
ELECTROCARDIOGRAM DISPLAY DEVICE, ELECTROCARDIOGRAM DISPLAY METHOD, AND PROGRAM
This electrocardiogram display device (3) includes: an input processing unit (341) which inputs divided electrocardiogram data, which is obtained by dividing complete electrocardiogram data obtained by measuring a patient during a prescribed period into the electrocardiogram data of a prescribed time length shorter than the prescribed period, to a machine learning model machine-learnt by using a plurality of teacher electrocardiogram data of the prescribed time length; a result acquisition unit (342) which acquires a determination result that indicates whether a waveform portion thought to indicate heart failure is included in the divided electrocardiogram data output from the machine learning unit (33); and a display control unit (343) which specifies, from the plurality of divided electrocardiogram data, one or more abnormal electrocardiogram data in which the waveform portion thought to indicate heart failure is included, on the basis of the determination result, and causes a waveform image corresponding to at least some data among the one or more abnormal electrocardiogram data among the specified one or more abnormal electrocardiogram data to be displayed in a doctor's terminal (2).
