EP4583783A1 - Verfahren zum ermitteln eines magnetokardiogrammsignals eines lebewesens - Google Patents
Verfahren zum ermitteln eines magnetokardiogrammsignals eines lebewesensInfo
- Publication number
- EP4583783A1 EP4583783A1 EP23761465.6A EP23761465A EP4583783A1 EP 4583783 A1 EP4583783 A1 EP 4583783A1 EP 23761465 A EP23761465 A EP 23761465A EP 4583783 A1 EP4583783 A1 EP 4583783A1
- Authority
- EP
- European Patent Office
- Prior art keywords
- signal
- magnetic
- field strength
- living
- sensor unit
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Classifications
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
- A61B5/242—Detecting biomagnetic fields, e.g. magnetic fields produced by bioelectric currents
- A61B5/243—Detecting biomagnetic fields, e.g. magnetic fields produced by bioelectric currents specially adapted for magnetocardiographic [MCG] signals
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/68—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient
- A61B5/6887—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient mounted on external non-worn devices, e.g. non-medical devices
- A61B5/6892—Mats
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
- A61B5/7235—Details of waveform analysis
- A61B5/7264—Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems
Definitions
- the invention relates to a method for determining a magnetocardiogram signal of a living being, a device for determining a magnetocardiogram signal of a living being, a computer program and a machine-readable storage medium.
- the object underlying the invention is to provide a concept for efficiently determining a magnetocardiogram signal of a living being.
- a method for determining a magnetocardiogram signal of a living being comprising the following
- a computer program which comprises instructions which, when the computer program is executed by a computer, for example by the device according to the second aspect, cause the computer to carry out a method according to the first aspect.
- the invention is based on and includes the knowledge that the above object is achieved in that a magnetic field strength is detected by the sensor unit, it being determined that this magnetic field strength is a reference field strength, i.e. a reference .
- the magnetic measuring field strength is subsequently recorded by the sensor unit in the presence of a living being in the vicinity of the sensor unit.
- the Magnetocardiogram signal of the living being is determined based on this recorded magnetic measuring field strength as well as on the previously determined or set reference.
- the magnetic measuring field strength recorded by the sensor unit in the presence of a living being in the vicinity of the sensor unit comes not only from the magnetic field of the heart, but also from other magnetic fields, for example the earth's magnetic field or for example from electrical devices, for example household appliances .
- Such magnetic fields form interference magnetic fields for the measurement of a cardiac magnetic field.
- the living being is, for example, a human or is, for example, an animal.
- MKG magnetictocardiogram
- a magnetic disturbance is determined in the environment of the sensor unit, which is taken into account when determining the magnetocardiogram signal.
- a magnetic interference can result, for example, from the operation of an electrical device in the vicinity of the sensor unit.
- an electrical device is, for example, an electrical household appliance or is, for example, a drive motor for an electric roller shutter.
- the sensor unit is located in a vehicle, for example a motor vehicle or an aircraft, such magnetic interference can result from operation of the vehicle.
- such a magnetic interference can result from an electrically driven rail vehicle that travels in the vicinity of the sensor unit.
- the power consumption of such a rail vehicle can create magnetic fields that can disrupt the MCG measurement.
- the signal to be determined based on the magnetic reference field strength i.e. the background signal and/or the interference signal
- the signal to be determined based on the magnetic reference field strength is filtered out of a measurement signal representing the detected magnetic measurement field strength in order to obtain a filtered measurement signal, the magnetocardiogram signal being based is determined on the filtered measurement signal.
- the magnetocardiogram signal can be determined efficiently. According to this embodiment, it is therefore provided that the magnetic background and/or the magnetic interference are filtered out of the detected magnetic measuring field strength.
- At least one time interval is determined, in particular estimated, within which the magnetic disturbance occurs and/or will occur, with only a magnetic measuring field strength detected outside the at least one time interval being used to determine the magnetocardiogram signal .
- the magnetocardiogram signal can be determined efficiently. According to this embodiment it is therefore provided that detected magnetic disturbances are not taken into account when determining the magnetocardiogram signal. On the one hand, measurements can only be carried out outside the time interval, i.e. the magnetocardiogram measurement can be carried out. On the other hand, an MKG measurement that was carried out within the time interval can additionally or alternatively not be taken into account when determining the magnetocardiogram signal. In one embodiment of the method it is provided that at least one vital parameter of the living being is determined based on the magnetocardiogram signal.
- Fig. 4 measured several interference signals over several nights in a row.
- the detection of such interference fields can be detected, for example, using a machine learning algorithm or using artificial intelligence.
- a pattern recognition method can be used to create patterns in the magnetic reference field strengths recognize, which can then be filtered out from the then existing measurement signal in the following nights, night 2 to night 4, for example.
- a reference measurement is initially carried out, for example a measurement of magnetic reference field strengths, for example over a night without any living being being in the vicinity of the sensor unit.
- the environment of the sensor unit can also generally be referred to as a measuring area.
- a magnetocardiogram measurement can then be carried out on a living being that is in the measurement area in the following nights. This means that a magnetic measuring field strength is detected by the sensor unit when the living being is in the vicinity of the sensor unit.
- the fact that the reference measurement can be carried out over the course of one night is to be understood as an example. Shorter periods of time, for example a few minutes, can also be provided. For example, a few minutes are enough during a self-calibration of the sensor unit and/or the device. This means, for example, that an embodiment of the method is carried out during a self-calibration of the sensor unit and/or the device. This means in particular that method steps are carried out, for example, during a self-calibration of the sensor unit and/or the device. A few minutes are sufficient, for example, if the method is or is to be used in a vehicle, for example a motor vehicle, or in a hospital.
- the magnetic reference field strength is subtracted from the measured magnetic measuring field strength. This is particularly synchronous with the time of day, generally synchronous with the time.
- the reference signal is subtracted from the measurement signal, with the magnetocardiogram signal being determined, for example, based on the correspondingly subtracted measurement signal.
- corresponding filters are provided which filter out these interference signals and/or background signals from the measurement signals.
- interference signals that always occur at the same time can be efficiently filtered out.
- a magnetic interference caused by a drive motor of an electric roller shutter can be efficiently filtered out.
- the roller shutter is raised or lowered at a certain time, so that an interference signal is to be expected at these times, so that this interference signal can be filtered out in the measurement signal at these times.
- patterns in the magnetic reference field strengths can be recognized. Such patterns can also be learned when the interference signal occurs. This means that if it is known that a disturbance always occurs at the same time, then the time course of the magnetic reference field strength at these times is defined as a pattern to be filtered out.
- An example is when an electrically driven rail vehicle travels in the vicinity of the sensor unit at approximately the same or similar times and thus disrupts the M KG measurement due to current consumption for the drive motor.
- the filters for data evaluation can be adapted efficiently for certain times of the day or night.
- Classic pattern recognition methods can be used and/or machine learning can be used.
- characteristic noise patterns can be identified in the reference data, i.e. in the recorded magnetic reference field strength, for example a rail vehicle passing by, for example a tram, or an elevator moving.
- the recognized noise patterns can then be subtracted from the measured signal, i.e. the measurement signal, for noise suppression, or the corresponding filter criteria can be trained.
- time periods with reduced functionality with regard to an MCG measurement can, for example, be identified. This makes it possible not to take these time periods into account for further analyzes or to provide feedback about the non-functionality of the device with regard to the MKG measurement. What is particularly advantageous is that by identifying patterns, a prediction can be made about the expected duration and degree of the disruption. Data weighted according to the patterns described in this way can then be managed in a database, for example online managed, are and can be used for data evaluation and associated functionality, for example an alert that a functionality is restricted.
Landscapes
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Biophysics (AREA)
- General Health & Medical Sciences (AREA)
- Veterinary Medicine (AREA)
- Public Health (AREA)
- Animal Behavior & Ethology (AREA)
- Surgery (AREA)
- Molecular Biology (AREA)
- Medical Informatics (AREA)
- Heart & Thoracic Surgery (AREA)
- Pathology (AREA)
- Biomedical Technology (AREA)
- Artificial Intelligence (AREA)
- Evolutionary Computation (AREA)
- Signal Processing (AREA)
- Psychiatry (AREA)
- Physiology (AREA)
- Mathematical Physics (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Fuzzy Systems (AREA)
- Cardiology (AREA)
- Measuring Magnetic Variables (AREA)
Abstract
Description
Claims
Applications Claiming Priority (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| DE102022209444.1A DE102022209444A1 (de) | 2022-09-09 | 2022-09-09 | Verfahren zum Ermitteln eines Magnetokardiogrammsignals eines Lebewesens |
| PCT/EP2023/072852 WO2024052092A1 (de) | 2022-09-09 | 2023-08-18 | Verfahren zum ermitteln eines magnetokardiogrammsignals eines lebewesens |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| EP4583783A1 true EP4583783A1 (de) | 2025-07-16 |
Family
ID=87845614
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| EP23761465.6A Pending EP4583783A1 (de) | 2022-09-09 | 2023-08-18 | Verfahren zum ermitteln eines magnetokardiogrammsignals eines lebewesens |
Country Status (4)
| Country | Link |
|---|---|
| EP (1) | EP4583783A1 (de) |
| CN (1) | CN119855549A (de) |
| DE (1) | DE102022209444A1 (de) |
| WO (1) | WO2024052092A1 (de) |
Family Cites Families (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| GB201211704D0 (en) * | 2012-07-02 | 2012-08-15 | Univ Leeds | Magnetometer for medical use |
| JP2016217930A (ja) * | 2015-05-22 | 2016-12-22 | セイコーエプソン株式会社 | 磁気計測システム |
| CN106343999B (zh) * | 2016-10-10 | 2019-04-19 | 中国科学院上海微系统与信息技术研究所 | 心磁图仪、基于其的补偿优化方法、系统及服务器 |
| US20190298202A1 (en) * | 2018-03-28 | 2019-10-03 | Asahi Kasei Microdevices Corporation | Magnetocardiographic measurement apparatus, calibration method, and recording medium having recorded thereon calibration program |
| DE102018214617A1 (de) | 2018-08-29 | 2020-03-05 | Robert Bosch Gmbh | Sensoreinrichtung |
| DE102018220234A1 (de) | 2018-11-26 | 2020-05-28 | Robert Bosch Gmbh | Verfahren und Sensorvorrichtung zur Magnetfeldmessung |
-
2022
- 2022-09-09 DE DE102022209444.1A patent/DE102022209444A1/de active Pending
-
2023
- 2023-08-18 WO PCT/EP2023/072852 patent/WO2024052092A1/de not_active Ceased
- 2023-08-18 CN CN202380064476.9A patent/CN119855549A/zh active Pending
- 2023-08-18 EP EP23761465.6A patent/EP4583783A1/de active Pending
Non-Patent Citations (1)
| Title |
|---|
| C B AHN ET AL: "Automatic artifact component removal using a neural network in MCG signal.", NEUROLOGY & CLINICAL NEUROPHYSIOLOGY, vol. 2004, 30 November 2004 (2004-11-30), pages 101 - 1, XP093357299, ISSN: 1538-4098, Retrieved from the Internet <URL:https://web.archive.org/web/20061121160051/http://www.neurojournal.com/article/view/340/292> * |
Also Published As
| Publication number | Publication date |
|---|---|
| WO2024052092A1 (de) | 2024-03-14 |
| CN119855549A (zh) | 2025-04-18 |
| DE102022209444A1 (de) | 2024-03-14 |
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