WO2022200610A1 - Methode et dispositif de detection d'une activite electrique cardiaque representative - Google Patents
Methode et dispositif de detection d'une activite electrique cardiaque representative Download PDFInfo
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Classifications
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- A61B5/00—Measuring for diagnostic purposes; Identification of persons
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- A61B5/316—Modalities, i.e. specific diagnostic methods
- A61B5/318—Heart-related electrical modalities, e.g. electrocardiography [ECG]
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Definitions
- the field of the invention relates to methods and devices for generating an electrophysiological parameter linked to an individual's cardiac activity. More particularly, the field of the invention relates to the methods implemented by means of surface electrodes recording signals used to detect a representative cardiac electrical activity.
- QRS duration ventricular depolarization time
- This measurement is a very good indicator to detect certain singular activities of the heart, but this measurement alone is only an overview of certain cardiac characteristics. It is for example possible, for a patient suffering from a given pathology, that the measurement of the duration of the QRS can be representative of an electrophysiological singularity. However, this measurement may prove to be insufficient to characterize certain electrophysiological activities of an individual, in particular an electrophysiological activity that can be used or corroborated with other variables to anticipate a cardiac risk.
- the invention therefore aims to propose a method for measuring the cardiac activity of a patient which overcomes the aforementioned drawbacks.
- the invention relates to a method for generating an electrophysiological parameter which comprises: selecting a subset of electrophysiological descriptors from a set of predefined electrophysiological descriptors according to an input parameter defining a measurement context, each electrophysiological descriptor of the subset being associated with at least one channel, with a type of signal, with a signal marker and with a statistical mode of calculation;
- each electrophysiological descriptor being calculated from the statistical modality which is applied to the signal marker of the signal acquired according to the type of signal on a selected pathway associated with said electrophysiological descriptor;
- An advantage of the invention is to propose a method taking into account a set of different electrophysiological descriptors to characterize cardiac activity.
- the possibility of selecting the measurement context by taking descriptors that relate to areas on the patient's body, types of signals analyzed, signal markers and different statistical modalities makes it possible to make a composite measurement of the patient's cardiac activity .
- the fact of composing the score following the crossing of a threshold for a plurality of descriptors with different modalities makes it possible to effectively detect cardiac activities which may be characteristic.
- this method makes it possible to form a corpus of electrophysiological variables making it possible to characterize a singular activity of the cardiac activity of an individual.
- patients of a reference group we mean a group of people selected from a class of individuals.
- the class of individuals is selected from one or more criteria.
- the criteria are selected from:
- the morphology of the persons considered For example, for a patient suffering from a cardiac pathology, it is possible that the measured indicator (for example the duration of the QRS) is normal, whereas it is considered as a characteristic measurement of this pathology.
- the other descriptors used can alert us to the presence of a characteristic cardiac activity . There is therefore a much better efficiency in the detection of said characteristic activity, compared to the known methods.
- At least one descriptor of the subset being associated with a statistical modality different from that of a second descriptor of the subset and a signal marker different from that of the second descriptor.
- This arrangement makes it possible to obtain a subset that includes several descriptors carrying different physiological information from each other.
- the different steps of the method of the invention can be implemented by means of calculations such as computers. These can be those of an electronic board of dedicated equipment or those of a computer or a remote data server.
- the comparison step is performed by comparing the value of the set of descriptors with the threshold value defined by a statistical distribution of said descriptors of the set of healthy patients of dimension equal to the number of descriptors of the sub - together.
- the comparison step is performed by comparing the value of each electrophysiological descriptor with at least one threshold value specific to said electrophysiological descriptor, said at least one threshold value being defined by a statistical distribution of said descriptor of a set healthy patients; and the step of calculating the score defining the electrophysiological parameter is performed by incrementing said score each time an electrophysiological descriptor crosses the at least one threshold value specific to it.
- This characteristic makes it possible to define the calculation of the score by comparing the values with a control population. The calculated score is therefore representative of the patient's cardiac activity.
- the at least one pathway comes from a predefined zone of the patient's body from among a set of predefined zones. This arrangement makes it possible to take into account the location of the measurements on the patient's body, the zones being predefined.
- the subset comprises at least one second geographical descriptor which is associated with several lanes and several geographical groups, each geographical group being formed by a central lane and the at least four lanes close to the central lane, the value of the electrophysiological descriptor being determined:
- This provision makes it possible to have a second type of descriptor which takes into account geographical groups.
- the addition of this other type of descriptors makes it possible to take into account the concentration of singular measured values and enriches the subset of selected descriptors.
- the input parameter defining the measurement context defines a subset of descriptors characteristic of a given cardiac pathology. This characteristic makes it possible to adapt the subset of descriptors to a cardiac pathology that one wishes to analyze.
- the input parameter defining the measurement context defines a subset of descriptors characteristic of a patient profile comprising at least one age and/or one gender/sex. Taking these characteristics into account makes it possible to increase the precision of the generated electrophysiological parameter.
- each first electrophysiological descriptor of the subset is associated with at least one channel of a predefined zone of the patient's body from among a set of predefined zones and in that for each electrophysiological descriptor, the predefined zone on the patient's body is chosen from:
- the plurality of electrodes comprises at least fifteen electrodes, preferably twenty-five. This arrangement makes it possible to obtain a mesh of measurement electrodes that is sufficiently fine to obtain the electrophysiological parameter.
- the type of signal analyzed is chosen from:
- This arrangement makes it possible to take into account several types of signals and therefore to have descriptors which take into account several types of signal measurement. Thus, the descriptors take into account several types of information and report more faithfully on the state of said patient.
- at least one reference electrode arranged on a lower limb or an upper limb of the patient. This arrangement allows the measurement of a reference potential.
- a plurality of reference electrodes is arranged on the surface of the lower or upper limb(s) of the patient. This arrangement makes it possible to obtain a reference potential with great precision.
- the signal marker is the measurement of the voltage of an averaged signal.
- the averaging of the signal makes it possible to obtain a stable measurement of said voltage.
- the signal marker is the measurement, on the signal averaged and filtered between 40 and 250 Hertz, of the duration of depolarization of the ventricles or of the fragmentation of the signal during the depolarization of the ventricles .
- Ventricle depolarization time is a very representative measure of cardiac activity.
- the signal marker is the measurement on the discrete wavelet decomposition of the signal:
- This arrangement allows the taking into account of different types of signals all carrying different information enriching the selected subset.
- the signal marker is the measurement on the decomposition into continuous wavelets of the signal of the number of chains of local maxima. This measurement is a measurement that makes it possible to account for a singular cardiac activity.
- the signal marker is the measurement on a roundel taken between 256 and 512 hertz of the signal:
- the signal marker is the measurement on a roundel taken between 128 and 256 hertz of the signal:
- the signal marker is the measurement on a roundel taken between 64 and 128 hertz of the RMS (Root Mean Square). This measurement makes it possible to report the cardiac activity of the patient.
- the statistical modality is chosen from:
- the estimation of the electrophysiological descriptors is carried out during a low breathing phase of the patient. This arrangement makes it possible to perform the measurement when during a breathing phase which does not disturb the measurement.
- a plethysmography belt is placed on the patient to estimate the breathing phases of the latter.
- the method of the invention may comprise a preliminary step aimed at selecting a subset of electrophysiological descriptors characteristic of cardiac electrical activity.
- this preliminary step can be carried out by a method of selecting a subset of first electrophysiological descriptors characteristic of a characteristic cardiac electrical activity from among a set of predefined first descriptors.
- Each first electrophysiological descriptor is associated with at least one channel, a signal type, a signal marker and a statistical calculation modality.
- the method includes recording a plurality of electrical activities defining said pathways and includes:
- Second quantification o of a second proximity factor between the values of the components of each descriptor not selected during the first selection step and the values of the components of the descriptor vector(s) selected during the first selection step; and o a third proximity factor between the component values of each descriptor not selected during the first selection step and the component values of the characteristic vector;
- the invention relates to a device or a system comprising means for implementing the method of the invention.
- the means may include computers, memories, electronic cards, electrodes and electrode supports.
- the device or system of the invention may include computers or servers when computing resources are required. The invention is described below in such a way that the features described may relate to the method of the invention or to the device or system of the invention.
- the invention also relates to a device for generating an electrophysiological parameter which comprises:
- a plurality of surface electrodes configured to be deposited on the body of a patient and to measure an electric potential of the surface of the body of the patient, each surface electrode defining a path;
- a means of calculation configured for: ⁇ select a subset of descriptors from a set of predefined descriptors according to an input parameter defining a measurement context, each electrophysiological descriptor of the subset being associated with at least one pathway, a type of signal, a marker of signal and to a statistical mode of calculation; at least one descriptor of the subset being associated with a statistical modality different from that of a second descriptor of the subset and a signal marker different from that of the second descriptor;
- ⁇ recording a plurality of cardiac electrical activities defining said pathways, each pathway being obtained by the recordings of at least two electrodes;
- each electrophysiological descriptor being calculated from the statistical modality which is applied to the signal marker of the signal acquired according to the type of signal on a selected channel associated with said electrophysiological descriptor; ⁇ comparing the value of the set of electrophysiological descriptors with at least one threshold value specific to the set of electrophysiological descriptors, said at least one threshold value being defined by a statistical distribution of said descriptors of a set of patients; ⁇ calculating a score defining an electrophysiological parameter as a function of exceeding the at least one threshold value defined by the statistical distribution.
- the electrodes are arranged on the patient's surface using adhesive strips. This arrangement allows a convenient and quick arrangement of the adhesive strips on the patient.
- the device comprises a device for detecting the breathing phases of a patient, preferably a plethysmography belt. This arrangement makes it possible to perform the measurement when during a breathing phase which does not disturb the measurement. According to one embodiment, the device is able to implement the method according to the invention.
- Fig. 1 a schematic flowchart of the process according to the invention
- Fig. 2 a flowchart presenting the selection of a descriptor
- Fig. 3 a front view of a patient's torso on which a plurality of measurement electrodes are placed to implement the method according to the invention
- Fig. 4 a view of a plurality of measurement electrodes in a predefined area of the patient's body
- Fig. 5 two curves illustrating the method for calculating an asymmetry index
- Fig. 6 a graph illustrating the method for calculating a Kurtosis index
- Fig. 7 a view of a curve illustrating the method for calculating the number of zones of reduced amplitude. Description of the invention
- the invention relates to a method for generating an electrophysiological parameter.
- electrophysiological parameter is meant a datum resulting from an electrical measurement which is characteristic of a physiological activity of a patient.
- the invention also relates to a device for generating an electrophysiological parameter.
- the device according to the invention is capable of implementing the method mentioned above. Subsequently, the elements described in this description will be applicable both to the method according to the invention and to the device according to the invention. The method according to the invention will be described with the support of Figure 1, which is a schematic flowchart of the method according to the invention.
- the invention relates to a method for generating an electrophysiological parameter.
- a first step of this method is a step of selecting a subset of first descriptors ⁇ Dk ⁇ from a set of predefined descriptors ⁇ DN ⁇ .
- electrophysiological descriptor Di means a measurement context of an electrical datum associated with an activity detected at the surface of a patient.
- Each first electrophysiological descriptor Di is associated with the recording of at least one pathway Vi.
- the recording of a Vi channel corresponds to the recording of the electrical activity picked up by at least one EL electrode placed on the surface of a patient's body.
- Each first descriptor Di is associated with at least one channel V, on a predefined zone Zi on the patient's body.
- predefined zone Zi is meant the zone of the patient's body on which the measuring electrode(s) EL are deposited, the electrical activities of which are recorded to obtain the channel(s) Vi.
- the surface of a patient's body can be segmented into different functional and/or geometric and/or physiological zones. These zones can therefore correspond to geographical zones on the patient's body, to functional zones with respect to the cardiac activity of the patient, or else to zones corresponding to the physiology and/or the physiology of the latter.
- Each first descriptor D i is associated with a type of measured signal Ti on the selected channels V.
- type of signal Ti is meant, for example, the measurement of a voltage between two electrodes. The different types of Ti signals that can be selected will be described later.
- Each first descriptor Di is associated with a signal marker
- signal marker Mi is meant the characteristic of the type of signal Ti which will be measured.
- a set of signal markers Mi used in the context of the invention comprises the measurement of frequency and energy characteristics of the signal. The various selectable Mi signal markers are described below.
- Each first descriptor Di is associated with a statistical modality MSi.
- Statistical modality MSi means a statistical measurement modality applied to the measurements performed on the signals.
- a statistical modality MSi can for example be the calculation of the mean of the signal marker Mi measured on several electrodes. The different MSi statistical modalities that can be selected will be described later.
- Each first electrophysiological descriptor Di is therefore defined both by a selection of the predefined zone Z, of the patient's body, of the type of signal Ti, of the signal marker Mi and of the statistical modality MSi.
- an input parameter Inp is acquired.
- the Inp input parameter defines a measurement context.
- measurement context we mean the number of descriptors Di that will be selected as well as, for each descriptor Di, the combination of the predefined zone Zi, the type of signal Ti, the signal marker Mi and the statistical modality MSi that are selected.
- the input parameter is generated from a patient profile, for example defined by his age, gender, history, and possibly other parameters.
- the input parameter is generated from a selection of a predefined pathology.
- the pathology can be associated in a database or a memory with a set of descriptors. This case can be interesting to associate the electrical activity measured with said selected pathology.
- the input parameter is defined by a selection of a set of descriptors. This selection can be made by an operator from a user interface.
- the input parameter is defined by a selection of a set of electrodes. This selection can be made by an operator from a user interface.
- the input parameter is defined by an instruction emitted by a device or a process implemented by computer.
- the setpoint may correspond to a set of descriptors selected according to an algorithm configured according to various parameters.
- Such an algorithm is, for example, described in the application FR2103047 filed on March 25, 2021, the title of which is “PROCESS FOR THE SELECTION OF ELECTROPHYSIOLOGICAL DESCRIPTORS”.
- the input parameter is defined by a combination of these different variants.
- At least two first descriptors Di, Dj of the subset ⁇ Dk ⁇ are associated with a different statistical modality MSi.
- two of the first descriptors Di, Dj are not associated with the same statistical modality MSi.
- At least two first descriptors Di, Dj of the subset ⁇ Dk ⁇ are associated with a different signal marker Mi.
- two of the first descriptors Di, Dj are not associated with the same signal marker Mi.
- a plurality of EL surface electrodes are arranged on the patient's body. Thus, at least two electrodes are placed on the patient's skin. These EL electrodes are configured to collect an electrical potential at the surface of the patient's skin.
- An ENR recording of a plurality of cardiac electrical activities defining said V pathways is made. During this step, the recording of all the available channels is preferably carried out. In other words, the electrical activity of each electrode of the plurality of electrodes arranged on the patient's body is recorded.
- the invention can be implemented in particular by means of a memory allowing the recording of data acquired and/or data processed by one of the steps of the method of the invention.
- An EST estimate of the set of electrophysiological descriptors D, of the subset of descriptors ⁇ Dk ⁇ is performed. In this step of the method, each value of each descriptor D, of the subset ⁇ Dk ⁇ is calculated. The calculation is performed for each descriptor Di in the predefined zone Zi, with the type of signal Ti, on the signal marker Mi, and according to the statistical modality MSi associated with it.
- each descriptor D is then compared with a threshold value Vseuii.
- Each threshold value Vseuii is characteristic of the electrophysiological descriptor Di in question. Thus, there is a threshold value Vseuii specific to each descriptor Di.
- a score is then calculated from the number of descriptors Di whose value has exceeded the threshold value Vseuii which is specific to it. Exceeding the threshold value Vseuii is understood to mean an overshoot by a higher value or by a lower value. The direction in which the threshold is exceeded is specific to each descriptor Di. Each time the threshold value Vseuii is exceeded by a descriptor Di, the score is incremented.
- the method according to the invention therefore makes it possible to obtain an electrophysiological parameter which takes into account the calculation of the value of several descriptors Di which have measurement and calculation methods which are very different.
- the electrophysiological parameter does not take into account only one parameter to calculate the score defining the electrophysiological parameter.
- the method according to the invention makes it possible to generate the electrophysiological parameter most representative of the cardiac activity of the patient.
- the comparison step can be performed by taking into account the statistical distribution of the set of descriptors in a space having a dimension equal to the number of descriptors D, of the subset ⁇ Dk ⁇ .
- the set of descriptors is compared to a threshold value resulting from the distribution with several dimensions.
- each electrophysiological descriptor Di is associated with at least one pathway V, of a predefined area Zi of the patient's body, with a type of signal Ti, with a signal marker Mi, and with a statistical calculation modality MSi .
- figure 2 is a flowchart showing the selection process of a descriptor Di.
- a selection is made of a predefined zone Zik among a set of predefined zones Zi.
- a selection is made of a Tik signal type from a set of Ti signal types.
- a selection is made of a signal marker Mik from a set of signal markers Mi.
- a selection is made of a statistical modality MSik from a set of statistical modalities MSi.
- a plurality of EL electrodes are deposited on the surface of the patient's torso.
- the number of electrodes in the example represented can vary, one can for example have a number of electrodes much lower than that represented, or much higher.
- the plurality of EL electrodes covers a large portion of the patient's torso. As can be seen, this plurality of electrodes is separated into four distinct zones on the latter. A first part of the EL electrodes is located on an area upper right Zi of the patient's torso. A second part of the EL electrodes is located on an upper left zone Z2 of the patient's torso. A third part of the EL electrodes is located on a lower right zone Z3 of the patient's torso. A part of the EL electrodes is located on a lower left zone Z4 of the patient's torso. Finally, the plurality of electrodes EL is included in a zone comprising the entire Z5 of the patient's torso.
- the demarcation between the zones located on the left of the torso and those located on the right of the torso is a vertical line passing through the center of the torso, or substantially through the center of the torso.
- the demarcation between the areas located at the bottom of the torso and those located at the top of the torso is a horizontal line passing through the center of the torso.
- Each zone has a predefined number of EL electrodes.
- the number of electrodes arranged per zone may be around thirty. It is for example possible to have thirty EL electrodes per zone.
- each zone comprises the same number of EL electrodes.
- the zone comprising the entire torso Z5 comprises a different number of electrodes than the others, because this zone Z5 comprises the union of the electrodes of all the other zones Z-i, Z2, Z3 and Z4.
- a lower number of EL electrodes can be provided, for example nine EL electrodes per zone Z-i, Z2, Z3, and Z4.
- the zone Z5 comprising the entire torso of the patient comprises thirty-six electrodes EL.
- Each Vi channel is obtained by recording the electrical activity of at least two EL electrodes.
- These at least two electrodes can be two electrodes of one or more areas of the patient's torso.
- These at least two electrodes can also be an electrode of a region of the patient's torso and a reference electrode.
- the subset ⁇ Dk ⁇ comprises at least one second geographical electrophysiological descriptor Di.
- the at least one geographical descriptor Di is associated with at least one route Vi and with several geographical groups.
- a geographical group is formed by an EL electrode and the four EL electrodes which are located directly near it.
- a geographical group is represented in FIG. 3. This geographical group comprises a central electrode ELi, as well as the electrode located directly above the latter. It also comprises the electrode located directly below the central electrode ELi, the electrode located directly to the left of the central electrode ELi and the electrode located directly to the left of the central electrode ELi. These four electrodes are shown hatched in FIG. 3.
- the measurement of the value according to the type of signal and the signal marker is carried out on all the available geographical groupings of the plurality of electrodes arranged on the body. of the patient.
- Other arrangements of the electrodes can be envisaged. It is possible in particular to select the central electrode and the four electrodes situated at the top left, at the top right, at the bottom left and at the bottom right of the central electrode ELi. These are the electrodes appearing without a pattern in FIG. 3. It is also possible to provide more electrodes, for example nine electrodes in the geographical group. These are the nine electrodes EL of FIG. 3 for example.
- the value obtained for each electrode EL of said grouping is compared with at least one geographical threshold value.
- the at least one geographic threshold value is obtained from a statistical distribution of the value of the considered EL electrode of a set of healthy patients.
- the geographical group is considered significant.
- the value of the descriptor is the number of significant geographical groups counted.
- the statistical modality is not taken into account, the value of the descriptor being the number of geographical groupings detected.
- the subset ⁇ Dk ⁇ of descriptors comprises at least one first descriptor Di and at least one second geographic descriptor. Additionally, the subset ⁇ Dk ⁇ comprises several first descriptors Di. According to this variant, the subset ⁇ Dk ⁇ comprises a second geographic descriptor per signal marker used in the first descriptors Di of the subset ⁇ Dk ⁇ .
- Each electrophysiological descriptor Di is associated with a type of signal Ti.
- Figure 4 is a schematic representation of nine contiguous EL electrodes on the patient's body.
- each circle represents an EL electrode.
- the dotted areas represent the different EL electrodes selected in the different signal types.
- the type of signal Ti can be chosen preferably between four different types of signals.
- a first type of signal T is a unipolar signal.
- a unipolar signal is a signal taken between an electrode EL of the predefined zone Zi and a reference electrode.
- the type of unipolar signal is the voltage measured between the electrode of the predefined zone and the reference electrode.
- Reference electrode means an electrode which is not located in one of the areas of the patient's torso defined above.
- a reference electrode can be an electrode placed on a patient's lower limb or upper limb.
- a second type of signal Ti is a vertical bipolar signal.
- a vertical bipolar signal is a signal taken between an electrode in the predefined zone and the electrode directly below it on the patient's torso. In other words, the type of signal acquired is the voltage between the two EL electrodes.
- a vertical bipolar signal is taken between two electrodes of the predefined zone Zi. These two electrodes form a vertical bipole B.
- a third type of signal Ti is a horizontal bipolar signal.
- a horizontal bipolar signal is a signal taken between an electrode of the zone preset and an electrode located directly next to it in a horizontal line on the patient's torso.
- the type of signal acquired is the voltage between the two EL electrodes.
- the horizontal bipolar signal is taken between two electrodes of the predefined zone Zi. These two electrodes form a horizontal bipole Bh.
- a vertical axis we mean an axis defined by a line parallel to the axis of the body taken in its largest dimension.
- a horizontal axis means an axis defined in a plane perpendicular to the vertical axis and tangent to the surface of the human body.
- a frame of reference linked to the human body can be defined so as to define the vertical and horizontal axes in particular with respect to the morphology of the human body or other reference axes.
- the invention can be defined with respect to reference axes other than the vertical axis and the horizontal axis insofar as the positions of the electrodes can be defined in the reference frame linked to the human body.
- a fourth type of signal Ti is a Laplacian signal.
- a Laplacian signal is estimated by subtracting from the potential of a central electrode ELi the average of the potentials of the eight electrodes which are directly close to said central electrode.
- the Laplacian signal is a compound voltage between the central electrode ELi and a set of EL electrodes peripheral to the central electrode ELi. These nine electrodes form an ELiap Laplacian electrode.
- Each electrophysiological descriptor is associated with a signal marker Mi.
- a signal marker Mi is a mode of measurement of a physical quantity associated with the types of signals measured by the EL electrodes.
- the signal marker Mi associated with a descriptor Di is preferably chosen from among fourteen signal markers Mi. These signal markers Mi are described below.
- a first signal marker Mi corresponds to the measurement of an averaged electrical signal.
- averaged electrical signal we mean the calculation, performed on the measured voltage, of the average between the maximum peak and the peak QRS minimum. This measurement of QRS duration is generally fairly representative of cardiac activity.
- the band pass filter is a bidirectional Butterworth filter.
- a bidirectional Butterworth filter has the advantage of limiting oscillations due to filtering, which makes the calculation of values for certain Mi signal markers more precise.
- a signal marker Mi on the filtered signal is the duration of the QRS on the filtered signal.
- a mark is placed on the beginning of the QRS and a second mark is placed at the end of the QRS. The time between the two markers is measured.
- This operation can be performed automatically using an algorithm for detecting the beginning and end of QRS.
- this duration can be measured manually by an operator on an interface. It is also possible to provide an automatic measurement of the duration of the QRS and a manual control of said measurement by the operator on the interface.
- the duration of the QRS is detected by moving a sliding window measuring the energy of the filtered signal.
- a marker is placed that marks the start of the window.
- the end mark of QRS is placed in the same way.
- Another signal marker Mi is the fragmentation measurement of the filtered averaged signal between 40 hertz and 250 hertz.
- the number of QRS peaks on the filtered signal is measured.
- peak is meant a local maximum of the curve of the filtered signal.
- the number of peaks is measured on the section of the curve corresponding to the QRS.
- the QRS start and end markers are set in the same way as for the previous Mi marker, which as a reminder is the QRS duration marker on the filtered signal.
- the following Mi markers are calculated on the wavelet decomposition of the signal.
- these markers Mi it is possible to use the decomposition into continuous wavelets or the decomposition into discrete wavelets.
- a first marker Mi is the calculation of the energy on the discrete wavelet decomposition of the signal. Specifically, the energy is calculated on the sum of the coefficients on several levels. Typically, the sum of the coefficients is carried out between 64 hertz and 1024 hertz, ie over the four levels of this frequency band. According to one embodiment, the measured energy is normalized with respect to the duration of the QRS. Alternatively or additionally, the energy is normalized with respect to the maximum amplitude of the signal.
- a second marker Mi calculated on the discrete wavelet transform is the measure of the index called Kurtosis Sku.
- Kurtosis is meant an index making it possible to estimate the spread of a given curve.
- Figure 6 illustrates several measurements of curve spread on three example curves.
- P the Kurtosis index
- E the index is positive.
- N the Kurtosis of a curve representing a normal distribution N is equal to zero.
- the Kurtosis Sku is calculated on the sum of the coefficients on several levels of the discrete wavelet decomposition. Typically, the sum of the coefficients is carried out between 64 hertz and 1024 hertz, ie over the four levels of this frequency band.
- a third marker Mi calculated on the discrete wavelet transform is the measurement of the Fischer asymmetry coefficient.
- This coefficient can also be called “skewness”. This coefficient makes it possible to estimate the asymmetry of a given curve.
- Figure 5 illustrates two measurements of the asymmetry on two curves given as examples. Curve 1 is a left-tending curve and curve 2 is a right-tending curve. Fischer's asymmetry coefficient has a positive value when the curve tends to the left. This is the case of curve 1. Fischer's asymmetry coefficient has a negative value when the curve tends to the right. This is the case of Figure 2. Concretely, the Fischer asymmetry coefficient is calculated on the sum of the coefficients on several levels of the discrete wavelet decomposition. Typically, the sum of the coefficients is carried out between 64 hertz and 1024 hertz, ie over the four levels of this frequency band.
- a fourth marker Mi calculated on the discrete wavelet transform is the measurement of the number of chains of local minima of said decomposition.
- a chain of local minima is the presence on several levels of decomposition into discrete wavelets of the same minimum.
- the measurement is made between 64 hertz and 1024 hertz, i.e. on the four levels of this frequency band.
- the measurement of the number of chains of local minima can be performed on the continuous wavelet decomposition.
- Another signal marker Mi that can be chosen is the measurement on the continuous wavelet decomposition of the number of chains of local maxima.
- a chain of local maxima is the presence on several levels of discrete wavelet decomposition of the same maximum. By measuring the number of maxima found in each level of decomposition, we measure the number of chains of local maxima. Typically, the measurement is made between 64 hertz and 1024 hertz, i.e. on the four levels of this frequency band.
- the maxima repeating themselves in the bands from 64 hertz to 128 hertz, then from 128 hertz to 256 hertz, then from 256 hertz to 512 hertz and finally 512 hertz to 1024 hertz.
- the measurement of the number of chains of local maxima can be performed on the discrete wavelet decomposition.
- the two following Mi signal markers are measured on the wavelet of the signal included in the frequency band going from 256 hertz to 512 hertz of the signal.
- the first concerns the measurement of the Kurtosis Sku index on this wavelet.
- Kurtosis Sku is meant the same indicator as described previously in the application.
- the second signal marker Mi measured on this wavelet is the measurement of the number of areas of reduced amplitudes RED of Rondelle. To calculate the number of areas of reduced amplitudes, the upper and lower envelopes of the signal are created. Thus, the number of reduced amplitude zones is calculated on the signal envelopes. This is illustrated by Figure 7 which shows a signal and the areas of reduced RED amplitudes detected.
- the following three signal markers Mi are measured on the wavelet of the signal comprised in the frequency band ranging from 128 hertz to 256 hertz of the signal.
- the first concerns the measurement of the Kurtosis index Sku on this wavelet.
- Kurtosis Sku is meant the same indicator as previously described in the application.
- the second signal marker Mi measured on this wavelet is the measurement of the number of zones of reduced amplitudes of the wavelet. The number of zones of reduced amplitude is calculated in the same way as for the marker relating to roundness of the signal comprised in the frequency band going from 256 hertz to 512 hertz of the signal.
- the third signal marker concerns the measurement of the RMS of rondeau in the frequency band 128 Hertz to 256 Hertz.
- RMS Room Mean Square
- a signal marker Mi which can be selected is measured on a roundel of the signal comprised in the frequency band going from 64 to 128 hertz. This signal marker Mi relates to the measurement of the effective amplitude RMS (“Root Mean Square”) of the signal.
- Mi signal markers may be used beyond the fourteen Mi signal markers described. It is for example possible to use signal markers Mi which are combinations of signal markers Mi already described.
- Each first electrophysiological descriptor Di is associated with a statistical modality MSi.
- statistical modality MSi is meant a modality for processing the various quantities measured in order to calculate a value for each descriptor Di.
- a statistical modality MSi For each descriptor Di, it is possible to select a statistical modality MSi from among a set of statistical modality MSi available.
- a first statistical modality is the minimum at the fifth percentile of the measured values. It is recalled that the set of values measured on each electrode of the predefined zone of the patient's body Zi is taken as the values. For this statistical modality, we take, on all the measured values, we remove the five percent of the lowest values and we select the minimum value on the remaining values. This statistical modality has the advantage, by removing the five percent of the lowest values, of removing aberrant values which could distort the representativeness of the measurement.
- a second statistical modality that can be selected is the maximum at the 95th percentile . For this statistical modality, the five percent highest values are taken from all the values selected. The highest value of the remaining values is then selected. This statistical modality makes it possible not to take into account, for a measurement of a maximum value, the aberrant values which could appear in the highest measured values. In this way, an
- a third statistical modality MSi is the average of the measured values.
- the mean is a classic indicator and representative of a distribution.
- a fourth statistical modality MSi is the standard deviation calculated on the set of measured values.
- the standard deviation is a representative value of the dispersion of values.
- the dispersion can be a significant value, a large variance in the measurements carried out being able to be the sign of a disorder in the cardiac activity of the patient.
- a fifth MSi statistical modality that can be selected is the median.
- the median value of a set of values is the value that separates the set of values into two sets of the same size. This value gives information that can vary from that given by the average value, because the median makes it possible not to give too much importance to aberrant values close to the maximum and the minimum of the measured values.
- a sixth statistical modality MSi is the value of the interquartile. To calculate this value, we calculate the value of the 25th percentile and has value of the 75th percentile .
- the interquartile value represents the difference between the 75th percentile value and the 25th percentile value.
- the interquartile is an interesting statistical value to look at to characterize the distribution of the measured values.
- each descriptor of the ⁇ Dk ⁇ subset is selected.
- a threshold value Vseuii is available for each of them.
- Each threshold value Vseuii for each descriptor Di of the subset ⁇ Dk ⁇ can advantageously be defined by the input parameter Inp.
- each value of each descriptor D, of the subset ⁇ Dk ⁇ is compared with the threshold value Vseuii of said descriptor Di.
- threshold value Vseuii is meant a lower threshold value or an upper threshold value.
- the threshold can be exceeded either if the value of the descriptor is lower than the threshold value, or if the value of the descriptor is higher than the threshold value Vseuii.
- a descriptor Di comprises several different threshold values Vseuii.
- a descriptor Di can comprise an upper threshold value Vseuii and a lower threshold value Vseuii.
- the threshold is exceeded if the value of the descriptor is between the lower threshold value Vseuii and the upper threshold value Vseuii.
- the threshold overflow can take place when the value of said descriptor is lower than the lower threshold value Vseuii or when the value is higher than the upper threshold value Vseuii.
- a descriptor Di can comprise three or more threshold values Vseuii which define value ranges corresponding to the overrun for the value of the descriptor Di.
- the value of the threshold value Vseuii is defined by the scientific literature relating to representative cardiac data.
- the threshold value can be defined at 120 milliseconds .
- the threshold value of the descriptor is exceeded for a duration greater than 120 milliseconds.
- the score retained is 0 if the value is less than 120 ms and the score is 2 if the value is greater than 120 ms.
- different thresholds can be defined for a descriptor Di associated with the marker and with the statistical modality. These different thresholds make it possible to assign different scores, for example an intermediate threshold of 80ms makes it possible to define a first score of 0 if the value is less than 80ms, a score of 1 if the value is between 80 ms and 120 ms and a score of 2 if the value is greater than 120 ms.
- the threshold value can be defined at 20 microvolts.
- the threshold value of the descriptor is exceeded for a measured voltage value which is less than 20 microvolts.
- a score of 0 can be assigned on the value is greater than 20 microvolts and a score of 1 can be assigned on the value is less than 20 microvolts.
- threshold values are described in the publication entitled “Characterization and detection of abnormal micro potentials associated with lethal ventricular arrhythmias, by analysis of high-resolution electrocardiographic signals recorded on the surface of the torso” (Nolwenn TAN et Al. ).
- the thresholds can correspond to physiological signs characterizing an electrical activity, a physical effort or a history.
- the threshold values can be chosen so as to identify an index of the presence of a given cardiac condition or of a singular cardiac electrical activity.
- the comparison between the value of each descriptor Di of the subset ⁇ Dk ⁇ and the respective threshold value Vseuii of each descriptor Di is performed.
- the result of these comparisons is used to establish a score.
- the established score defines an electrophysiological parameter. More precisely, the score takes into account the number of times that the value of one of the descriptors Di of the subset ⁇ Dk ⁇ exceeds the threshold value Vseuii. The number of overruns of threshold values Vseuii makes it possible to establish the score.
- the score calculated according to the invention has the advantage of taking into account the value of a set of different physiological data, which makes it very representative with respect to conventional measurements taking into account only a limited number of parameters.
- the score is equal to the number of descriptor values D, exceeding the threshold value Vseuii associated with said descriptor Di.
- a score established in this way is very representative of cardiac activity. If the ⁇ Dk ⁇ subset is well chosen, the score is very representative of the patient's cardiac activity.
- the score is compared to a score threshold value.
- Said score threshold value is specific to the predefined state ET-i.
- the invention also relates to a device for generating the electrophysiological parameter.
- the characteristics described above concerning the method according to the invention also apply to the device according to the invention.
- the characteristics described below for the device also apply to the method according to the invention.
- the device for generating an electrophysiological parameter comprises a plurality of electrodes which are arranged on the surface of the patient's body. Each surface electrode defines a channel Vi.
- the device comprises adhesive strips comprising the surface electrodes.
- the adhesive strips are intended to be stuck to the surface of the patient's body.
- each adhesive strip comprises several surface electrodes. This arrangement facilitates the installation of the electrodes on the patient, the installation of a strip comprising several electrodes being simpler than that of the electrodes one by one.
- the device comprises a vest or a jacket comprising the plurality of EL measurement electrodes. The vest is intended to be put on by the patient. This arrangement allows rapid installation of the device on the patient.
- the device comprises at least 14 electrodes.
- the device comprises means for measuring the signal of each channel Vi. More specifically, the measuring means is configured to measure one the electric potential of each of the channels V.
- the measuring means can for example be an acquisition card.
- the acquisition card may include an input to collect an electrical signal, and an analog-digital converter to digitize the acquired signal.
- the digitized signal is then transmitted to a computer.
- the digitized signal can for example be transmitted to a computer which performs the processing steps on the signal.
- the device comprises a calculation means.
- the calculating means records the measurements of the channels Vi provided by the measuring means.
- the computer then processes this data.
- the computer selects a subset ⁇ Dk ⁇ of descriptors Di from the set ⁇ DN ⁇ of descriptors Di. This selection is made according to the Inp input parameter.
- the computer then calculates the value of each descriptor D, of the subset ⁇ Dk ⁇ . This calculation is made from the measurements of the channels Vi. The calculation is carried out in accordance with the predefined zone Zi, the type of signal Ti, the signal marker MSi and the statistical modality STi selected for the descriptor Di in question.
- the computer compares the value of the descriptors D, selected with the threshold value Vseuii relating to each descriptor Di.
- the device comprises a device for detecting the patient's breathing phases. Such a device detects when the patient is in the exhalation phase or “flat” breathing phase. It also detects when the patient is in the inspiration phase. Breathing tends to interfere with measurements made at the EL electrodes. This is particularly the case during the inspiration phases during which heartbeats and their measurement may be affected. Preferably, the measurement of the potential of each pathway V i is carried out during the expiration phase. This arrangement makes it possible to avoid the disturbances generated by a measurement during the inspiration phases.
- the breathing phase detection device can be connected to the computer. Alternatively, it is connected to the signal measurement means of each channel Vi.
- the breathing phase detection device is a plethysmography belt.
- the plethysmography belt is a convenient way to perform this type of detection.
- An object of the invention is also a method for generating an electrophysiological parameter which comprises:
- each electrophysiological descriptor of the subset being associated with at least one channel, with a type of signal , a signal marker and a statistical calculation modality; arrangement of a plurality of surface electrodes on a patient's body;
- each pathway being obtained by the recordings of at least two electrodes; estimation of the set of electrophysiological descriptors of the subset, each electrophysiological descriptor being calculated from the statistical modality which is applied to the signal marker of the signal acquired according to the type of signal on a selected channel associated with said electrophysiological descriptor;
- the sorting key takes into account an ascending or descending order of incremental values. Alternatively or additionally, the sorting key takes into account the value of the discrepancies noted between the value of each descriptor and the at least one threshold value relating to said descriptor. Alternatively or additionally, the sorting key takes into account the descriptors, i.e. it classifies the descriptors and their value according to a predefined order. Alternatively or additionally, the sorting key takes into account the area on the patient's torso considered in the choice of descriptors. Alternatively or additionally the sorting key takes into account the descriptors.
- the step of displaying comprises a step of displaying a calculated score defining an electrophysiological parameter as a function of the exceeding of the at least one threshold value defined by the statistical distribution.
- Electrophysiological descriptor ⁇ Dk ⁇ Subset of electrophysiological descriptors ⁇ DN ⁇ : Set of electrophysiological descriptors Inp: Input parameter Vi: Path
- DISPO arrangement of a plurality of electrodes
- ENR Recording of a plurality of electrical activities
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EP22718873.7A EP4312770A1 (fr) | 2021-03-25 | 2022-03-25 | Methode et dispositif de detection d'une activite electrique cardiaque representative |
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Citations (6)
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FR2103047A7 (fr) | 1971-07-09 | 1972-04-07 | Bergeret Jean Pierre | |
US20110201951A1 (en) * | 2010-02-12 | 2011-08-18 | Siemens Medical Solutions Usa, Inc. | System for cardiac arrhythmia detection and characterization |
US20150032016A1 (en) * | 2013-07-23 | 2015-01-29 | Medtronic, Inc. | Identification of healthy versus unhealthy substrate for pacing from a multipolar lead |
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US20160270682A1 (en) * | 2013-11-08 | 2016-09-22 | Spangler Scientific Llc | Non-invasive prediction of risk for sudden cardiac death |
US20180249965A1 (en) * | 2015-09-18 | 2018-09-06 | Spangler Scientific Llc | Non?invasive prediction of risk for sudden cardiac death |
-
2021
- 2021-03-25 FR FR2103044A patent/FR3121027A1/fr active Pending
-
2022
- 2022-03-25 WO PCT/EP2022/058005 patent/WO2022200610A1/fr active Application Filing
- 2022-03-25 EP EP22718873.7A patent/EP4312770A1/fr active Pending
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FR2103047A7 (fr) | 1971-07-09 | 1972-04-07 | Bergeret Jean Pierre | |
US20110201951A1 (en) * | 2010-02-12 | 2011-08-18 | Siemens Medical Solutions Usa, Inc. | System for cardiac arrhythmia detection and characterization |
US20150032016A1 (en) * | 2013-07-23 | 2015-01-29 | Medtronic, Inc. | Identification of healthy versus unhealthy substrate for pacing from a multipolar lead |
US20160270682A1 (en) * | 2013-11-08 | 2016-09-22 | Spangler Scientific Llc | Non-invasive prediction of risk for sudden cardiac death |
US20150272464A1 (en) * | 2014-03-27 | 2015-10-01 | The General Hospital Corporation | System and Method For Determining Dynamic Elecardiographic Ischemic Changes |
US20180249965A1 (en) * | 2015-09-18 | 2018-09-06 | Spangler Scientific Llc | Non?invasive prediction of risk for sudden cardiac death |
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TAN NOLWENN ET AL: "New Insights Into Non-Invasive His Bundle Potential Detection on High Resolution Body Surface Recordings", 13 September 2020 (2020-09-13), pages 1 - 4, XP055857933, Retrieved from the Internet <URL:https://ieeexplore.ieee.org/ielx7/9344050/9344051/09344317.pdf?tp=&arnumber=9344317&isnumber=9344051&ref=aHR0cHM6Ly9pZWVleHBsb3JlLmllZWUub3JnL2Fic3RyYWN0L2RvY3VtZW50LzkzNDQzMTc=> [retrieved on 20211105], DOI: 10.22489/CinC.2020.244 * |
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