WO2003084605A1 - Method and device for the prevention of epileptic attacks - Google Patents

Method and device for the prevention of epileptic attacks

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Publication number
WO2003084605A1
WO2003084605A1 PCT/EP2003/003543 EP0303543W WO03084605A1 WO 2003084605 A1 WO2003084605 A1 WO 2003084605A1 EP 0303543 W EP0303543 W EP 0303543W WO 03084605 A1 WO03084605 A1 WO 03084605A1
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WO
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Patent type
Prior art keywords
seizure
transmitter
amp
epileptic
method
Prior art date
Application number
PCT/EP2003/003543
Other languages
German (de)
French (fr)
Inventor
Oliver Holzner
Original Assignee
Oliver Holzner
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    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61NELECTROTHERAPY; MAGNETOTHERAPY; RADIATION THERAPY; ULTRASOUND THERAPY
    • A61N1/00Electrotherapy; Circuits therefor
    • A61N1/18Applying electric currents by contact electrodes
    • A61N1/32Applying electric currents by contact electrodes alternating or intermittent currents
    • A61N1/36Applying electric currents by contact electrodes alternating or intermittent currents for stimulation
    • A61N1/36014External stimulators, e.g. with patch electrodes
    • A61N1/36025External stimulators, e.g. with patch electrodes for treating a mental or cerebral condition
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/04Detecting, measuring or recording bioelectric signals of the body or parts thereof
    • A61B5/04012Analysis of electro-cardiograms, electro-encephalograms, electro-myograms
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/04Detecting, measuring or recording bioelectric signals of the body or parts thereof
    • A61B5/0476Electroencephalography
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/16Devices for psychotechnics; Testing reaction times ; Devices for evaluating the psychological state
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/40Detecting, measuring or recording for evaluating the nervous system
    • A61B5/4076Diagnosing or monitoring particular conditions of the nervous system
    • A61B5/4094Diagnosing or monitoring seizure diseases, e.g. epilepsy
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61MDEVICES FOR INTRODUCING MEDIA INTO, OR ONTO, THE BODY; DEVICES FOR TRANSDUCING BODY MEDIA OR FOR TAKING MEDIA FROM THE BODY; DEVICES FOR PRODUCING OR ENDING SLEEP OR STUPOR
    • A61M21/00Other devices or methods to cause a change in the state of consciousness; Devices for producing or ending sleep by mechanical, optical, or acoustical means, e.g. for hypnosis
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61NELECTROTHERAPY; MAGNETOTHERAPY; RADIATION THERAPY; ULTRASOUND THERAPY
    • A61N2/00Magnetotherapy
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/04Detecting, measuring or recording bioelectric signals of the body or parts thereof
    • A61B5/04005Detecting magnetic fields produced by bio-electric currents
    • A61B5/04008Detecting magnetic fields produced by bio-electric currents specially adapted for magneto-encephalographic signals
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61MDEVICES FOR INTRODUCING MEDIA INTO, OR ONTO, THE BODY; DEVICES FOR TRANSDUCING BODY MEDIA OR FOR TAKING MEDIA FROM THE BODY; DEVICES FOR PRODUCING OR ENDING SLEEP OR STUPOR
    • A61M21/00Other devices or methods to cause a change in the state of consciousness; Devices for producing or ending sleep by mechanical, optical, or acoustical means, e.g. for hypnosis
    • A61M2021/0005Other devices or methods to cause a change in the state of consciousness; Devices for producing or ending sleep by mechanical, optical, or acoustical means, e.g. for hypnosis by the use of a particular sense, or stimulus
    • A61M2021/0055Other devices or methods to cause a change in the state of consciousness; Devices for producing or ending sleep by mechanical, optical, or acoustical means, e.g. for hypnosis by the use of a particular sense, or stimulus with electric or electro-magnetic fields
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61MDEVICES FOR INTRODUCING MEDIA INTO, OR ONTO, THE BODY; DEVICES FOR TRANSDUCING BODY MEDIA OR FOR TAKING MEDIA FROM THE BODY; DEVICES FOR PRODUCING OR ENDING SLEEP OR STUPOR
    • A61M2230/00Measuring parameters of the user
    • A61M2230/08Other bio-electrical signals
    • A61M2230/10Electroencephalographic signals
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61NELECTROTHERAPY; MAGNETOTHERAPY; RADIATION THERAPY; ULTRASOUND THERAPY
    • A61N1/00Electrotherapy; Circuits therefor
    • A61N1/02Details
    • A61N1/04Electrodes
    • A61N1/0404Electrodes for external use
    • A61N1/0472Structure-related aspects
    • A61N1/0476Array electrodes (including any electrode arrangement with more than one electrode for at least one of the polarities)

Abstract

The invention relates to a method and a device for the automatic non-invasive controlled or regulated electromagnetic prevention of epileptic attacks in vivo, based on attack models. The method firstly comprises, in addition to continuous extracranial measurement of electromagnetic fields ( in particular those connected with brain activity), the continuous calculation of early warning indicators from the measured data and secondly, in the case of critical indicator values, in addition to the continuous calculation of attack-preventing interventions based on an attack model, the continuous application of said interventions by means of extra-cranial generation of suitable magnetic fields.

Description

METHOD AND DEVICE FOR PREVENTION epileptic seizures

The invention relates to a method and apparatus for automatic non-invasive, controlled or regulated electromagnetic prevention of epileptic seizures in vivo.

The relevant technologies include the following approaches:

1 Significant research efforts are on the neurophysiological genesis of epileptic seizures, and there to the level of cell preparations fo- kussiert [8], [9].

2 early warning methods based extracranial EEG data have been described in principle, for example, [1], [21].

3 Diagnostic using TMS (transcranial magnetic stimulation) has been described in principle, also coupled with EEG, for example, [2]

4 The use of TMS for intervention in epilepsy consists of the discovery of an epileptic focus on the basis of medical experience of the used doctor imaging procedures, or testing, and subsequent attempts to elicit with one or two coil systems epileptic seizures (for example, [5], [6 ], [10]).

5 seizure models, gung processes describe the conditions and characteristics of collective exciter exist as examples of recent physical theories, such as Synergetics (overview see [7]).

WO 98/18394 describes a method by which a magnetic stimulation to egg nem subjects is performed at the same time whose brain activity using EEG is measured. This known method is used for diagnosis.

From WO 01/21067 a method for early detecting an impending epileptic seizure shows. With this method, an impending epileptic seizure is to be predicted hours or days. In this method, the brain activity of a patient at different points before, during and measured after epileptic seizures. For these patients are determined using various nonlinear processes sensor pairs that can predict very well under an existing seizures from training phase to attack. Periodically signal pairs are adapted, including more attacks are necessary. The training and adaptation contained in this procedure prevent complete prevention, because the data must be updated with new attacks again and again.

The object of the present invention is to provide a method and an apparatus for prevention of epileptic seizures.

The object is achieved by a method having the features of claim 1 and by an apparatus having the features of claim 8. Advantageous embodiments of the invention are given in the respective subclaims.

The use of a seizure model provides a reliable prevention of epileptic seizures. The invention is based on the recognition that leading to epileptic seizures operations under specification of appropriate control parameters be quantified with these models so that a reliable prevention pre- is possible.

The invention is illustrated by way of example with reference to the drawings. In the drawings: Figure 1 is a transmitter in a sectional view, Figure 2 shows the transmitter of Figure 1 in a view from below, Figure 3 is a planar projection of openings for sensors and transmitters accordingly their arrangement to a helmet...

Fig. 4 a helmet and a carrier axis, together with a chin rest,

Fig. 5 shows a further planar projection of openings for sensors and transmitters in accordance with their arrangement to a helmet, and Fig. 6 shows an example of a time series of values ​​of an EEG sensor, Fig. 7 shows a detail from the time series in Figure 6 in a Phasenraumdarstel - tion, and Figure 8 shows a typical curve of the SNR (signal-to-Noise-ratio)..

device

The inventive device on the input side comprises a measuring system with apparatus for the electromagnetic measurement data acquisition, preprocessing, and - weitergäbe, for example, in an advantageous embodiment comprising an EEG cap with their sensors, connections to the amplifier, amplifier, connections to the A D converter, A / D converter, connections to the computer unit, electricity suppliers for the equipment, along with links.

The device on the output side comprises a control system with apparatus for extrakra--colonial generating magnetic fields, "Transmitter" called, and a device for implementation of the outgoing from the computer unit the digital control and regulation requirements into transmitter signals, for example, in an advantageous embodiment comprises current conducting coils, electricity providers , compounds D / AUmsetzer, besides compounds.

Furthermore, the device between the input and output side comprises a computer unit (PC or workstation) with software for implementing the method explained in greater detail below. Suitable sensors are EEG or MEG sensors. The MEG sensors are for example of a SQUID sensor element with a suitable evaluation device for Detektie- a magnetic field and cooling means ren formed. The EEG sensors include, for example, two electrodes for measuring an electrical potential difference.

A sensor may comprise an electric and / or magnetic shielding against its environment to the extent characterized its function is not inhibited (thus, for example, no shield in the direction of the cranium of the patient, but certainly a shield in the direction of the other transmitters and / or sensors and / or connecting cable).

The head-proximal portion of the input side may have a plurality of sensors that are distributed throughout the brain close to the head surface, said plurality of sensors is referred to as a sensor grid.

The sensor grid has a fixing device for fixing the same with respect to the cranium of the patient on, so that the sensors assume in repeated insertion and removal of the sensor grid their respective relative position again, for example by fitting the sensor grid in a helmet, the inside of the Kranialform of the particular patient replicates. The fixing can also be video-supported, which detects the position of the head of the patient in the room, and the sensors respect to the head over several cameras and real-time 3D data is converted.

An advantageous embodiment of the input side of which comprises partially ambulatory shape in which the measurement data extraction takes place via a portable sensor grid, which is connected to a backpack or as part of clothing by the patient-worn devices for Messdatenvorverarbeitung, and wherein the data transfer to the computer unit advantageously wirelessly he follows.

A transmitter 5 comprises a current-carrying coil 6 with para-, dia- or ferromag- netischem core 7, as shown in Figure 1 in sectional view, wherein the directions of the arrows symbolize the directions of current flow. The transmitter 5 has substantially a cylindrical shape, wherein the lateral surface and an end face forming the back of the cylinder are dressed with a shield. 8 On the free side of the shield of the transmitter coil 6 and the core 7 are directly adjacent, and with this side of the transmitter 5 is aligned in operation at the cranium for delivering exogenous magnetic fields. At the back of the transmitter 5, a retaining member 9 is arranged, with which the transmitter 5 is fixed in a home.

The extracranial transmitter 5 can be protected against deformation, beispielswei- se by pouring the current-carrying parts in suitable resin, or embedding of current-carrying parts in stable insulating material.

The transmitter 5 may be provided with a cooling device.

In a further embodiment intrakra- NiAl implanted electrodes are used as sensors and / or transmitters, EEG measurements can be performed on both, as well as streams can be directed into the brain. These electrode-carrying lines and / or their interfaces to the computer unit and / or more lines and / or further measuring instruments and / or the associated computer unit and / or the utility of electrodes and / or computer unit is also implanted, whereby an outpatient operation is permitted.

An advantageous embodiment of the head-proximal portions of the actuation system includes a plurality of Transmittem which are intra- and extracranial or distributed, This arrangement of Transmittem is referred to as a transmitter grating.

An advantageous embodiment of an extracranial transmitter grating includes fixing thereof relative to the cranium of the respective user, so that the transmitter assume their respective relative position again with repeated insertion and removal of the transmitter grating, for example by fitting the transmitter grating in a helmet, the inside of the Kranialform of the respective user replicates. Another advantageous embodiment of the transmitter grid includes implanted electrodes.

An advantageous embodiment of the head nearby parts of extracranial measuring and positioning system comprises a on its inner side the Kranialform of the respective user simulating helmet 10 with 12 through a support axis 11 extending connecting cables and a chin rest sensor and transmitter grating inside the helmet are such fixed that overlap both grating - ie to a sufficient number of transmitters are located in the vicinity of each sensor and vice versa. A planar projection of the superposition of the transmitter with the sensor grid is shown in FIG 3 (here shown are for transmitter 5 as four corner openings 13 for sensors as circles and openings 14). In the described embodiment, the user sits on a chair with neck support below the helmet 10th

In an alternative embodiment, the sensor grid is intracranial, and the helmet includes the extracranial transmitter grating.

In an alternative embodiment, the transmitter grating is intracranial, and the helmet includes the extracranial sensor grid.

In an alternative embodiment both sensor, transmitter and grids are intracranial.

In an advantageous embodiment, the sensor density or Sensorkonfigu- can adjust ration of extracranial sensor grid. In a further advantageous embodiment, this change happens automatically, controlled or regulated via the intermediate unit.

In an advantageous embodiment, the transmitter density and Transmit terkonfiguration an extracranial transmitter grid can be set and / or change the inclination angle of each transmitter to the cranium of the patient. A planar projection of a mechanical holder of this embodiment is shown in FIG 5. In this case, openings 13 for sensors as circles and openings 14 for transmitters are illustrated in shape. Here, it is possible to anchor the transmitter 5 into the openings 14 of the holder, and / or tilt transmitter 5 relative to the holder. Among other things, all conventional coil configurations can be represented with their location, orientation, and field direction in this embodiment.

In an advantageous embodiment of the device with conventional protection against power failures and / or voltage fluctuations is provided.

In an advantageous embodiment be executed in the computer unit in real time and auto- matically: i) Continuous calculation of Anfallsfrühwamindikators from the input data, ii) In the case of threshold crossing by the indicator calculation of an intervention instruction for seizure prevention, as well as performing the intervention using the generated by transmitter magnetic fields, iii) Upon return of the indicator into the normal range and / or exceeding a time limit shutdown of the intervention, iv) Conventional algorithms for eliminating artifacts caused by artificially induced magnetic fields (see for example [2]), as well as (for other artifact removal, for example by muscle twitching) ,

In an advantageous embodiment run over i-iv addition, continuous addition to the computer unit in real time and automatically approximately optimization algorithms for density and positioning of sensors and Transmittem.

procedure:

1. The data acquisition via EEG, and measurement data Messdatenvorverarbeitung tenweitergabe in digital form, together with the possible artifact removing carried out continuously by conventional methods. The measurement data are automatically processed according to the used empirically validated early warning indicator to a value of this early warning indicator. 2. When the response of the early warning indicator, the calculation of a compatible with the used seizure model automatic intervention instruction for seizure prevention, as well as their current conversion via magnetic field generating (B-field generation) by using the transmitter is carried out. The specifics of the magnetic field generation (for example, location, strength, direction, frequency, pattern, and / or others) resulting from the intervention instructions. The B-field changes cause intracranial induced voltages. The digital control of the magnetic field generation is done with conventional methods. Current health recommendations for extracranial generated electromagnetic radiation are known whose compliance is automated.

3. Return of the early warning indicator to its normal range and / or exceeding a time limit for intervention to shut down the intervention takes place.

An early warning indicator is calculated from the electromagnetic brain activity data size, which significantly changes before an epileptic seizure. For the present invention early warning indicators are preferred whose change is at least a few minutes before the attack.

A suitable Frühwamindikator is the correlation of Ahnlichkeitsindices a predefined proportion of sensors, at decreasing Ahnlichkeitsindices. The similarity index (engl .: Similarity index) "is made [1] and a large number of previous publications, for example [21] are known. The early warning time is indicated mean here at 325 seconds.

In another advantageous embodiment of the method of Frühwamindikator is the mutual information of Ahnlichkeitsindices a predefined proportion of sensors, at decreasing Ahnlichkeitsindices. "Mutual Information" known "riabler divided by the product of their individual probabilities joint probability of occurrence of two Zufallsva-" as a binary logarithm of.

In another advantageous embodiment of the method Frühwamindikator is the mutual information of Ahnlichkeitsindices a predefined proportion of sensors, at decreasing Ahnlichkeitsindices, associated with activation of indicators (such as for waking up characteristic changes in body temperature, muscle movements, characteristic EEG pattern, and / or others). This provides the possibility of false alarms by simultaneous for many sensors changes Wachheitszu- article of the patient is minimized, depending on the additional indicator additional requirements arise on the device (for example, current EMG measurement).

These examples given above for the calculation of early warning indicators do not require training phases that include epileptic seizures. The calculation of the warning indicators is carried out by means of a phase-space representation of the normal state of the relevant patient.

The early warning indicators above are robust to noise and artifacts. For other non-robust early warning indicators filtering and artifact removal procedures must be switched between.

An example of phases space embedding given in Figures 6 to 7, wherein Figure 6 shows an 8 seconds comprehensive EEG time series of a single channel at a sampling rate of 128 points per second (x-axis time, y-axis voltage between electrode and reference electrode in arbitrary units), Figure 7 comprising a beginning with measuring point 128 32 measuring points section from the time series (of Figure 6 in phase space representation x axis measurement value at the time t, the y-axis measured value at time t-20). The method of embedding in a phase space is described for example in [13] in detail. Here, it is assumed that the one-dimensional signal (as in Figure 6) projecting a HOE herdimensionalen signal which is to be restored. This higher-dimensional signal is represented two-dimensionally in FIG. 7

As a preferred embodiment of an early warning before an epileptic seizure, a detection module can specify with

1) means to calculate the similarity of the current series of measurements representing for each measuring channel with the normal measurements. The elevation of the normal condition of each individual patient takes place before the egg tual use of the detection module.

2) means for outputting a local warning signal for each channel: if the above genante similarity falls below a threshold value. \

3) means for discharging a global warning signal if a timely manner a plurality of measuring channels lead to local warning signals.

To make the intervention reliable, fit models are used. As seizure models eg following models can be used. Oscillator seizure model, chaos seizure model, Synergetikanfallsmodell, stochastic oscillator seizure model, stochastic chaos seizure model, stochastic Synergetikanfallsmodell

This seizure models describe the calculated from electromagnetic activity of neurons and / or populations of neurons that are relevant to an epileptic seizure parameters. These parameters are for example the chaoticity means of an EEG electrode and its reference electrode measured potential difference time series, expressed by the maximum Lyapunov exponents [12]. Typical further parameters are critical deceleration critical fluctuations, similar to a normal state in the (meta) phase space, etc. These characteristics are expressed by concrete numerical parameters. Thus, the chaoticity may alternatively be represented by embedding dimension [13], correlation dimension, Kullback-Leibler entropy, etc., for example. In place by the Lyapunov exponent.

An oscillator seizure model is based on [3]. Here, the neuron populations described are so-called neural limit-cycle oscillators, ie, that they can oscillate or parameter-dependent rest. The interaction of neural oscillators with each other will be described with an interaction equation. The seizure generation requires this interaction. The attack prevention is based on isolation of the neural oscillators.

"Neural oscillator" is used synonymously to "limit-cycle oscillation". Of this special case, the phase oscillators (for example, see [22]) to distinguish in which decouple amplitude and phase, and only the phase of an oscillator is considered. In the phase space, the limit cycle represents as can also enter any closed curve the phase of oscillator is a circular path. A corresponding seizure model is based on clusters of 1- over other clusters increased occurrence. This special case and related interventional procedures (re setting plus entrainment, s., For example [22]) result in the case of general Limit Cycle Oscillators are not successful, with not even a hard reset with high amplitude that is often repeated (already problematic leads to seizure prevention health limits) - under the rTMS. General interventions for Limit Cycle Oscillators, however, work for phase oscillators.

A suitable interaction for the oscillator seizure model is the specific weak coupling between the neural oscillators. Seizures are associated with increasing the number of oscillating neural oscillators along with increased mutual information between oscillation frequencies of these weakly coupled neural oscillators. A neural oscillator is an isolated neuronal ensemble that is capable of oscillating rendem and nichtoszillierendem behavior. The dynamics of each neural oscillator under interaction with other neural oscillators by

Z - = (z, -) + £ Σ "= Λ * Z; ε" l

given. Here, for each i between 1 and n Zj neural oscillator gj is given by the well-known from [3] Wilson-Cowan equations for the i-th neural oscillator hy is the strength of the connection of Zj by Zj. The coupling strength Epsilon obtained empirically from 0.04 to 0.08. If one coupling strength and connection strengths compared to the time scale of a seizure takes as slowly varying arrival, remains next global possible interference by strong externally generated supplementary terme, g- with possible transfer of an oscillation in Nichtoszillation primarily an intervention by using the function ,. It is known from the theory of neural oscillators that they interact only in the case of oscillations, and only at commensurate oscillation frequencies.

An advantageous embodiment of a compatible with the "seizure model with specific weak coupling between neural oscillators" instruction to preventive on epileptic seizures is:

To afflict first adjacent and, secondly before the intervention with the same and / or commensurate frequencies oscillating neural oscillators incommensurable frequencies which are included in their original frequencies or to nearby incommensurable frequencies (for example, adjacent oscillators have the frequencies 3 Hertz and 15 Hertz , thus forcing the second oscillator to the frequency of 5 Hertz Another example:. both have the frequency 8 hertz, hence a force thereof to 7. Hertz). The vibrations are forced at high amplitude magnetic fields by means of these frequencies. Since oscillating on the same and / or commensurate frequencies neural oscillators and adjacent to the possible existence of physiological compound point, by the forced Incommensurability, ie change of gj, possible, and certainly constructive interaction between the respective zι interrupted minimizes the mutual information , thus preventing the seizure generation. The procedural renskomplexität allows for continuous real-time calculation of all required sizes.

Whether the incommensurable-making neighboring oscillators succeed, however, depends on their diversity and minimality their mutual coupling. In extreme cases, neighboring, nearly identical, strongly coupled oscillators can not force to various incommensurable frequencies in the area of ​​influence of a transmitter through this. but here it is sufficient to move groups of oscillators in the sphere of influence of different transmitters on incommensurable frequencies to prevent the attack. This also has the prevention of the development of one-clusters within the control of multiple transmitters and to prevent the emergence of "traveling waves" result.

A further advantageous embodiment of a compliant with the "seizure model with specific weak coupling between the neural oscillators" statement for the prevention of epileptic seizures is One active in step 1, firstly the neural oscillators to chaotic behavior [14] on (for example, by time-delayed feedback with systematic error ), and known then stabilizes in step 2, depending on the sphere of influence of the respective transmitter, the neural oscillators on the first orbit with incommensurate frequencies which achieve this, by conventional methods. as shown in [4], has step 2 of this procedure as already in cell preparations However, sufficiently proven for inhibiting seizure propagation. the algorithm used therein ( "OGY method") is due to its arrival f f or computer speed and memory capacity for the real time in vivo case unsuitable.

In the stochastic oscillator seizure model specific parameters are compared to the aforementioned seizure model as a random variable assumed. The proposed method can also be applied (eg [15]).

In the chaos-seizure model it is assumed that normal brain activity, as it is captured from each sensor having a minimum of chaoticity. The attacks are accompanied by a simultaneous decrease for all sensors of this chaoticity. Seizure prevention via maintain a certain degree of chaos ([4] and [16]).

In the stochastic chaos seizure model dimensional effects complement the low-dimensional deterministic variation of the electromagnetic quantities. The attack-prevention strategies match those of the chaos seizure model.

In the Synergetikanfallsmodell is assumed that brain activity can be described by a small number of degrees of freedom, so-called ordering parameter, [17]. It is circular causality: the order parameter caused and determined by the cooperation of neurons at the same time but the order parameter determine the macroscopic system behavior. An epileptic seizure corresponds to a phase transition. This goes hand in hand with critical slowing down and critical fluctuations. Seizure prevention via prevention of the phase transition (for example, by control of bifurcation according to [18]). In the stochastic Synergetikanfallsmodell stochastic forces are introduced into the dell Synergetikmo- in phenomenological way with the so-called Lange vin approach. For seizure prevention, there is in addition to the above method, the possibility of stochastic resonance [20], and its opposite, noise Drowning: It is known that, for example, depending on a noise amplitude (for example, for Gaussian white noise) in systems with stochastic component signals generated ( "Coherence Resonance"), or the signal-to-Noise ratio (SNR) reinforced ( "stochastic Resonance") or attenuated be (the latter will be referred to as "Noise Drowning" here). The typical course of SNR is shown in Figure 8. (x-axis noise amplitude y axis SNR).

an intervention instruction is calculated on the basis of these models describing the magnetic field to be generated. This description is made for example by location, strength, direction, frequency, pattern, and / or other parameters of the magnetic field (B-field). With this magnetic field, the electromagnetic activity of neurons and / or neuronal populations can be suitably changed, and thus prevents an imminent epileptic seizure.

The use of one or more seizure models provides a reliable comparison hindrance epileptic seizures. The invention is based on the recognition that leading to epileptic seizures operations under specification of appropriate control parameters be quantified with these models, so that a reliable prevention is possible.

The preferred embodiment of the invention comprises an intervention module which is useful in a variety of models, to prevent the attack, for example, the transmitters are at high transmitter density classified in three classes, class 1 for Chaotisieren, class 2 for incommensurate stabilizing, - class 3 for Noise-Drowning, of such that in every neighborhood of each transmitter of a class can be found transmitters of other classes. Among other things, 1 chaos-seizure models are satisfied class by class 2 oscillator seizure models, by class 3 models with stochastic components. The satisfaction synergistic models automatically obtained here by canceling the master mode (by frequency shifts) while encryption prevent the ascent of slave mode to master mode (by noise Drowning). The satisfaction of phase oscillator models of seizures also automatically arises because one cluster states are prevented (incommensurability prevented phases se-locking, noise Drowning prevent higher modes). The satisfaction of chaos seizure models also results automatically for Class 1 and Class 3 (see Rau = high dimensional chaos).

In the above described method can either during or immediately after an intervention measured brain activity are, whereby a closed loop is obtained, since from the measured brain activity in turn the Frühwamindikator and, if necessary, a further intervention instruction is calculated.

An advantageous embodiment of the back driving the intervention is a running simultaneous retraction of all the magnetic fields generated.

An advantageous embodiment of the back driving of intervention is the sliding thinning of the magnetic fields generating transmitter (thinning as spatially uniform distributed retraction and / or switching off a percentage of all the transmitters).

An advantageous embodiment of the Back driving the intervention is the spatially localized retraction and / or switching off of multiple transmitters at a gradual expansion of the region, in the retracted and / or is switched off.

It is not necessary to operate the interventions with usual TMS high fields of 1-2 Tesla per coil. "Running" is a "continuous" or defined as "at appropriate intervals". The monitoring of compliance with electromagnetic exposure limits is done continuously and automatically. The use of the invention is not aimed at a cure epilepsy from, but also allows for the use of permanent seizure freedom without medical personnel or the use of drugs are necessary. This does not only minimize disease consequences and treatment side effects, but also a significant reduction in running costs. Furthermore, an outpatient use of the invention are possible, which in addition to a further cost reduction freedom of movement patients improved substantially.

With the method described above epileptic seizures can be prevented. In addition, can be achieved with a similar but broader, proactive method instead of reactive prevention of epileptic seizures based on models of seizures other behavioral objectives, preferably in healthy individuals on the basis of corresponding behavioral models and general brain activity models. The general procedure involves the determination of the interactive Nichtobser- vablen the models used for that person, on and unknown to the models based the calculation of an a priori intervention order, as well as the selective implementation of the statement while preventing undesirable propagation effects. The aim of this modification is to stabilize at the request of a per- son whose behavior reliably or modify and / or stabilize this change. This method can be performed with a device of the above-described similar apparatus.

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Claims

claims
1. A method for non-invasive control type electromagnetic prevention of epileptic seizures in vivo comprising the steps of:
- automatic extrakraniales electromagnetic measuring brain activity,
- automatically calculating an early warning indicator for epileptic seizures, - automatically calculating an intervention instruction for seizure prevention in response of the early warning indicator based on a fit model and measured brain activity, and
- automatic reacting the intervention instruction via controlled or regulated extracranial magnetic field generation.
2. The method of claim 1, characterized in that comparable as seizure model of the relevant electromagnetic activities of neurons and / or neuronal populations for epileptic seizures parameters applies.
3. The method according to claim 2, characterized in that a fit model selected from the group oscillator seizure model, a stochastic oscillator seizure model, Chaos-seizure model, a stochastic chaos seizure model, Synergetikanfallsmodell stochastic Synergetikanfallsmodell is used.
4. The method according to any one of claims 1 to 3, characterized in that the measurement of brain activity, and calculating the early warning indicator is ongoing.
5. The method according to any one of claims 1 to 4, characterized in that an intervention instruction is implemented by extracranial generating magnetic fields.
6. The method according to any one of claims 1 to 5, characterized in that either during or after intervention, the brain activity is measured immediately.
7. The method according to any one of claims 1 to 6, characterized by controlled or controlled automatic shutdown of intervention upon return of the early warning indicator in its normal range and / or exceeds a time limit.
8. An apparatus for automatic non-invasive control type electromagnetic prevention of epileptic seizures in vivo, in particular for performing a method according to any one of claims 1 to 7, comprising: - a measuring device with at least one sensor for measuring electromagnetic brain activity,
- means for determining an early warning indicator for the early detection of epileptic seizures,
- means for calculating an intervention instruction reference to an attack model and measured brain activity, and
- means for converting the Inten / entionsanweisung with at least one transmitter for generating a magnetic field.
, Device according to claim 8, characterized in that the measuring device comprises a plurality of extracranial sensors forming a sensor grid.
10. The device according to claim 8 or 9, characterized in that the sensors are arranged in an EEG cap.
11. Device according to one of claims 8 to 10, characterized in that the means for converting the intervention command comprises a plurality of transmitters, the transmitters form a lattice.
12. Device according to one of claims 8 to 11, characterized in that a computer unit is provided in which a software module for implementing the method according to any one of claims 1 to 7 is stored.
13. The device according to one of claims 8 to 12, characterized in that an electric and / or magnetic shield is provided for each sensor and each transmitter.
14. Device according to one of claims 8 to 13, characterized in that a fixing of the measuring device is provided with respect to the cranium of the patient so that the sensors take their turn respective relative position with repeated insertion and removal of the sensor grid again.
15. The device according to one of claims 8 to 14, characterized in that the measuring device is designed mechanically decoupled from the rest of the device, so the measuring device can be carried by a patient.
16. Device according to one of claims 8 to 15. characterized in that a fixing means for the means for converting the intervention instruction is provided with respect to the patient's cranium.
17. Device 8 to 16, characterized in that the sensors and transmitters on an inner side simulating the Kranialform of the particular patient helmet are arranged according to one of the claims.
18. Device according to one of claims 9 and 11 to 17, characterized in that the transmitter grating and the sensor grid are interlaced such that each transmitter sensors and each sensor transmitters are adjacent.
19. Device according to one of claims 11 to 18, characterized in that are provided in the transmitter grating mounts for receiving additional transmitter so that the transmitter density of a transmitter grating is changed locally and / or so that the inclination angle of individual transmitters to the cranium of the patient can be changed.
PCT/EP2003/003543 2002-04-05 2003-04-04 Method and device for the prevention of epileptic attacks WO2003084605A1 (en)

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