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WO2018202273A1 - Procédé de détermination de la performance cérébrale d'un sujet - Google Patents

Procédé de détermination de la performance cérébrale d'un sujet Download PDF

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Publication number
WO2018202273A1
WO2018202273A1 PCT/EP2017/060318 EP2017060318W WO2018202273A1 WO 2018202273 A1 WO2018202273 A1 WO 2018202273A1 EP 2017060318 W EP2017060318 W EP 2017060318W WO 2018202273 A1 WO2018202273 A1 WO 2018202273A1
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Prior art keywords
module
instant
strength
eeg
total
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PCT/EP2017/060318
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English (en)
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Anastasios SMEROS
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    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7235—Details of waveform analysis
    • A61B5/7264—Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
    • A61B5/316—Modalities, i.e. specific diagnostic methods
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
    • A61B5/316—Modalities, i.e. specific diagnostic methods
    • A61B5/369—Electroencephalography [EEG]
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
    • A61B5/316—Modalities, i.e. specific diagnostic methods
    • A61B5/369—Electroencephalography [EEG]
    • A61B5/372—Analysis of electroencephalograms
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7235—Details of waveform analysis
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/20—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems

Definitions

  • the present invention generally relates to the determination of brain performance of a subject.
  • US 2010/324440 A1 discloses an approach for applying a real time stimulus triggered by a certain brain state. It includes receiving data that indicates onset of an instance of the brain state, whereupon a stimulus is initiated before the instance ends.
  • the approach is intended to enhance performance, enhance learning or enhance the probing of impact of that state on perception, action or cognition.
  • WO 2006/073915 A2 describes a biological interface system comprising a sensor having a plurality of electrodes for detecting multicellular signals emanating from one or more living cells of a patient and a processing unit configured to receive the multicellular signals from the sensor to produce a processed signal.
  • the system is configured to perform an integrated patient training routine to generate one or more system configuration parameters that are used by the processing unit to produce the processed signal.
  • Horstmann et al. (“State dependent properties of epileptic brain networks: comparative graph-theoretical analyses of simultaneously recorded EEG and MEG", Clinical Neurophysiology 121 (2010) 172-183) discloses a device for determining a brain performance status of an epilepsy patient.
  • transmission means for transmitting each one of said digitized EEG signals S j (t) to one of said input ports associated with one of said EEG electrodes;
  • each system state (k ⁇ ) at a given time is uniquely defined by the following properties:
  • steps B and C in any order: increase link strength between every pair of modules (i,j) and self-link strength of every module (i) to obtain updated values L(i,j)(k) according to:
  • A' Increase total sublink strength, starting from the last available value L l s ⁇ (k - 1), to obtain an updated total sublink strength L l s ⁇ (k for each module i according to:
  • a modular device for carrying out the method of the invention comprising a digital processing unit formed of at least four mutually interconnected brain core modules ( j), each module further comprising an input port (/;) for receiving a digitized EEG signal Sj(t) obtained from said subject, the processing unit further comprising:
  • each total sublink strength is a positive real number
  • an acquisition system for carrying out the method of the invention comprising:
  • transmission means for transmitting each one of said digitized EEG signals S j (t) to one of said input ports (/j) associated with one of said EEG electrodes.
  • the device is configured to operate with digitized signals normalized and integerized, e.g. to be an integer in the range between 0 and 10 or in the range between 0 and 100.
  • AT 1 sec
  • any other convenient definitions of the running index k could be used without departing from the scope of the present invention.
  • the link strength between two modules can be understood as a coupling strength which determines how strongly the activity of two modules is correlated.
  • the total sublink strength of a module plays the role of a state function which characterizes the instant situation of the module and reflects the concept of each module having a plurality of internal nodes that are mutually coupled by respective sublinks.
  • the total internal coupling strength within a given module can be characterized by one scalar property called the total sublink strength.
  • EEG signals Devices and procedures for measuring EEG signals are generally known. Basically they comprise some kind of headset or other fixture for holding a plurality of EEG electrodes in contact with the subject's skull at predefined cranial positions. Each EEG electrode primarily generates a time dependent output voltage comprising a physiologically relevant signal component which is usually superimposed on a non-relevant background signal.
  • Various signal processing means for subtracting unwanted background consisting e.g. of inevitable noise and/or a constant or quasi-constant baseline signal, are known in the art.
  • signal processing means allow for transformation of analog primary EEG signals into digitized and optionally normalized EEG signals.
  • suitable transmission means serve for transmitting the various digitized and optionally normalized EEG signals to the brain performance device mentioned at the outset.
  • EEG electrodes instead of using just one EEG electrode for each module one could use a group of EEG electrodes for each module, and an input port could also serve multiple modules. Such more complex can be implemented within the signal processing sequence. The practical relevance of such arrangements will depend on the achievable signal quality, i.e. reliability, S/N ratio etc.
  • the architecture will comprise an offsite "cloud” server.
  • the predefined termination criterion is reached when k reaches its maximum value K.
  • additional termination criteria could be introduced leading to an earlier termination in certain predefined situations.
  • L(i,y) shall be understood to include both the link strength values L(i,y ' )and the self-link strength values L(i, i), that is, it applies for V(i,y) e (1, K).
  • this step firstly involves determining updated values L l s ⁇ (k and L(i,j)(k) as a function of measured signals and other properties as explained further below, and secondly it involves evaluating the instant modular performance P ( . k), as also explained further below;
  • the loop of updating operations that is carried out after each acquisition time interval comprises the following steps carried out for each module M noting again that a, ⁇ , ⁇ and ⁇ are non-negative scaling factors.
  • step A is conducted before step B.
  • ⁇ and a are positive valued scaling factors that depend on the units chosen for the various quantities. For example, if the signals S t are expressed in “mV”, the are expressed in “sublinks” and the L(i,j) are expressed in “links”, the dimension of ⁇ is “sublinks ⁇ mV "1 " and the dimension of is “sublinks ⁇ links "1 ".
  • L(i, i)(/c) L(i, i)(k - 1) + ⁇ (Sj(/c) + Sj(/c)) wherein ⁇ is a positive valued scaling factor with units of "links ⁇ mV "1 ".
  • step A is conducted after step B and will be called A' due to different indexing:
  • A' Increase total sublink strength, starting from the last available value L ⁇ ik - 1), to obtain an updated total sublink strength L l s ⁇ (k for each module i according to:
  • step A' of the second sequence uses link strengths and self-link strengths of the instant running index k, not k-1 .
  • step C is carried out after step A or A'.
  • step C an instant modular performance P (k) for a given module, which is defined as
  • some kind of partial "resetting" can be periodically performed to deactivate a certain fraction of total sublink strength of each module and/or of link strength between each pair of modules.
  • the refining criterion should be fulfilled several times before the termination criterion is fulfilled.
  • the system of the present invention progressively adopts the activity patterns of the brain regions contributing to the signals of the various electrodes.
  • This activity pattern is encoded in terms of total sublink strengths, which are a measure of neuronal performance of a given module, and in terms of link strengths, which are a measure of synesthesia type coupling between any module pairs.
  • scaling factors a, ⁇ , ⁇ and ⁇ may require some initial numerical testing, for which purpose one may use simulations runs. As will be understood, such simulation runs can be carried out in silico, i.e. by inputting realistic model EEG signals S j (/c) and computing therefrom the modular performances of interest. As a general guidance one may note the following principal effects of the various scaling factors:
  • Factors and ⁇ scale the importance of signal contribution and link strength, respectively, for the updating of sublink strength of every module i and consequent updating of modular performance.
  • Factor ⁇ affects the importance of updating of link strength between every pair of modules i and j.
  • a large value of ⁇ leads to a gradual rise of modular performance and thereby acts as an integrator of signal inputs from all channels whereas a small value of ⁇ emphasizes the effect of a specific channel input.
  • Factor ⁇ merely scales the linear relationship between instant modular performance and the underlying increase in total sublink strength. Accordingly, one can select ⁇ in order to display the calcualted performance on a convenient scale.
  • Advantageous embodiments of the invention are defined in the dependent claims and described in the examples.
  • the number of EEG electrodes should be at least 4. However, it is preferable to have a somewhat larger number of EEG electrodes, for example 10 electrodes with 5 EEG electrodes each disposed on the left side and on the right side of the skull. According to an advantageous embodiment (claim 8), the EEG electrodes of said EEG headset are arranged according to the International 10-20-System.
  • the transmission means can be configured as conventional electrical or electro-optic signal transmission lines.
  • the transmission means comprise wireless transmission means.
  • the predefined initial system state is a final system state obtained in a previous execution of the method.
  • the brain performance status P(k) at any time during execution of the method is determined from the instant modular performances P x (k) obtained so far.
  • an expanded definition of P(k) is adopted in which the instant modular performances at earlier times, i.e. values of Pi(k ⁇ k x ) are also taken into account. This could involve just a few of the most recent values.
  • weighting function for example a weighting function that progressively reduces the impact of increasingly earlier values.
  • the brain performance status is obtained according to which means averaging over the instant modular performances of all the modules.
  • the partial resetting step comprises re-scaling each one of said total sublink strengths by multiplication with a scaling factor p sub selected to be a real number between 0 and 1 .
  • This operation can be understood to be analogous to the process of apoptosis (programmed cell death) of neuronal cells.
  • the partial resetting step comprises re- scaling each one of said total link strengths by multiplication with a scaling factor p Unk selected to be a real number between 0 and 1 .
  • This operation can be understood as a process of reducing an excessive degree of synesthetic behavior that may build up during the brain mapping.
  • using scaling factor p link near 1 will have only a marginal effect, whereas low scaling factors around 0.1 or smaller will substantially erase any long term patterns accumulated during the measurement. Accordingly, scaling factors of about 0.5 will be useful for many settings.
  • a subject's brain performance can be determined within various environments in parallel with real life actions as solo or within a group. Billions of hours per day are being spent by persons in conjunction with machines, mainly driving from a point a to b; or playing games for health benefits, sports, education, fun; or carrying, wearing devices; or using robots to serve, help in small or large tasks. Therefore, the determined brain performance of a subject obtained according to the present invention provides a feedback mechanism between a subject's inner brain functionality and machines; promoting machine intelligence and improving brain health at the same time.
  • the above process runs on a suitable software platform which acts to control the modular device and the acquisition system and to display, filter, store, compare and otherwise process the results.
  • Fig. 1 a device for determining a brain performance status of a subject, in a schematic view
  • Fig. 2 a first example of a 4-channel EEG, with a first pass single peak in one EEG channel, with:
  • Fig. 3 a second example of a 4-channel EEG, with a second pass single peak in one EEG channel, with:
  • Fig. 4 a third example of a 4-channel EEG, with a complex signal pattern in all
  • EEG channels with:
  • Fig. 5 a fourth example of a 4-channel EEG, with a complex signal pattern in all
  • Fig. 6 a fifth example of a 4-channel EEG, with a repetitive peak in one EEG channel and comparatively low noise level in all channels, with:
  • Fig. 7 a sixth example of a 4-channel EEG, with a repetitive peak in one EEG
  • a device for determining a brain performance status of a subject H comprises a digital processing unit PL) formed of four mutually interconnected brain core modules M l t M 2 , M 3 and 4 .
  • Each module 3 ⁇ 4 has an input port I t for receiving a digitized EEG signal Sj(t) obtained from the subject.
  • the processing unit PL further comprises:
  • each total sublink strength is a positive real number
  • the device comprises an analog-to-digital converter A/D serving to convert the raw EEG signals S[ aw (t) acquired by means of a headset HS into corresponding digitized signals Sj(t).
  • the device also comprises suitable filters and/or discriminators, which can be configured as analog or digital components acting on the analog or digital version of the signal, respectively.
  • the device can operate with digitized signals normalized and optionally integerized, e.g. to be an integer in the range between 0 and 10 or in the range between 0 and 100, and also digitally clocked.
  • simulations were run assuming a "first pass", i.e. using a default initial state with
  • this signal input leads to a step-like increase of the link strengths L(1 ,2), L(1 ,3) and L(1 ,4) induced by the peak of S1 .
  • These are the link strengths coupled to the module excited by S1 .
  • the other link strengths, i.e. L(2,3), L(2,4) and L(3,4), but also the link strengths L(1 ,j) in the regions displaced from the signal peak S1 merely show a weak gradual increase.
  • Fig. 2c shows that the above signal input also leads to a step-like increase of the total sublink strength M1 of module 1 , again coincident with the peak of S1 , whereas M2, M3 and M4 again show a weak gradual increase.
  • Fig. 2d shows that the performance value P1 essentially matches the shape of the signal peak of S1 whereas the performance values P2, P3 and P4 in the other channels fluctuate around a very low value.
  • Example 2 the same signal sequence as that used in Example 1 was fed to a system in which the final system state of Example 1 was used as the initial system state.
  • the performance P1 has a peak coincident with the signal peak of S1 , but in contrast to the first pass case P1 remains at a significant level of about 25 a.u. after the peak.
  • Such signals lead to a correspondingly complex behavior of the link strengths (Fig. 4b), total sublink strengths (Fig. 4c) and performance (Fig. 4d).

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Abstract

La présente invention décrit un procédé de détermination de la performance cérébrale d'un sujet à partir d'un ensemble de signaux d'EEG qui utilise un dispositif comprenant une unité de traitement numérique formée d'au moins quatre modules de noyau cérébral mutuellement interconnectés (Mi) en conjonction avec un casque d'EEG muni de moyens de traitement et de transmission des signaux mesurés d'EEG au niveau des orifices d'entrée du dispositif. Chaque module de dispositif comprend un orifice d'entrée destiné à recevoir un signal numérique d'EEG Si(t) obtenu du sujet. Le procédé concerne un état du système instantané Ψ(t) défini par les paramètres suivants : • force de liaison L(i,j)(t) entre chaque paire de modules i et j; • force d'auto-liaison L(i, i)(t) de chaque module i; • résistance de sous-liaison totale L sous i tot (t) de chaque module i.
PCT/EP2017/060318 2017-05-01 2017-05-01 Procédé de détermination de la performance cérébrale d'un sujet Ceased WO2018202273A1 (fr)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN119498866A (zh) * 2025-01-20 2025-02-25 浙江普可医疗科技有限公司 脑电状态实时监测方法、装置及电子设备

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Publication number Priority date Publication date Assignee Title
WO2006073915A2 (fr) 2005-01-06 2006-07-13 Cyberkinetics Neurotechnology Systems, Inc. Routine d'entrainement d'un patient destinee a un systeme d'interface biologique
US20100324440A1 (en) 2009-06-19 2010-12-23 Massachusetts Institute Of Technology Real time stimulus triggered by brain state to enhance perception and cognition

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* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2006073915A2 (fr) 2005-01-06 2006-07-13 Cyberkinetics Neurotechnology Systems, Inc. Routine d'entrainement d'un patient destinee a un systeme d'interface biologique
US20100324440A1 (en) 2009-06-19 2010-12-23 Massachusetts Institute Of Technology Real time stimulus triggered by brain state to enhance perception and cognition

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HORSTMANN M T ET AL: "State dependent properties of epileptic brain networks: Comparative graph-theoretical analyses of simultaneously recorded EEG and MEG", CLINICAL NEUROPHYSIOLOGY, ELSEVIER SCIENCE, IE, vol. 121, no. 2, 1 February 2010 (2010-02-01), pages 172 - 185, XP026883060, ISSN: 1388-2457, [retrieved on 20091231], DOI: 10.1016/J.CLINPH.2009.10.013 *
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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN119498866A (zh) * 2025-01-20 2025-02-25 浙江普可医疗科技有限公司 脑电状态实时监测方法、装置及电子设备

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