EP3319516A1

EP3319516A1 - System and method for characterising the sleep of an individual

Info

Publication number: EP3319516A1
Application number: EP16750933.0A
Authority: EP
Inventors: Béatrice SPILUTTINI HEBERT
Original assignee: Urgotech
Current assignee: Urgotech
Priority date: 2015-07-07
Filing date: 2016-07-07
Publication date: 2018-05-16
Also published as: JP2018524084A; US20180263553A1; CA2989986A1; FR3038509B1; CN107847177A; JP6913036B2; US11051752B2; CN107847177B; FR3038509A1; KR20180026720A; WO2017006062A1

Abstract

The invention relates to a system for characterising the sleep of an individual, the characterisation system comprising: a measuring device for measuring a brain activity signal representing the brain waves; a central electronic unit for identifying, in a range of frequencies of between 9 and 16 Hz, a smaller range of sleep spindles of the individual, the smaller range of sleep spindles comprising the brain wave frequencies of the sleeping individual, having an amplitude higher than 15 µV and a duration of between 0.5 seconds and 2 seconds, and comparing, with a threshold, at least one parameter of the brain activity signal of the awake individual in the range of frequencies corresponding to the smaller range of sleep spindles; and a communication interface connected to the central unit and used to emit a warning signal perceptible by the individual when the parameter of the brain activity signal in the range of frequencies corresponding to the smaller range of sleep spindles exceeds the threshold.

Description

System and method for characterizing the sleep of an individual

The invention relates to a system and method for characterizing the sleep of an individual.

In particular, the invention applies to increasing the density (that is to say, the number over a determined period of time) and / or the amplitude of the sleep spindles (or "sleep spindles" according to the Anglo-Saxon denomination). ).

In addition, the present invention is not only for people prone to sleep disorders such as insomnia but more generally to anyone wishing to improve its recovery capacity including during or after an effort, a trip, a stressful situation or something else.

Sleep spindles are signals of cerebral electrical activity of frequencies generally between 9 and 16 Hz (Molle et al., 2011) and of amplitude ranging from 25 to 150 microvolts. There are sleep spindles of low frequencies and high frequencies, variable and specific to each individual. Sleep spindles usually last between 0.5 to 2 seconds and are the product of reticulo-thalamo cortical network activity.

Sleep spindles, as their name suggests, appear during sleep, especially during the light sleep phase (phase called sleep NREM stage N2) (De Gennaro & Ferrara, 2003, De Gennaro, Ferrara, Curcio, & Cristiani, 2001). Indeed, during this phase, we see that they appear in greater numbers. We still distinguish it in deep sleep (phase called N3 stage of sleep) but are more rare or even absent in so-called paradoxical sleep (phase called N4 stage of sleep or REM sleep). Sleep spindles are often referred to as "sleep wardens" and usually a high density of sleep spindles is associated with effective sleep. Conversely, the scientific literature has recently shown that a low density of sleep spindles seems to be a sign of sleep disturbed by stress (Dang-Vu et al., 2015).

At present, it has been shown that certain drugs in the class of hypnotic drugs cause an increase in the density of sleep spindles. Nevertheless, this type of medication seems to be only for patients with a definite symptomatology. In addition, these medications have side effects and may cause some addiction. Other techniques to improve the generation of sleep spindles should therefore be considered.

Thus, it has been developed new technologies to bring an individual to act on a biological activity by a feedback treatment, also called Biofeedback in Anglo-Saxon terminology. In the particular case of an action on a neurological or neurological activity, the neurological feedback treatment or Neuwfeedback in Anglo-Saxon terminology consists for example in a training of the individual to help him relax and encourage him to modify its cerebral activity, in particular by the production of a certain class of brain waves.

From a first study conducted on the cat (Sterman, Howe, & Macdonald,

1970), successive researches have shown that the application of neurological feedback treatment can lead to an improvement in the sleep time and sleep quality of an individual. This neurofeedback treatment device is designed to encourage the production of μ or Sensori-Motor Rhythm (SMR) waves. The frequency of these waves is generally between 9 Hz and 16 Hz. These waves appear at sleep (phase called NI stage of sleep), that is to say the transition between wakefulness and sleep. This phase is often accompanied by signs of fatigue such as yawning. This phase is the seat of waves SMR and a. A waves have a frequency generally between 8 Hz and 13 Hz and are generally associated with attention and alertness. SMR waves can also be present in a state of relaxation in the waking state. They disappear with attention. Since alpha and SMR waves may have overlapping frequencies or some filters may pass some of the brain activity corresponding to the alpha wave frequency window, the specific training of SMR waves may be compromised in the as it is the alpha waves that will be driven and not the SMR waves.

In parallel, SMR wave training is also used in various applications such as those aimed at improving the symptoms of attention deficit disorder with or without hyperactivity (Arns, Feddema, & Kenemans, 2014). relaxation and, as described in US 2013/150659, improvement of sleep (see also Cortoos et al., 2010). The training of SMR waves would allow an improvement of certain cognitive performances (Schabus et al., Brain research (2008), 1191, 127-135 and Stuart et al., Neuroscience and Biobehaviour (2011), 35, 1154-1165) and drive. However, there are certain disparities in the effectiveness of such neurological feedback treatment depending on the individual, including the fact that until now, the teaching from the prior art has always bet on a failure to take into account a personalization or a specific adaptation of such treatment to a particular individual.

The invention therefore aims to overcome the problems mentioned above.

The inventors have thus discovered that sleep spindles, which have a frequency specific to each individual, play an important role during the light sleep phase by their waking inhibitory effect. In addition, they found that the training of brainwaves in the waking state in the specific range corresponding to the sleep spindles of the individual leads to an improvement in the amplitude and density of the sleep spindles. asleep state thus contributing to improve the quality of sleep. On the other hand, according to various methods known and exposed in the prior art such as those described in the document US 2013/150659, a training of the brain waves emitted by the individual in the awake state and based on frequency intervals of Standardized SMR waves without taking into account any specific frequency range corresponding to sleep spindles specifically emitted by an individual in the asleep state, does not allow effective customization of a treatment to a particular individual. Such a treatment only allows the stimulation of certain SMR waves whose frequencies do not necessarily correspond to those of the sleeping spindles of said individual in the asleep state. This type of training, which does not guarantee or at least obtain in a simple and fast way an increase in the density and amplitude of the spindles of sleep, does not offer a satisfactory efficiency on the treatment of disorders especially sleep.

For this purpose, the invention proposes a system for characterizing the sleep of an individual, comprising:

a measurement device adapted to measure a signal of brain activity representative of the brain waves,

an electronic central unit adapted to:

identifying, in a frequency range of 9 to 16 Hz, at least a reduced range of individual sleep spindles, the reduced range of sleep spindles including brainwave frequencies of the sleepy individual having amplitude greater than 15 μν and a duration of between 0.5 seconds and 2 seconds,

comparing at least one parameter of the cerebral activity signal of the awake individual in the frequency range corresponding to the reduced range of sleep spindles, to a threshold, a communication interface connected to the central unit and adapted to emit a warning signal perceptible by the individual when the parameter of the cerebral activity signal in the frequency range corresponding to the reduced range of sleep spindles exceeds the threshold, preferably during a determined period of time, such as at least 0.25 seconds.

It is important to note that in addition to characterizing the density and / or the amplitude of sleep spindles specific to the individual, the system that is the subject of the present invention can also make it possible to characterize the individual frequency of an Alpha peak ( iAPF of English, "individual alpha peak frequency") during the first two minutes during which the eyes of the individual are closed. This characterization then informs about the best choice of filtering parameters to set up in order to select at least a reduced range of sleep spindles and / or to modify frequency parameters, for example by installing higher order filters and more specific. This selection makes it possible to avoid any overlap between the specific frequency band to be trained corresponding to the sleep spindles and the specific frequency band of the alpha waves that one does not wish to cause. These provisions make it possible to better characterize the range of reduced spindles of sleep proper to the individual and thus to improve the training. The user can thus more effectively improve the quality of his sleep.

The frequency of the alpha waves is generally between 7 and 13 Hz. The spectral power density of the alpha waves corresponds to the distribution of the amplitude in volts of these waves between the frequencies ranging from 7 to 13 Hz. alpha waves, we subtract the power spectrum between 7 and 13 Hz, that is to say the amplitude of these waves, obtained in the subject in the awake state having the eyes open to the spectrum of the same individual to the awake state with eyes closed. This amounts to keeping only the overall power spectrum of the alpha waves which therefore defines the individual frequency of the alpha peak of a particular individual. The individual frequency of the alpha peak thus corresponds to the absolute maximum of the amplitude in this frequency window ranging from 7 to 13 Hz. (Klimesch W. EEG-alpha rhythms and memory processes Int J Psychophysiol 1997; 26: 319-40) . The individual frequency of the alpha peak can be measured (in Hertz) according to another embodiment by the following calculation: a ratio of the weighted sum of the spectral powers in a frequency window between 7 and 13 Hz on the total spectral power of the alpha waves in the window, the spectral powers of the weighted sum being weighted by the frequencies of the window:

with f; the frequency i of the alpha waves, and

a; (f), the amplitude of the alpha waves at the frequency i.

Once the individual frequency of the alpha peak has been defined specifically for a particular individual, this then makes it possible to characterize a tangible boundary between the frequencies of the alpha waves and those of the sleep spindles of the individual in question and therefore of to free the set of alpha waves with a frequency close to that of the sleep spindles in order to allow an analysis of the frequencies of unpolluted sleep spindles by the frequencies of the alpha waves.

Thus, according to another embodiment, the characterization system comprises an electronic central unit which is adapted to identify, beforehand, the sleep spindles and within a frequency window of between 7 and 13 Hz, the individual frequency of the alpha peak of the 'individual.

The latter is therefore defined within a window of frequencies between 7 and 13 Hz and after subtraction of the power spectrum obtained in an individual with open eyes from that obtained in an individual with eyes closed.

In addition, the question of the specificity of the training can also be improved by measuring this individual frequency of the alpha waves in order to provide a more specific feedback at the level of the generation of the spindles of sleep while avoiding that a unwanted alpha signal does not interfere with these.

The characterization system implements, during the first use or at each new use, a learning phase to specifically characterize the individual's sleep by identifying the sleep zones that are specific to him and to allow him to driving said sleep spindles. By particularizing each individual the range of frequencies to be trained, the effectiveness of the neurological feedback treatment on a set of individuals can be improved.

In order to identify the reduced range (s) of sleep spindles, the electronic central unit may be adapted to detect, in the 9 to 16 Hz frequency range of the cerebral activity signal of the sleeping individual, the brain waves of the sleeping individual with an amplitude greater than 15 μν and a duration between 0.5 seconds and 2 seconds. Alternatively, to identify the reduced range of sleep spindles, the electronic central unit can be adapted to:

determining, in the 9 to 16 Hz frequency range of the cerebral activity signal of the sleeping individual, a plurality of reduced ranges of frequencies,

comparing the cerebral activity signal parameter of the sleeping individual in each of the reduced frequency ranges at the threshold,

- define the reduced range of sleep spindles as the reduced range of frequencies in which the cerebral activity signal exceeds the threshold at a greater number of times.

The measuring device may comprise:

a support intended to be placed on the head of the individual, and

at least one ground electrode, a reference electrode and a measurement electrode, which can optionally be combined within the same electrode having both functions, more particularly for the reference and measurement functions, connected to the CPU and arranged on the support for measuring an electrical potential difference between the reference, mass and measurement electrodes as a cerebral activity signal.

The central unit can be mounted on the support and be adapted to amplify the cerebral activity signal.

The central unit can be adapted to digitize the cerebral activity signal.

The reference electrodes, but also the ground and measurement electrodes can be dry electrodes. They may, however, also be wet electrodes semi-dry electrodes or semi-wet electrodes. According to a particular embodiment of the invention, each type of electrode may have a particular and different nature.

The communication interface can be portable by hand by the individual.

The central unit can be within a headset connected to the communication interface or within an external device or remote, such as a server.

The CPU may be adapted to modify, i.e., raise or lower, the threshold and / or a time period above the threshold.

The parameter of the cerebral activity signal may be selected from an amplitude and a density.

According to a second aspect, the invention proposes a method for characterizing the sleep of an individual, comprising the steps of: measure a signal of brain activity representative of the brain waves,

identifying, in a frequency range of 9 to 16 Hz, at least a reduced range of individual sleep spindles, the reduced range of sleep spindles including brainwave frequencies of the sleeping individual having a amplitude greater than 15 μν and a duration of between 0.5 seconds and 2 seconds,

comparing at least one parameter of the cerebral activity signal of the awake individual in the frequency range corresponding to the reduced range of sleep spindles to a threshold and emitting a warning signal perceptible to the individual when the parameter of the signal of cerebral activity in the frequency range (s) corresponding to the reduced range (s) of sleep spindles exceeds the threshold.

The step of identifying the reduced range of sleep spindles may include detecting, within the 9 to 16 Hz frequency range of the cerebral activity signal of the dormant individual, brain waves of the sleeping individual exhibiting an amplitude greater than 15 μν and a duration of between 0.5 seconds and 2 seconds.

Alternatively, the step of identifying the reduced range of sleep spindles may include:

a determination, in the 9 to 16 Hz frequency range of the cerebral activity signal of the sleeping individual, of a plurality of reduced frequency ranges,

a comparison of the cerebral activity signal parameter of the sleeping individual in each of the reduced frequency ranges at the threshold,

a definition of the reduced range of sleep spindles as the reduced range of frequencies in which the parameter of the cerebral activity signal exceeds the threshold at a greater number of times.

According to another embodiment, the method of characterization may comprise during the step of identifying the reduced range of sleep spindles, a prior identification of the individual frequency of the individual's alpha peak, defined within a window of frequencies between 7 to 13 Hz. The spectral power density of the alpha waves corresponds to the distribution of the amplitude in volt of these waves between the frequencies ranging from 7 to 13 Hz. To obtain the signal of the alpha waves, one subtract the power spectrum between 7 and 13 Hz, that is to say the amplitude of these waves, obtained in the awake subject having the eyes open to the spectrum of the same individual in the awake state having the eyes closed. The individual frequency of the alpha peak thus corresponds to the absolute maximum of the amplitude in this frequency window ranging from 7 to 13 Hz. (Klimesch W. EEG-alpha rhythms and memory processes. Int J Psychophysiol 1997; 26: 319-40). The individual frequency of the peak alpha can be measured (in Hertz), according to another embodiment, by the following calculation: a ratio of the weighted sum of the spectral powers in a frequency window of between 7 and 13 Hz on the spectral power total of the alpha waves in the window, the spectral powers of the weighted sum being weighted by the frequencies of the window:

with f; the frequency i of the alpha waves, and

ai (fi), the amplitude of the alpha waves at the frequency i.

Once the individual frequency of the alpha peak is defined specifically for a particular individual, it then makes it possible to characterize one or more tangible terminals making it possible to discriminate the frequencies of the alpha waves and those of the sleep spindles of the individual in question. thus to get rid of all the alpha waves having a frequency close to that of the sleep spindles in order to allow an analysis of the frequencies of the spindles of unpolluted sleep by the frequencies of the alpha waves.

The step of measuring the cerebral activity signal may include measuring an electrical potential difference between reference, mass and measurement electrodes.

The characterization process can provide:

prior to the step of comparing the parameter of the cerebral activity signal with the threshold, of amplifying the cerebral activity signal and

during the step of comparing the parameter of the cerebral activity signal with the threshold, comparing the parameter of the amplified brain activity signal with the threshold.

The characterization process can provide:

prior to the step of comparing the parameter of the cerebral activity signal with the threshold, digitizing the cerebral activity signal and

during the step of comparing the parameter of the cerebral activity signal with the threshold, comparing the parameter of the digitized cerebral activity signal with the threshold.

The characterization method may provide, during the step of comparing the parameter of the cerebral activity signal to the threshold, to modify the threshold. By "Change threshold" means any action to raise or lower the threshold level.

The method of characterization may provide, during the step of comparing the parameter of the cerebral activity signal to the threshold, to select the parameter from an amplitude and a density.

Other objects and advantages of the invention will appear on reading the following description of a particular embodiment of the invention given by way of non-limiting example, the description being made with reference to the appended drawings in which :

FIG. 1 is a representation of a sleep characterization system of an individual, comprising a measuring device in the form of a helmet adapted to measure a cerebral activity signal representative of the brain waves, and a central unit electronics adapted to identify at least a reduced range of individual sleep spindles, and a portable hand-held communication interface for providing a warning signal when a cerebral activity signal parameter in the reduced range of sleep spindles exceeds a threshold,

FIG. 2 is a schematic representation of the frequency ranges of α waves and μ or Sensori-Motor Rhythm (SMR) waves emitted in the drowsiness phase, and sleep spindles (spindle) emitted in the sleep phase. light by two different individuals,

FIG. 3 is a representation of the cerebral activity signal representative of the brain waves of the individual acquired by the measuring device of FIG. 1, identifying the reduced range of sleep spindles specific to the individual,

FIG. 4 is a diagram illustrating a method of characterization of sleep implemented by the sleep characterization system of FIG. 1.

In the figures, the same references designate identical or similar elements.

FIG. 1 shows an embodiment of a user 2 sleep characterization system 1 for use in neurological feedback processing to improve the user's sleep speed and sleep quality 2.

The characterization system 1 comprises:

a measuring device 5 adapted to measure a cerebral activity signal representative of the brain waves of the user's brain 2, and

an electronic central unit 21 for processing the cerebral activity signal, a communication interface 22 with the user 2.

The measuring device 5 is in the form of a helmet 6 comprising a support 7, possibly adjustable, intended to be placed on the head of the user 2. The cerebral activity signal is measured in the form of a electrical potential difference between one or more reference electrodes 8, a ground electrode 11 and one or more measuring electrodes 9 arranged on the support 7 as appropriate. The reference electrodes 8, 9 and mass 11 are preferably dry electrodes.

The reference electrodes 8, of mass 11 and measurement 9 and the electronic processor are connected by a wired link 23 or wirelessly to the central unit 21. The central unit 21 may comprise an electronic processor, an amplifier adapted to amplify the cerebral activity signal and an analog-to-digital converter adapted to digitize the cerebral activity signal. The cerebral activity signal acquired by the reference electrodes 8, of mass 11 and measuring electrode 9 and then digitized and amplified can thus be transmitted to the processor of the central processing unit 21 for processing. Without being limited thereto, and the central unit 21 may be provided in the helmet 6.

The central unit 21 is connected to the communication interface 22 with the user. In the embodiment shown, the communication interface 22 comprises two earphones 10 mounted on the helmet 6 to be placed on the ears of the user 2 in order to be able to deliver a sound warning signal representative of the transmission of a particular brain wave. The communication interface 22 also includes any other appropriate electronic device portable by hand such as a mobile phone, a tablet, a PDA or other. The communication interface 22 may in particular comprise a screen for displaying a warning signal, in particular a visual signal. The screen can be touch-sensitive to interact with the central unit 21. In a complementary or alternative way, an interaction with the central unit 21 can be obtained via a keyboard, one or more activation buttons. , a memory card reader or other belonging to the communication interface 22.

Figure 2 illustrates the frequency decomposition of the cerebral activity signal of two individuals.

In a phase of drowsiness and sleep, the brain activity of each individual, then in a waking state, is characterized by: - waves emitted in a frequency range between 8 Hz and 13 Hz for one of the individuals identified as subject 1, and in a frequency range between 8 Hz and 12 Hz for the other individual identified as subject 2 ,

- μ or Sensori-Motor Rhythm (SMR) waves transmitted in a frequency range between 12 Hz and 15.5 Hz for subject 1 and subject 2.

In a light sleep phase, the brain activity of each individual, then in a sleep state, is characterized by sleep spindles or spindles emitted in a reduced range of sleep spindles between 12 Hz and 15 Hz for the subject 1, and in a reduced range of sleep spindles between 13.5 Hz and 16 Hz for subject 2. It appears that the reduced range of sleep spindles, whose waking inhibitory effect plays an important role during the light sleep phase, is specific to each individual.

In order to characterize the sleep of the user 2, the central unit 21 is adapted to perform a frequency decomposition of the cerebral activity signal and to identify, in a frequency range of 9 to 16 Hz, the range or ranges. ) In particular, the reduced range (s) of sleep spindles comprise the brainwave frequencies of the user 2 in the state. asleep having an amplitude greater than 15 μν and a duration of between 0.5 seconds and 2 seconds.

As shown in FIG. 3 which illustrates a signal of brain activity acquired in the light sleep phase of the user 2, the identification of a reduced range of sleep spindles can be performed in the asleep state of the user 2 by detecting, in the 9 to 16 Hz frequency range of the cerebral activity signal during the light sleep phase, brain waves having an amplitude greater than 15 μν and a duration of between 0.5 second and 2 seconds.

Alternatively, identification of the reduced range of sleep spindles could be accomplished by an iterative process of modulating a reduced range of frequencies to identify the reduced range of frequencies corresponding to that of the sleep spindles. In particular, the iterative process provides for determining, in the 9 to 16 Hz frequency range of the cerebral activity signal of the sleeping individual, a plurality of reduced frequency ranges. In each of the reduced frequency ranges, a parameter, such as an amplitude or a density, that is to say a number of peaks having a minimum amplitude over a determined period of time, of the cerebral activity signal of the individual asleep is compared to a representative threshold of the same parameter for sleep spindles. The reduced range of sleep spindles can then be defined as the reduced range of frequencies in which the signal of brain activity exceeds the threshold at a greater number of times.

In the awake state of the user 2, the central unit 21 can then compare at least one parameter of the cerebral activity signal to the awake state in the frequency range corresponding to the reduced range of sleep spindles to one. threshold. The frequency range corresponding to the reduced range of sleep spindles is different, generally narrower and possibly offset, from the SMR frequency range. The parameter is, for example, chosen from an amplitude and a density, that is to say a number of peaks having a minimum amplitude determined over a predetermined period.

The central unit 21 is then adapted to control the transmission of the audible warning signal in the earphones 10 and the visual warning signal on the screen of the communication interface 22 when the parameter of the cerebral activity signal in the frequency range corresponding to the reduced range of sleep spindles exceeds the threshold, preferably for a specified period of time, such as at least 0.25 seconds.

In connection with FIG. 4, a method of characterizing the sleep of the user implemented with the characterization system is now described.

In the asleep state, the difference in electrical potential between the reference electrodes 8, of mass 11 and measurement 9 is measured by the headphones 6 to obtain the cerebral activity signal representative of the brain waves of the user 2. This cerebral activity signal is amplified and digitized by the central unit 21.

In the 9 to 16 Hz frequency range of the cerebral activity signal in the light sleep phase, the central unit 21 identifies the reduced range of sleep spindles of the user 2. This reduced range of sleep spindles includes the brainwave frequencies of the sleeping user having an amplitude greater than 15 μν and a duration of between 0.5 seconds and 2 seconds.

In the awake state, the difference in electrical potential between the reference electrodes 8, of mass 11 and measurement 9 is measured by the headphones 6 to obtain the cerebral activity signal representative of the brain waves of the user 2. This cerebral activity signal is amplified and digitized by the central unit 21. In the frequency range corresponding to the reduced range of sleep spindles, the CPU 21 compares to the threshold at least one of the following two parameters such as amplitude or density.

When the parameter of the cerebral activity signal in the frequency range corresponding to the reduced range of sleep spindles exceeds the threshold, if necessary beyond the determined time period, the audible warning signal is emitted in the 10 and the visual warning signal is displayed via the communication interface 22. Complementarily or alternatively, the communication interface 22 can be adapted to issue any other type of warning signal and in particular , tactile, olfactory or taste.

The user 2 is thus warned of the emission of brain waves promoting the quality of sleep.

From this sleep characterization, a Neurofeedback treatment can be set up to improve the quality of the user's sleep 2. The Neurofeedback treatment then comprises a training aimed at encouraging the user 2 to produce the desired brain waves. . The training includes one or more relaxation and exercise sequences rewarding the emission of brain waves desired by particular warning signals.

During training, the threshold may be increased to advance user 2 in the production of appropriate brainwaves. During training, the threshold can also be lowered to make it easier for a user who is not performing well. Complementarily or alternatively, it is possible to play on the determined period during which the threshold must be exceeded to emit the warning signal to complicate or simplify training.

Claims

1. System for characterizing (1) the sleep of an individual (2), the characterization system (1) comprising:

a measurement device (5) adapted to measure a signal of brain activity representative of the brain waves,

an electronic central unit (21) adapted to:

identifying, in a frequency range of 9 to 16 Hz, at least a reduced range of sleep spindles specific to the individual (2), the reduced range of sleep spindles including brainwave frequencies of the individual ( 2) asleep with an amplitude greater than 15 μν and a duration of between 0.5 seconds and 2 seconds,

comparing at least one parameter of the cerebral activity signal of the individual (2) awake in the frequency range corresponding to the reduced range of sleep spindles to a threshold,

a communication interface (22) connected to the central unit (21) and adapted to emit a warning signal perceptible by the individual when the parameter of the cerebral activity signal in the frequency range corresponding to the reduced range; of spindles of sleep exceeds the threshold.

The characterization system (1) according to claim 1, wherein to identify the reduced range of sleep spindles, the electronic central unit (21) is adapted to detect, in the frequency range of 9 to 16 Hz of the signal of cerebral activity of the sleeping individual (2), brain waves of the sleeping individual (2) having an amplitude greater than 15 μν and a duration of between 0.5 seconds and 2 seconds.

The characterization system (1) according to claim 1 or 2, wherein to identify the reduced range of sleep spindles, the electronic central unit (21) is adapted to first identify an individual frequency of an alpha peak. the individual (2), said frequency being defined as a ratio of a weighted sum of spectral powers in a window of frequencies between 7 and 13 Hz on a total spectral power of alpha waves in the window, the spectral powers of the weighted sum being weighted by the frequencies of the window: with fj the frequency i of the alpha waves, and

ai (fi), the amplitude of the alpha waves at the frequency i.

The characterization system (1) according to any one of claims 1 to 3, wherein the measuring device (5) comprises:

a support (7) intended to be placed on the head of the individual (2), and

at least one reference electrode (8), a ground electrode (11) and a measuring electrode (9) connected to the central unit (21) and arranged on the support (7) for measuring an electric potential difference between the reference (8), mass (11) and measurement electrodes (9) as a cerebral activity signal.

5. Characterization system (1) according to claim 4, wherein the central unit (21) is mounted on the support (7) and is adapted to amplify the cerebral activity signal.

The characterization system (1) according to claim 5, wherein the central unit (21) is adapted to digitize the cerebral activity signal.

7. Characterization system (1) according to any one of claims 4 to 6, wherein the reference electrodes (8), the ground electrode (11) and the measuring electrode (9) are dry electrodes .

8. Characterization system (1) according to any one of claims 1 to 7, wherein the communication interface (22) is portable by hand by the individual (2).

9. Characterization system (1) according to any one of claims 1 to 8, wherein the central unit (21) is adapted to change the threshold and / or a period of time above the threshold.

The characterization system (1) according to any one of claims 1 to 9, wherein the parameter of the cerebral activity signal is selected from an amplitude and a density.

11. A method of characterizing the sleep of an individual (2), comprising the steps of:

measure a signal of brain activity representative of the brain waves,

identifying, in a frequency range of 9 to 16 Hz, at least a reduced range of sleep spindles specific to the individual (2), the reduced range of sleep spindles including brainwave frequencies of the individual (2) asleep having an amplitude greater than 15 μν and a duration of between 0.5 seconds and 2 seconds,

comparing at least one parameter of the cerebral activity signal of the awake individual (2) in the frequency range corresponding to the reduced range of sleep spindles at a threshold and emit a perceptible warning signal by the individual when the cerebral activity signal parameter in the frequency range corresponding to the reduced range of sleep spindles exceeds the threshold.

The method of characterization according to claim 11, wherein the step of identifying the reduced range of sleep spindles comprises detecting, in the frequency range of 9 to 16 Hz, the signal of brain activity of the individual ( 2) asleep, brain waves of the sleeping individual (2) having an amplitude greater than 15 μΥ and a duration between 0.5 seconds and 2 seconds.

The method of characterization according to claim 11 or 12, wherein the step of identifying the reduced range of sleep spindles comprises a prior identification of an individual frequency of an alpha peak of the individual (2), said frequency being defined as a ratio of a weighted sum of spectral powers in a window of frequencies between 7 and 13 Hz on a total spectral power of the alpha waves in the window, the spectral powers of the weighted sum being weighted by the frequencies of the window :

with fj the frequency i of the alpha waves, and

a; (f), the amplitude of the alpha waves at the frequency i.

The method of characterization according to any one of claims 11 to 13, wherein the step of measuring the cerebral activity signal comprises a measurement of an electrical potential difference between reference electrodes (8), mass (11) and measuring (9).

15. A method of characterization according to any one of claims 11 to 14, providing:

16. A method of characterization according to any one of claims 11 to 15, providing: prior to the step of comparing the parameter of the cerebral activity signal with the threshold, digitizing the cerebral activity signal and

17. A method of characterization according to any one of claims 1 to 16, providing, during the step of comparing the parameter of the cerebral activity signal to the threshold, to modify the threshold.

18. A method of characterization according to any one of claims 1 to 17, providing, during the step of comparing the parameter of the cerebral activity signal threshold, to choose the parameter from an amplitude and a density.