FR3102054A1 - Helmet to improve the balance of the sympathovagal balance of an individual - Google Patents

Abstract

The invention describes a helmet intended to be worn by an individual so as to improve the balance of his sympathovagal balance, characterized in that it comprises: a sensor for acquiring pulsed oxygen saturation (SpO2) (22), - at least one acquisition electrode (21) of a brain wave, - a processing unit (30) configured to determine, from data acquired by the SpO2 acquisition sensor (22) and by at least one acquisition electrode (21) of a cerebral wave, a mechanical wave characteristic adapted to improve the balance of the sympathovagal balance, - at least one transducer (23) configured to emit a mechanical wave, a characteristic of the mechanical wave corresponding to the characteristic determined by the processing unit (30). The invention also describes a method for improving the balance of the sympathovagal balance of an individual. Figure for the abstract: Fig. 5

Description

Helmet to improve the balance of the sympatho-vagal balance of an individual

FIELD OF THE INVENTION

The present invention relates to the field of devices intended to influence the activity of the nervous system. In particular, the present invention relates to the field of devices adapted to improve the balance between the activity of the sympathetic and parasympathetic nervous systems of an individual, that is to say to improve the balance of the sympathovagal balance. of an individual.

TECHNOLOGICAL BACKGROUND

The brain is made up of two hemispheres, which include neurons communicating by electrical type messages. Brain activity refers to an electromagnetic oscillation in a given frequency band resulting from the coherent electrical activity of a large number of neurons in the brain. The different types of waves emitted by the human brain are of the order of microvolts, generally between 0 and 200μV. Their shape and regularity depend, for example, on the psychological or physical state of the individual, or on pathological symptoms.

The cerebral activities of the brain are classified according to five types of waves distinguished by their frequency. Signals corresponding to each of these five types of waves are illustrated by way of example in figure 1. Each wave is associated with a particular brain state:

- Alpha waves correspond to frequencies between 8 and 13 Hz. They characterize a state of relaxation, of peaceful and calm consciousness. They usually appear when the subject has their eyes closed and can increase certain performance, improve mood and reduce anxiety.

- Beta waves correspond to frequencies between 13 Hz and 30 Hz. They appear during periods of mental activity, concentration, state of alert or anxiety, when the brain is in active standby. They stimulate and wake up the brain and help to improve its mental and physical performance, for example memory performance.

- Gamma waves correspond to frequencies above 30 Hz, which can go up to 100 Hz. They are involved in the processes of perceptual binding. These waves stimulate the connections between neurons and improve capacities, in particular long-term memory. They appear during intense mental activity.

- Delta waves correspond to frequencies from 0.1 to 4 Hz. They appear during certain pathological states or deep sleep. Delta waves induce sleep as well as waking dream phenomena. These waves promote natural drowsiness which helps to fall asleep, and increase the production of melatonin, which the body produces during deep and natural sleep.

- Theta waves correspond to frequencies between 4 and 8 Hz. They appear during certain states of drowsiness, hypnosis, deep relaxation or meditation, or when memorizing information. Theta waves promote learning by improving concentration and focus, as well as creativity. These waves help to reduce stress, as well as negative thoughts and emotions.

Heart rate is the interval between two contractions of the heart. Heart Rate Variability (HRV) refers to fluctuations in heart rate. Brain waves are correlated to HRV and can alter HRV.

HRV monitoring is important in order to detect risks of high blood pressure, stress, sleep disorders, cardiovascular and coronary pathologies or even heart failure. Indeed, a decrease in HRV is associated with such risks, while a high HRV indicates a good immediate ability of the heart to adapt to stresses, and is thus both a sign and a factor of health. After a myocardial infarction, for example, the decrease in heart rate variability is a predictive factor for mortality and serious arrhythmia.

The HRV can be measured in a known way using an electrocardiogram, which measures all the electrical signals of the heart, or by photoplethysmography. Nevertheless, the electrocardiogram is an examination that must be carried out in a medical environment, with special equipment, and which requires placing electrodes in various places on the individual's body, which makes it impractical and unsuitable for follow-up. daily, in real time.

The nervous system is considered responsible for our behavior. Thanks to the sensitive, integrative and motor functions of the nervous system, we can move, walk, smell, see, hear but also speak, memorize, recognize, experience emotions and develop strategies and reasoning.

Structurally, the nervous system consists of the central nervous system, which includes the brain and spinal cord, and the peripheral nervous system, consisting of the cranial and spinal nerves. This system allows the maintenance of the balance, essential for survival, of certain biological constants of the internal environment.

The autonomic nervous system is, along with the somatic nervous system, one of the two components of the peripheral nervous system. The autonomic nervous system includes:

- The sympathetic system, which is essentially involved in alert reactions. It prepares the body for a rapid reaction to attacks from the external environment.

- The parasympathetic system, which is essentially involved in normal physiological conditions and in relaxation responses. Among other things, it controls heart rate and respiratory activity, digestive activity and blood pressure. Its activation helps to reduce heart and respiratory rates, and to lower blood pressure.

The balance between the activity of the sympathetic system and the activity of the parasympathetic system characterizes the equilibrium of the sympathovagal balance.

An imbalance in the sympathovagal balance can induce pathologies, in particular vascular and respiratory or cardiac risks.

The various physiological parameters such as brain activity, electrical signals from the heart, respiratory information and their monitoring, are key and correlated indicators, making it possible to identify such pathologies in a preventive manner.

In particular, brain waves act on the sympatho-vagal balance, for example by influencing HRV. The electrical activity of neurons in the brain can be observed using an electroencephalogram, using electrodes placed on the skull. The recording makes it possible to observe electromagnetic oscillations corresponding to the different types of waves emitted by the brain, as illustrated for example in figure 2. Thus, the recording of cerebral activity makes it possible to study the functioning of the brain. , to detect or characterize neurological diseases.

The recording of brain activity also makes it possible to study the phases of sleep. Examinations such as polysomnography (examination which integrates the measurement of brain waves, heart and SPO2) and polygraphy, allow the detection of sleep disorders, TROS (obstructive respiratory sleep disorders), or OSAS (syndrome obstructive sleep apnea). Thus, it is possible to prevent cardiac, vascular and respiratory decompensations.

However, these one-off examinations do not allow permanent support for the individual on a daily basis. In addition, they are restrictive to carry out, and require the individual to travel to a hospital environment in order to be taken care of.

However, some individuals could benefit from home monitoring and be treated at home, in a favorable social and family context and with adequate psychological support.

Devices, in particular connected devices, offer real-time and home monitoring of an individual's physiological parameters. They thus allow a permanent accompaniment of the individual, improve his quality of life, reduce the stress of the individual and his close relations and offer a preventive orientation of the disease. In addition, such connected devices lighten the burden on specialized services by optimizing care and treatment, thus limiting health expenditure, while guaranteeing better quality follow-up for the individual.

Connected medical devices, for example to smartphones or tablets, make it possible to measure and process physiological parameters in real time. Indeed, on-board sensors and microcontrollers now offer calculation systems integrating mathematical libraries and allowing the continuous processing of acquired data, the detection of anomalies from control parameters, as well as the generation of alerts for the doctor.

The physiological activity of the individual can thus be monitored in real time, cardiovascular and respiratory anomalies can be detected early, while guaranteeing quality monitoring of hospital environments.

Document US 2014/0114165 describes a connected device placed on a bone puck of an individual and comprising brain wave acquisition electrodes. The device further comprises means for transmitting the acquired data to a computer processor.

Document US 2009/0076405 describes a connected patch comprising brain wave acquisition electrodes, in order for example to carry out sleep studies of an individual, and comprising means for transmitting the acquired data.

Nevertheless, these devices are content to acquire physiological parameters in order to monitor them, but do not make it possible to influence the balance of the sympathovagal balance. In particular, these devices do not make it possible to modify the activity of neurons by regulating brain waves in certain regions of the brain, in order to induce a specific state of the brain. They are therefore limited to a follow-up role, but cannot help reduce cardiovascular and respiratory risks.

Medications can be used to alter brain function. Nevertheless, the drugs are expensive, must be taken at regular intervals, and can induce undesirable side effects for the individual.

An object of the invention is to propose a helmet making it possible to modify the cerebral activity and to rebalance the sympathovagal balance of an individual.

Another object of the invention is to improve the monitoring of an individual and the prevention of diseases, in particular of the neurovascular, neurodegenerative, neuromotor and respiratory type.

Another object of the invention is to allow real-time and home monitoring of an individual wearing this helmet.

According to a first aspect, the invention relates to a helmet intended to be worn by an individual so as to improve the balance of the sympatho-vagal balance of said individual, the helmet being characterized in that it comprises:
- a pulsed oxygen saturation acquisition sensor,
- at least one brain wave acquisition electrode,
- a processing unit configured to determine, from data acquired by the SpO2 acquisition sensor and by the at least one brain wave acquisition electrode, a mechanical wave characteristic adapted to improve the balance of the sympatho-vagal balance,
- at least one transducer configured to emit a mechanical wave, a characteristic of the mechanical wave corresponding to the characteristic determined by the processing unit.

Some preferred but non-limiting features of the helmet described above are as follows, taken individually or in combination:

- the mechanical wave intended to be emitted by the at least one transducer is an acoustic wave;

- the mechanical wave intended to be emitted by the at least one transducer is a binaural wave;

- the acoustic or binaural mechanical wave characteristic is a frequency;

- the mechanical wave intended to be emitted is transmitted by bone conduction;

- the helmet further comprises a temperature sensor;

- said at least one acquisition electrode is suitable for acquiring at least one cerebral wave from among an alpha wave, a beta wave, a gamma wave, a theta wave, and a delta wave;

- the helmet includes ten acquisition electrodes and two transducers;

- the helmet further comprises a support adapted to be positioned on an individual's head, the support being configured to ensure the maintenance of the SpO2 acquisition sensor, of the at least one acquisition electrode and of the at least one transducer, the support comprising a rigid part and an elastic part;

- the processing unit comprises storage means suitable for storing data acquired during a time interval greater than one day, preferably greater than seven days;

- the processing unit comprises signal processing means suitable for carrying out a frequency analysis by wavelets of the acquired SpO2 and of the acquired cerebral wave;

- the processing unit comprises a communication module configured to communicate with a mobile device via a wireless link.

According to a second aspect, the invention also relates to a system for improving the balance of the sympatho-vagal balance of an individual, comprising a helmet according to the first aspect and a mobile device with which the processing unit of the helmet is configured to communicate.

The mobile device can comprise a parameterization interface suitable for parameterizing the processing unit, and a communication interface suitable for transferring data via an access network.

According to a third aspect, the invention also relates to a method intended to improve the balance of the sympatho-vagal balance of an individual, the method comprising the following steps:

- a step of acquisition of a pulsed oxygen saturation by an SpO2 acquisition sensor and acquisition of a cerebral wave by at least one electrode for acquisition of a cerebral wave,

- a step of determining a mechanical wave characteristic adapted to improve the balance of the sympatho-vagal balance, by a processing unit and from data acquired during the acquisition step,

- a step of emission of a mechanical wave by at least one transducer, a characteristic of the mechanical wave emitted corresponding to the characteristic determined during the determination step.

The mechanical wave can be an acoustic wave, or even a binaural wave.

The mechanical wave characteristic may be a frequency.

According to a fourth aspect, the invention also relates to a computer program product comprising code instructions for the execution of the method of improving the balance of the sympatho-vagal balance according to the third aspect.

PRESENTATION OF FIGURES

Other aspects, aims and advantages of the present invention will appear on reading the detailed description which follows, given by way of non-limiting example, which will be illustrated by the following figures:

FIG. 1, already commented on, is a graph illustrating signals corresponding to different waves likely to be emitted by the brain.

FIG. 2, already commented upon, represents a graph illustrating an electroencephalogram signal.

FIG. 3 represents a diagram illustrating the architecture and the interactions of a processing unit in accordance with an embodiment of the invention.

FIG. 4 represents a diagram illustrating lobes of the brain.

FIG. 5 represents a diagram in side view of elements of a helmet according to one embodiment of the invention.

FIG. 6 represents a diagram in top view of elements of a helmet according to one embodiment of the invention.

FIG. 7 represents a diagram in front view of a support for a helmet according to one embodiment of the invention.

FIG. 8 represents a diagram in side view of a support for a helmet according to one embodiment of the invention.

Figure 9 shows a diagram of a method according to one embodiment of the invention.

FIG. 10 represents a diagram in side view of a support for a helmet according to one embodiment of the invention.

FIG. 11 represents a diagram in side view of a support for a helmet according to one embodiment of the invention.

DETAILED DESCRIPTION OF AN EMBODIMENT

A helmet intended to be worn by an individual so as to improve the balance of the sympatho-vagal balance of said individual is shown by way of non-limiting example in Figures 5 to 8. The helmet comprises:
- a sensor for acquiring pulsed oxygen saturation (SpO2) 22,
- at least one acquisition electrode 21 of a cerebral wave,
- a processing unit 30 configured to determine, from data acquired by the SpO2 acquisition sensor 22 , by the at least one acquisition electrode 21 of a cerebral wave and the acquisition sensor of the 24 temperature, a mechanical wave characteristic suitable for improving the balance of sympatho-vagal balance,
- at least one transducer 23 configured to emit a mechanical wave, a characteristic of the mechanical wave corresponding to the characteristic determined by the processing unit 30.

The helmet is intended to be used, for example, by individuals at risk or subject to neurovascular or cardio-respiratory diseases, neurological disorders (depressive, behavioral or motor disorders), or any other disease likely to be affected by a balance between the activity of the sympathetic and parasympathetic nervous systems.

The helmet is intended to be worn for varying periods of time, which may be short or long. For example, an individual may wear the helmet for periods of several minutes to several hours, or even days, at a stretch. The helmet can be worn at night and/or during the day, regardless of the individual's activity or sleep state.

Such a helmet, when it is put in place at the level of a head 1 of the individual, makes it possible to acquire the cerebral waves at the level of the skull, that is close to their place of emission, which improves the quality and the amplitude of the acquired signal.

The emission of a mechanical wave whose characteristic depends on the acquired data makes it possible to balance the sympathovagal balance, by influencing the activity of at least one of the sympathetic nervous system and the parasympathetic nervous system.

Indeed, such a mechanical wave emission makes it possible to implement a feedback control of the cerebral waves: when a variation of a cerebral wave is detected by the processing unit 30, the latter can adapt the characteristic of the wave mechanism to be emitted by the transducers 23 so as to restore the balance of the sympatho-vagal balance. Restoring the balance of the sympathovagal balance helps to improve memory, reduce stress, and restore a good heart rhythm.

For example, when the processing unit 30 detects a drop in a certain brain wave, or detects the presence of an unwanted brain wave, the transducers 23 can emit the appropriate mechanical wave in order to restore the balance of the sympatho-vagal balance.

The at least one acquisition electrode 21 of a cerebral wave can be any electrode suitable for acquiring an electroencephalogram signal. In particular, the at least one acquisition electrode 21 can be adapted to acquire at least one cerebral wave from among an alpha, beta, gamma, delta and/or theta wave.

The at least one acquisition electrode 21 can be a comb-shaped silicone and carbon electrode. As a variant, the at least one acquisition electrode 21 can have any other material and/or shape suitable for acquiring the desired cerebral wave.

The helmet can comprise more than two acquisition electrodes 21. The electrodes 21 can be distributed on the helmet according to any arrangement allowing satisfactory acquisition of the cerebral waves. The acquisition electrodes 21 can be identical or different from each other. The electrodes 21 can each be connected to the processing unit 30 by separate wiring, so as to ensure the independence of the measurements of each acquisition electrode 21.

The lobes of the brain are illustrated schematically in FIG. 4, and include the frontal lobe 11, the parietal lobe 12, the temporal lobe 13, the occipital lobe 14 and the cerebellum 15. The acquisition electrodes 21 can be placed at the level at least one lobe 11, 12, 13, 14, 15 of the brain. In particular, the electrodes 21 can be placed at the level of at least the frontal lobe 11, the parietal lobe 12 and the occipital lobe 14, so as to pick up the signals coming from these lobes 11, 12, 14.

The pulse oxygen saturation (SpO2) acquisition sensor 22, which corresponds to the level of oxygen saturation in the blood, can be a pulse oximeter sensor, or any other sensor suitable for measuring pulse oxygen saturation. .

A pulse oximeter measures SpO2 by emitting two lights, for example red and infrared lights, and measuring their absorption by pulsatile flow.

Too low SpO2 can cause respiratory problems such as asthma or chronic obstructive pulmonary disease, and be correlated with sleep apnea. In addition, the measurement of SpO2 makes it possible to obtain a photoplethysmography curve. From the period of the photoplethysmographic wave pulses, heart rate variability (HRV) and heart rate can be estimated. The SpO2 measurement can therefore represent an alternative to the electrocardiogram, less restrictive than the latter and less expensive to implement, to determine the HRV. In addition, SpO2 measurement can be performed in real time, without requiring the individual to travel to a medical office.

As a variant, the helmet can comprise several SpO2 acquisition sensors 22, or any other means making it possible to acquire a physiological parameter from which the HRV can be estimated.

The helmet can also include one or more temperature sensors 24, adapted to acquire a temperature. The monitoring and measurement of this variable is necessary in order to detect temperature regulation disorders due, for example, to a disruption of the thermoregulation center which is under the control of the hypothalamus, a structure of the central nervous system located on the ventral side of the brain.

The human body has a relatively constant temperature, around 37°c, within a few degrees. Only in pathological and/or special situations does the temperature exceed its normal value. Thus, an abnormal variation in temperature could indicate an imbalance in the autonomic nervous system, because it is this system that controls the automatic (vegetative) functions of the body, such as temperature regulation, blood pressure, functioning of bladder, sweating, etc. An abnormal variation in temperature could therefore be an indicator of poor homeostasis, that is to say of a poor balance within the body, of dysautonomia. The acquisition of the temperature can for example be used to determine the phase of sleep in which the individual is at a given moment.

The helmet can include one or more batteries for powering the various elements of the helmet, such as the SpO2 acquisition sensor 22, the electrode(s) 21, the processing unit 30 and the transducer 23.

As illustrated by way of non-limiting example in FIG. 3, the processing unit 30 can comprise a processor 31, adapted in particular to ensure the acquisition and processing of signals in an autonomous manner. The processor 31 can have an execution speed suitable for processing the signals acquired in real time. Thus, the helmet allows continuous monitoring of the data acquired, thus improving prevention and the quality of monitoring of the individual.

The processing unit 30 can be configured to communicate with the SpO2 acquisition sensor 22, the at least one acquisition electrode 21, the at least one transducer 23, and the temperature sensor 24 when the latter here is present. Thus, the acquired data is transmitted to the processing unit 30, which can then analyze it.

The processing unit 30 may further comprise storage means 32 suitable for storing data acquired for a time interval greater than one hour, preferably greater than one day, preferably greater than seven days. Thus, the helmet can be worn for long periods of time, and the processing unit 30 can analyze and store in memory data acquired and processed corresponding to these long periods of time.

The processing unit 30 may further comprise an amplifier 34 suitable for amplifying the acquired cerebral electrical signals. Such amplification increases the amplitude level of the signals, which improves the quality of their processing.

The processing unit 30 may further comprise a filter 33, such as a high pass filter and/or a low pass filter. Thus, the acquired signal can be filtered analogically, which improves its quality without causing any loss of information. The signal can then be converted to be processed by the processing unit 30.

The processing unit 30 may further comprise an encryption module 36, adapted to encrypt the acquired data and/or the analyzed data. Thus, the confidentiality of the individual's data is protected.

The processing unit 30 can further comprise a communication module 35 configured to communicate with a mobile device 40. The communication with the mobile device 40 can take place via a wired connection with contact or via a wireless connection, for example a WiFi or Bluetooth connection. Thus, the data acquired and/or analyzed by the processing unit 30 can be transmitted in real time to a mobile device 40. The possibility of communicating via a connection with contact, such as a wired connection, makes it possible to communicate including in the event of unavailability of the Wi-Fi or Bluetooth network, when communication by wireless link is impossible.

The mobile device 40 can for example be a tablet, a smartphone, a computer and/or a smart dock.

The mobile device 40 can include a configuration interface adapted to configure the processing unit 30. For example, an application can be installed on the mobile device 40 to ensure easy and remote configuration of the processing unit 30.

The mobile device 40 can further comprise a communication interface suitable for transferring data via an access network 41. For example, the acquired data can be transferred to an HAS-approved health data host.

The mobile device, in particular the smart dock, can further comprise a charging station for the batteries of the helmet. The smart dock can also acquire data from the headset to feed the algorithms implemented by the processing unit 30.

The processing unit 30, in particular the processor 31, can comprise signal processing means suitable for performing a time and/or frequency analysis of the acquired data. Signal processing can be performed in real time.

Frequency analysis is a mathematical method for studying the oscillations of waves as a function of their frequency, the signal representing the variation of a physical parameter carrying information.

In particular, the signal processing means can be adapted to perform a frequency analysis by wavelets of the acquired SpO2 and/or of the acquired brain wave. A wavelet is a wave-like oscillation that decays rapidly and has a zero average. Unlike sinusoids, which extend to infinity, a wavelet exists for a limited time. Wavelet analysis allows local spectral decomposition in space or time. The two main transformations in wavelet analysis are continuous (CWT) and discrete (DWT) wavelet transformations. The wavelet can be chosen according to the application for which it is used.

Wavelet analysis allows precise analysis of signals not limited in time, which is the case of signals acquired by headphones. Indeed, it is intended to be worn by the individual for several hours in a row, the acquired data therefore have an unlimited duration at the scale of the signal processing.

On the other hand, wavelet analysis gives a time-frequency representation with the precise location of the transitions, that is, it allows to accurately determine the time of abrupt changes in the processed signals, which correspond to sudden variations in the acquired data.

As a variant or in addition, the processing unit 30 can comprise signal processing means suitable for carrying out an analysis of the acquired SpO2 and/or of the brain wave acquired by a Fourier transform method, by a measurement of entropy, by a method of nonlinear analysis of fluctuations, by an autoregressive method, by a straightening of the brain wave by comparison, by a method of differentiation, and/or by any other conceivable method of analysis .

The results of HRV analysis include the following four spectral components:
- High frequencies, between 0.15 and 0.4 Hz, mainly indicative of parasympathetic activity.
- Low frequencies, between 0.04 and 0.15 Hz, mainly indicative of sympathetic activity.
- Very low frequencies, between 0.0033 and 0.04 Hz, mainly indicative of long-term regulation mechanisms.
- Ultra low frequencies, between 0 and 0.0033 Hz.

The processor 31 can, as a variant or in addition, comprise means for analyzing a variability of the heart rate from a plethysmography curve obtained from the acquired SpO2, the analysis of the plethysmography contributing to determining a mechanical wave characteristic adapted to improve the balance of the sympatho-vagal balance.

As a variant or in addition, the processing unit 30 can comprise suitable means for analyzing the data acquired on the basis of learning and prediction algorithms, of the machine learning and deep learning type. Indeed, with the progress of computing, the analysis of EEG signals can go through the machine and deep learning. Artificial intelligence improves the accuracy, robustness and speed of algorithms. Classification with deep learning has proven successful in seizure detection, mental workload, sleep stages, emotion recognition. Among other things, artificial intelligence will make it possible to diagnose, monitor and/or act on epilepsy, cognitive disorders (for example memory difficulties), motor disorders (for example post-traumatic dyskinesia), neurological (for example depression), obstructive respiratory disorders or heart rhythm disorders.

The helmet makes it possible to balance the sympatho-vagal balance by the retrocontrol of the cerebral waves. This feedback is performed by means of the transmission of a mechanical wave by the transducers 23.

The mechanical wave intended to be emitted by the transducers 23 can be an acoustic wave. In particular, the wave can be an electroacoustic wave, which corresponds to the conversion by the transducers 23 of an electrical signal into an acoustic wave. In particular, the wave emitted by the transducers 23 can be a binaural wave. The mechanical wave characteristic may be a frequency. Alternatively, the processing unit 30 could determine one or more mechanical wave characteristics to be transmitted based on the acquired data. For example, the processing unit 30 could determine one or more characteristics of a mechanical wave to be transmitted from among a frequency, an amplitude, a phase, an average value, a shape or any other possible characteristic.

The headset can include two transducers 23, adapted to ensure the diffusion of acoustic waves, in particular waves, in particular binaural waves. Several mechanical waves with different characteristics can be emitted by each transducer 23. For example, the two transducers 23 can each emit a mechanical wave having a characteristic, for example a different frequency.

Listening to binaural waves of given frequencies balances the sympatho-vagal balance by regulating the nervous system, and therefore has many benefits on physical, mental and emotional health, and acts on dysautonomia at the cardiac level, respiratory and vascular.

The use of feedback by the emission of binaural waves makes it possible to stimulate the emission by the brain of cerebral waves such as alpha, beta, gamma, delta, and/or theta waves, which has the effect to modify the brain state of the individual.

The use of binaural sounds is based on the fact that when two signals of close but different frequencies are reported to each of an individual's ears, the brain detects the differences between the frequencies and tries to reconcile them, creating a third signal called binaural sound, which is equal to the difference between the two frequencies.

Thus, when two sound waves of different frequencies are picked up by the brain, it is caused to resonate in harmony with the difference in frequency, which has the effect of inducing the activation of certain cerebral areas. The choice of the frequencies of the mechanical waves emitted therefore makes it possible to simultaneously stimulate various parts of the brain and to synchronize the two hemispheres, which can induce a wide variety of states in an individual (concentration, relaxation, better attentional and memory performance, processing of emotions and reduced anxiety, etc.). Moreover, since the nervous system communicates with all the other systems of the body (hormonal, immune, etc.), the whole body is impacted by this change in the state of the brain.

Binaural sounds:
- between 8 and 13 Hz, induce the production of alpha waves by the brain.
- between 13 Hz and 30 Hz, preferably between 16 Hz and 24 Hz, induce the production of beta waves by the brain.
- higher than 30 Hz, preferably higher than 35 Hz, induce the production of gamma waves by the brain.
- between 0.1 and 4 Hz, preferably between 1 Hz and 4 Hz, induce the production of delta waves by the brain.
- between 4 and 8 Hz, induce the production of theta waves by the brain.

Thus, in the case of a helmet comprising two transducers 23, the frequency of the binaural sounds emitted by each of the transducers 23 can be adapted according to the cerebral waves to be induced in the brain, corresponding to different cerebral states. The nervous system is then regulated and the sympatho-vagal balance balanced thanks to the emission of these binaural sounds.

For example, listening to alpha frequency binaural sounds, i.e. inducing the brain to produce alpha waves, can help reduce stress, through a reduction in cortisol levels, thus inducing a state of relaxation in the individual. Blood pressure is naturally lowered, blood circulation is improved, and the body's healing processes are more efficient to repair and prevent.

Listening to binaural gamma-frequency sounds can help stimulate connections between neurons, and can improve abilities, especially long-term memory.

Listening to delta-frequency binaural sounds can help promote drowsiness to induce deep, restful sleep.

Listening to binaural theta frequency sounds can help improve concentration and creativity, and reduce stress and negative emotions.

Additionally, binaural sounds can help increase the body's production of catecholamines, a hormone strongly associated with better memory, serotonin, DHEA, which reduces the impact of disease and aging, and endorphins.

Binaural sounds can be transmitted directly through the ears. The auditory organ is made up of the outer ear, made up of the auricle and the auditory canal, the middle ear, made up of the ossicles and the eardrum, and the inner ear, made up of the cochlea and the auditory nerve. The sound emitted, corresponding to an oscillation or vibration of the air consisting of sinusoidal alternations of compression and depression, first passes through the outer ear and the middle ear. The ossicles transmit vibrations from the tympanic membrane to the cochlea in the inner ear. The cochlea is connected to the auditory nerve, which transmits sounds to the brain via a pressure action of the wave on a basilar membrane.

Alternatively, the emitted mechanical wave can be transmitted by bone conduction. In particular, sound energy can be delivered to the cochlea by bone conduction of the sound vibration through the bones of the skull. The vibration is then transmitted through the cranial cavity. This transmission involves the three divisions of the ear, either by compression-decompression directly to the cochlea, or by an inertial mechanism through the middle ear. Sound transmitted by bone conduction produces a movement of waves on the basilar membrane similar to that of air-conducting sound.

The transmission of binaural sounds by bone conduction avoids involving the eardrum. Thus, the use of the headphones does not risk damaging the eardrum, and the headphones can be used even by people with a damaged eardrum, or who are not able to hear sounds propagated by the ears. Furthermore, bone conduction allows an individual wearing the helmet to continue to hear the sounds coming from his external surroundings, which makes wearing the helmet less restrictive.

The helmet can comprise a support 50 adapted to be positioned on the head 1 of an individual, the support 50 being configured to ensure the positioning of the SpO2 acquisition sensor 22, of the at least one electrode of acquisition 21, of the at least one transducer 23, and of the temperature sensor 24 when the latter is present. In particular, the support 50 can ensure the placement of one or more acquisition electrodes 21 in one or more places of the individual's skull, the placement of the SpO2 acquisition sensor 22 close to one ear of the individual, and placing the temperature sensor 24 close to another ear of the individual. The support 50 can also ensure the placement of at least one transducer 23 on either side of the individual's head close to an ear.

The support 50, illustrated by way of example in Figures 5 to 8, can comprise a rigid part 51, an elastic part 52 and/or a network 53.

The rigid part 51 of the support 50 can ensure the role of reinforcement of the helmet and installation of one or more electrodes 21 of the helmet. The rigid part 51 can be broken down into two rigid parts each arranged on either side of a median axis of the head 1 of the individual wearing the helmet, the median axis separating the right half and the left half of the head 1 of the individual.

Each rigid part 51, as illustrated by way of example in FIGS. 7, 8 and 10, may have a substantially Y-shape, and be intended to be placed substantially above and in front of the ear of the the individual wearing the helmet, close to it. The rigid part 51 can rest on the ear, which contributes to its positioning on the head 1 of the individual.

Alternatively, as illustrated by way of example in Figure 11, the rigid part 51 can be formed in one piece and rest on the ears of the individual. The rigid part 51 then comprises a front portion, for example in the form of a strip, extending between the two ears close to the forehead of the individual, a rear portion, for example in the form of a strip, extending between the two ears close to the back of the individual's skull, as well as a connecting portion, located between the front and rear portions and substantially matching the shape of the top of the individual's ear, in order to ensure the positioning and maintaining the helmet on the individual's head.

The elastic part 52 of the support 50 can comprise one or more elastic bands that can adapt to the head 1 of an individual. The elastic band or bands can act as a headband to put the helmet in place, while guaranteeing comfort to the individual wearing the helmet. The elastic band or bands can be conductive, for example via printed electronics technology, in order to ensure electrical continuity between the various components of the helmet. For example, the elastic part 52 can comprise two, three or four elastic bands.

In the example illustrated in Figures 7 and 8, a first elastic band connects the first branches of the Ys of the two rigid parts 51, and is placed close to the forehead of the individual. A second elastic band connects the second branches of the Ys of the two rigid parts 51, and is placed substantially at the level of the top of the individual's skull. A third elastic band is placed near the neck of the individual, towards the back of the skull.

In the example illustrated in FIG. 10, the first and second elastic bands connecting the first and second branches of the Ys of the two rigid parts 51 are arranged close to the top of the individual's skull, respectively at the front and at the back of the top of the skull. A third elastic band is placed near the individual's forehead, and a fourth elastic band is placed near the individual's neck.

In the example illustrated in FIG. 11, the elastic part 52 comprises two elastic bands 52, arranged close to the top of the individual's skull, respectively at the front and at the back of the top of the skull. The two elastic bands 52 are arranged between the front and rear portions of the rigid part 51.

As a variant, the elastic part 52 can comprise any other shape or arrangement and number of elastic bands allowing the installation of the support 50 and one or more elements of the helmet on the head 1 of an individual wearing the helmet. The helmet may include a rigid part 51 and not include an elastic part 52. For example, the helmet may include a rigid frame capable of adapting to different shapes of heads 1, or the helmet may have a non-adjustable rigid frame, and be available in several different sizes. As a further variant, the whole of the support 50 can be elastic, in order to best adapt to the morphology of the user's skull.

The network 53 can be adapted to implement different elements of the helmet. Network 53 can extend in contact with the skull, at the level of one or more lobes of the brain. In particular, the network 53 can be arranged so as to cover the skull of the individual, from the top of his forehead to the top of his neck.

The network 53 may comprise several links placed between the rigid 51 and elastic 52 parts of the support 50, the links crossing each other and being able to be connected together at the level of nodes. Links can be rigid or elastic. The acquisition electrodes 21, SpO2 acquisition sensor 22 and transducers 23 can be positioned at the level of the nodes of the network 53, and/or at the level of the rigid 51 and elastic 52 parts of the support 50.

The elastic part 52, the rigid part 51 and the network 53 may have dimensions adapted so that, when the helmet is worn by an individual, the electrodes 21 exert sufficient pressure on the individual's skull to ensure contact with the individual's hair or skin. Furthermore, the helmet can ensure positioning of the electrodes 21 with a tolerance of around 10 cm, preferably around 1 cm.

Preferably, the materials used for the helmet are biocompatible materials.

The helmet may include a central row, one or more inner peripheral rows arranged symmetrically with respect to the median axis, and one or more outer peripheral rows arranged symmetrically with respect to the median axis, outside the inner peripheral rows.

The acquisition electrodes 21 can be arranged on certain rows only or on all the rows, a row possibly comprising one or more acquisition electrodes 21. The acquisition electrodes 21 can be arranged symmetrically with respect to the axis median, at the level of network nodes 53.

The helmet can comprise two processing units 30, located on either side of the central axis, each unit being integrated into a Y-shaped frame.

In a first embodiment, the network 53 comprises four inner peripheral rows and two outer peripheral rows. The inner peripheral rows are arranged symmetrically with respect to the median axis, between the central row and the outer rows. The helmet comprises ten acquisition electrodes 21, two transducers 23, an SpO2 acquisition sensor 22 and a temperature sensor 24. The SpO2 acquisition sensor 22, the temperature sensor 24 and the transducers 23 are located on either side of the median axis at the level of the top of the skull, near the outer peripheral rows.

In a second embodiment, illustrated by way of non-limiting example in FIGS. 5 and 6, the network 53 comprises a central row, two inner peripheral rows, and two outer peripheral rows. The helmet comprises eight acquisition electrodes 21. Each inner peripheral row comprises an electrode 21 placed substantially at the level of the front of the skull, an electrode 21 placed substantially at the level of the top of the skull and an electrode 21 placed substantially at the level of the back of the skull, and each outer peripheral row comprises an electrode 21 placed close to an ear. The helmet also includes two transducers 23, an SpO2 acquisition sensor 22 and a temperature sensor 24. Each transducer 23 is located on either side of the median axis of the head 1, substantially at the level back of the head of an individual wearing the helmet, near the back of the neck. The SpO2 acquisition sensor 22 and the temperature sensor 24 are located on either side of the midline at the top of the skull, near the outer peripheral rows.

As a variant, any other arrangement of the elements of the helmet is possible. In particular, acquisition electrodes 21 can be present in a greater or lesser number, one or more electrodes 21 can be located on the central row, one or more electrodes 21 can be arranged at the level of the rigid 51 or elastic 52 parts, and/or the electrodes 21 may not be arranged symmetrically with respect to the central axis.

A method for improving the balance of an individual's sympatho-vagal balance, illustrated by way of example in Figure 9, comprises the following steps.

In a first step E1, a pulsed oxygen saturation (SpO2) is acquired by an SpO2 acquisition sensor 22, a brain wave is acquired by at least one brain wave acquisition electrode 21 and the temperature is acquired by a temperature acquisition sensor 24. These physiological parameters are representative of a state of the autonomic nervous system.

In a second step E2, a mechanical wave characteristic adapted to improve the balance of the sympathovagal balance is determined by a processing unit 30 from data acquired during the acquisition step.

In a third step E3, a mechanical wave, in particular an acoustic wave, in particular a binaural wave, is emitted by at least one transducer 23, a characteristic of the emitted mechanical wave corresponding to the characteristic determined during the determination step .

The mechanical wave emitted is adapted to retroact on the autonomic nervous system (ANS), so as to modify the brain state of the individual to balance his sympathovagal balance. The modification of the cerebral state can also cause a modification of the cardiac activity tending to reduce the cardio-respiratory risks of the individual.

The step of determining a mechanical wave characteristic suitable for improving the balance of the sympathovagal balance may comprise a step of frequency analysis of the acquired SpO2 and/or of the acquired brain wave. In particular, the analysis can be a wavelet frequency analysis.

The step E2 of determining a mechanical wave characteristic suitable for improving the balance of the sympathovagal balance may comprise a step of analyzing a variability of the heart rate from a plethysmography obtained from SpO2 acquired by SpO2 acquisition sensor in acquisition step E1.

The method may further comprise a step of transmitting data to a mobile device 40.

Other embodiments can be envisaged and a person skilled in the art can easily modify the embodiments or exemplary embodiments set out above or envisage others while remaining within the scope of the invention.

Claims (11)

Helmet intended to be worn by an individual so as to improve the balance of the sympatho-vagal balance of said individual, the helmet being characterized in that it comprises:
- a sensor for acquiring pulsed oxygen saturation (SpO2) (22),
- at least one acquisition electrode (21) of a cerebral wave,
- a processing unit (30) configured to determine, from data acquired by the SpO2 acquisition sensor (22) and by the at least one brain wave acquisition electrode (21), a mechanical wave characteristic adapted to improve the balance of sympatho-vagal balance,
- at least one transducer (23) configured to emit a mechanical wave, a characteristic of the mechanical wave corresponding to the characteristic determined by the processing unit (30). A headset according to claim 1, wherein the transducer (23) is configured to emit a binaural wave, and wherein the binaural mechanical wave characteristic is a frequency. Helmet according to one of claims 1 or 2, further comprising a temperature sensor (24). Helmet according to one of Claims 1 to 3, in which the said at least one acquisition electrode (21) is configured to acquire at least one cerebral wave among an alpha wave, a beta wave, a gamma wave, a theta wave, and a delta wave. Helmet according to one of Claims 1 to 4, comprising ten acquisition electrodes (21) and two transducers (23). Helmet according to one of Claims 1 to 5, further comprising a support (50) adapted to be positioned on an individual's head (1), the support (50) being configured to ensure the maintenance of the acquisition sensor of the SpO2 (22), of the at least one acquisition electrode (21) and of the at least one transducer (23), the support (50) comprising a rigid part (51) and an elastic part (52 ). Helmet according to one of Claims 1 to 6, in which the processing unit (30) comprises storage means (32) suitable for storing data acquired during a time interval greater than one day, preferably greater than seven days. Helmet according to one of Claims 1 to 7, in which the processing unit (30) comprises signal processing means suitable for carrying out a frequency analysis by wavelets of the acquired SpO2 and of the acquired cerebral wave. Headset according to one of Claims 1 to 8, in which the processing unit (30) comprises a communication module (35) configured to communicate with a mobile device (40) via a wireless link. System for improving the balance of the sympatho-vagal balance of an individual, comprising a helmet according to one of Claims 1 to 9 and a mobile device (40) with which the processing unit (30) of the helmet is configured to communicate. System according to claim 10, in which the mobile device (40) comprises a parameterization interface adapted to parameterize the processing unit (30), and in which the mobile device (40) further comprises a communication interface adapted to transfer data via an access network (41).