The myWaves Project

Alain Destexhe

Gif sur Yvette, June 2020 (updated on 19 March 2023).

A technology conceived by CNRS researchers of the Paris-Saclay Institute of Neuroscience (NeuroPSI)

myWaves is a technology originally conceived by two CNRS researchers of the Paris-Saclay Institute of Neuroscience (NeuroPSI), Alain Destexhe and Luc Foubert. The technnology consists of generating personalized sensory stimuli (typically sounds) from recordings of the physiological activity of subjects (typically brain activity). The main idea is to convert the parameters of the EEG wave (amplitude, rise, decay, etc) to the ADSR (attack, decay, sustain, release) format of synthesizers, where the sound is generated.  This technology was patented by the CNRS in 2017, and numerous applications are being developed.

Brain Waves

It all starts with brain waves… The figure below shows typical brain waves generated in different brain states, as recorded using the electro-encephalogram (EEG) in human subjects. One can see that the more the brain drifts towards deep sleep, the slower the waves. In the deepest phase of sleep (bottom), the brain produces slow waves, also called delta waves.

Even in slow-wave sleep, not all brains produce identical slow waves. The figure below illustrates EEG recordings of different subjects during slow-wave sleep. In the top traces (“same”), the same subject was recorded during 5 different nights. One can see that the different recordings show different slow-wave patterns, but there is a “personalized” pattern in the way those waves are produced. This is apparent when comparing to the bottom traces (“different”), where 6 different subjects were recorded during their slow-wave sleep. One can see that the patterns of the waves are different, but each subject seems to have its own way of producing the delta waves…

Acoustic Stimuli can Affect Brain Activity

It is well known that brain activity can be affected by acoustic stimuli, as shown by examples from the literature displayed below. In particular, it was shown that acoustic stimuli delivered during sleep can affect the sleep slow-waves generated by the brain.

It was also shown that stimuli given when the subject was awake can induce changes in the sleep architecture.

NeuroAcoustic Transduction

Based on these results, we have conceived a way to produce personalized sound (or music) from our brain waves. The figure below illustrates the myWaves concept. We hypothesize that sounds made from sleep brain waves can exert strong relaxing effects and even induce sleep. To test this, we have conceived a procedure which we called Neuro-Acoustic Transduction, and which consists of generating sounds or music based on electro-encephalogram (EEG) recordings of the subject. The sound sequences reflect the temporal organization of the brain waves, and are thus totally specific to the subject.

The NeuroAcoustic Transuction procedure is illustrated below. The delta waves are first detected in the EEG, then they are parametrized. This parametrization is the main originality of the procedure: the parameters of each delta wave (time of occurrence, rise, amplitude, decay, duration, etc) are estimated by a computer algorithm. These parameters are then passed to synthesizers to generate sound envelopes that will reflect the shape of the brain waves (using the ADSR format). A period of sleep, consisting of hundred of delta waves, will therefore be translated into a complex sound sequence, called myWaves. This term was used to reflect the fact that the music sequence will strictly reflect the sequence and structure of the slow-waves of a given subject, and thus will be specific to that subject.

Testing myWaves

Here are two audio examples of myWaves sounds generated by NeuroAcoustic Transduction:

These two myWaves sequences were generated by applying the neuroacoustic transduction method to the the same sequence of delta waves in a normal human subject. The two sequences differ from the use of different samples. Many other “compositions” are possible from the same set of EEG waves, depending on the samples used. This constitutes a very interesting subject to explore.

We have analyzed in more detail the potential of the neuroacoustic transduction technique to generate relaxing myWaves sounds, based on EEG recordings of slow-wave sleep of different subjects. The myWaves sequences were replayed to the subject, and we have discovered that generating a music sequence made of someone’s slow waves can be efficient to induce sleep, and especially if the subject listens to the music from its own brain activity.

The myWaves sleep-induction method was tried on a number of voluntary healthy subjects (n=36), 77% of which reported a general relaxing effect superior to 8/10. Remarkably, a significant fraction of them reported that they could fall asleep: 77% of the subjects reported a sleep induction effect superior to 7/10. We also tested the personalized effect by mixing myWaves sounds generated by the subject’s own brain, with myWaves surrogates (where the individual waves were randomly shuffled). Interestingly, on the 36 subjects, none could fall asleep with the randomized sound sequences (not shown). This testing is still on-going today.

Clinical Testing

We also began to test the sleep induction potential of myWaves with the Clinical Center for Sleep and Vigilance (APHP, Hôtel-Dieu, Paris), on 5 patients suffering from chronic insomnia. There was a positive response from two of these patients (40%), who reported that the myWaves music could really help them falling asleep. We are presently running a clinical study on a more extended sample of patients.

We also discussed applications with another center, Sleep, Addiction and NeuroPsychriatry Institute (CNRS, Bordeaux), on patients suffering psychiatric disorders.


An important aspect is the intellectual property and its protection. The approach of Neuroacoustic Transduction was patented in 2017 (Patent number 17-53609; Date: April 25, 2017; Publication number 3065366; Patent owners: A. Destexhe, L. Foubert and the CNRS). The patent was accepted in France, and was published in 2018. It was submitted at the international level (PCT extension; number WO-2018/197155-A1; Date: November 1, 2018). The patent was published in 2020 in the US Patent Office (patent number: US-2020-0138322-A1; Patent Application Publication date: May 7, 2020; Title “Physio-Sensory Transduction Method and Device”; Owner: CNRS; Inventors: Alain Destexhe and Luc Foubert), and officially accepted in US in December 2022.

Future Applications

The future applications of the myWaves concepts are numerous. A first application, as outlined above, consists in generating personalized myWaves music as a means to help falling asleep. In this case, we record the subject using a portable EEG recording device, then generate the myWaves sound sequences. The music is arranged as a “fade-out” lasting 30 minutes. This is the format we have used for the testing of the myWaves music.

As mentioned earlier, the myWaves concept is not limited to sleep, and not even to sounds. A possible application would be to use the same concept but with the opposite goal of maintaining concentration and vigilance. In this case, we record the faster EEG rhythms that are expressed when the subject is attentive. These oscillations, called Beta waves could also be used to generate sensory stimuli that strictly respect the sequence of the waves recorded in the EEG. This could be sounds, but also visual (light intensity variations for example). This application is still in beta-testing at the moment!

Finally, another application would be to use the myWaves concept to generate musing specifically to help babies falling asleep. This application is currently being examined at the moment as well.

Financial Support

The project obtained financial support from the SATT Paris-Saclay, BPI-France, CNRS-Innovation, as well as from private investors.  A startup company was created recently, myWaves Technologies

We are presently seeking financial support for a clinical study on 50 patients with chronic insomnia and 200 control subjects.


We would like thank all those who helped us at various stages of this project, Luc Foubert, Jean-Francois Destexhe, Kim Whiley, Nicholas Lai, Paul Pham, Philippe Smelty, Jules Meunier, Thomas Ribeiro, Damien Leger, Maxime Elbaz, Jean-Paul Cromière, Guillaume Mezache, and Franck Rodriguez for the many hours spent on the project.

For more information, please contact: Alain Destexhe