EEG Audification System for Personalized Music Therapy
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Solution Overview
Problem
Current treatments for neurological conditions such as epilepsy often have damaging side-effects and are not tailored to individual patients, leading to a need for a highly effective, side-effect-free treatment that can be personalized.
Innovation Solution
A computer system that receives EEG data of healthy brain behavior, audifies it, and analyzes both the audified EEG data and music audio files using a neuro-physiological model to create a personalized playlist of music that can entrain healthy brain behavior and provide treatment for neurological conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If current treatments (medication, vagus nerve stimulation, brain surgery) are used for epilepsy, then neurological conditions can be treated, but damaging side-effects occur
Solution Approach 1:
The patent replaces mechanical and surgical interventions (vagus nerve stimulation, brain surgery) with an acoustic field-based treatment system. The system uses audio tracks analyzed through neuro-physiological modeling to stimulate brain regions non-invasively, substituting physical intrusion with acoustic energy manipulation to achieve therapeutic effects without damaging side-effects
Solution Approach 2:
The system changes the parameters of acoustic stimulation by analyzing multiple audio tracks and selecting those with specific neuro-physiological characteristics (rhythmicity, inharmonicity, turbulence values) that match the patient's individual brain response patterns. This parameter optimization enables effective treatment while avoiding harmful over-stimulation
2Productivity
If current treatments are applied to all patients, then treatment coverage is achieved, but individual personalization is lost
Solution Approach 1:
The system employs feedback mechanisms by recording each patient's EEG data and measuring their specific neuro-physiological response to various audio tracks. This feedback information is used to build a personalized predictive model that guides future audio selections, enabling the system to adapt to individual patient needs while maintaining efficient treatment delivery
Solution Approach 2:
The system performs preliminary analysis of each patient's brain response characteristics through initial EEG recording and audio track testing. This preliminary action creates a personalized neuro-physiological profile that pre-determines the optimal audio track selections for that patient, enabling rapid deployment of personalized treatment without compromising treatment coverage
3Adaptability or versatility
If EEG data analysis and music matching is performed for each patient, then personalized treatment is achieved, but system complexity increases
Solution Approach 1:
The system creates a simplified computational model (predictive model) that copies and represents the complex neuro-physiological relationships between audio characteristics and brain responses. This model serves as a virtual replica of the patient's brain response patterns, enabling personalized treatment selection through computational analysis rather than complex physical measurement systems
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system generates a playlist of music that can effectively entrain healthy brain behavior, providing a personalized treatment for neurological conditions such as epilepsy without damaging side-effects, and can be used for both children and adults, including during sleep.
Implementation Method 1
audifying the EEG data of healthy brain behaviour of the human subject
Implementation Method 2
scaling the upsampled extracted sinusoidal waves with time varying frequency in the range of 5 to 9 octaves
Implementation Method 3
analyse the audified EEG data according to a neuro-physiological model of the principal areas and networks of the human brain involved in processing music, to produce analysis data of the audified EEG data
Implementation Method 4
match the analysis data of the audified EEG data with matched analysis data of the music file audio data, to produce a playlist of matched music audio files corresponding to the matched music file audio data, wherein the matched music audio files are suitable to entrain healthy brain behaviour
Data Source
AI summary
A computer system configured to: (i) receive a file of electroencephalogram (EEG) data comprising EEG data of healthy brain behaviour of a human subject; (ii) audify the EEG data; (iii) analyse the audified EEG data according to a neuro-physiological model of the principal areas and networks of the human brain involved in processing music, to produce analysis data of the audified EEG data; (iv) analyse the music file audio data according to the neuro-physiological model, to produce analysis data of the music file audio data; (v) compare the analysis data of the audified EEG data with the analysis data of the music file audio data, to match the analysis data of the audified EEG data with matched analysis data of the music file audio data, to produce a playlist of matched music audio files corresponding to the matched music file audio data, wherein the matched music audio files are suitable to entrain healthy brain behaviour in the human subject.