Personalized Sonification Model for Health Data
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Solution Overview
Problem
Existing wellness technologies primarily rely on visual perception to convey health information, lacking effective methods to promote healthier lifestyles through auditory cues.
Innovation Solution
The development of personalized sonification models that convert biobehavioral data into musical melodies, allowing users to perceive their health status and behavioral parameters through music.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If visual perception methods are used to convey health information, then information delivery is straightforward, but user engagement and behavioral modification are limited
Solution Approach 1:
The patent replaces visual display mechanisms with auditory sonification mechanisms. Health data is transformed into musical melodies and sounds that users can hear, substituting the traditional visual interface with an audio-based interface that leverages music's emotional and cognitive impact to drive behavioral change.
Solution Approach 2:
The patent changes the sensory modality parameter from visual to auditory. By transforming health metrics into acoustic parameters (pitch, tempo, rhythm, melody), the system creates a fundamentally different user experience that engages emotional processing centers in the brain, thereby improving behavioral modification effectiveness.
2Device complexity
If generic sonification methods are used, then implementation is simpler, but personalization and user connection are reduced
Solution Approach 1:
The system performs preliminary actions by collecting user preference data during an onboarding phase. Users indicate their preferred genres, instruments, and musical characteristics before using the system. This preliminary customization data is stored and used to generate personalized melodies, allowing the system to adapt to individual users without adding complexity during active use.
Solution Approach 2:
The sonification model is dynamic and adapts to each user's preferences. The system generates different musical parameters (instrument selection, tempo range, key signature, melody style) based on stored user preferences, making the implementation adaptable while maintaining a consistent underlying architecture that doesn't significantly increase complexity.
Data Source
AI summary
Systems and methods of generating music that encodes personalized information implement and/or include generating a personalized sonification model based on music modeling data pertaining to a user; receiving physiological data pertaining to the user, wherein the physiological data is related to at least one of a physical wellness or a behavioral wellness of the user; generating a melody, wherein the melody encodes a wellness information or modification based on the personalized sonification model and the physiological data; and providing the melody to the user to convey the wellness information or modification.


