Physiology-Driven Music Generation for Real-Time Therapeutic Feedback
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Solution Overview
Problem
Existing methods lack a solution for sensor-controlled algorithmic composition that realizes a directed musical form and clinically effective musical-energetic envelope, failing to create new musical works in real time suitable for intensive care medicine and neurorehabilitation, and often perceiving physiological data as sonification rather than music.
Innovation Solution
A digital system using artificial intelligence generates aesthetically appealing music in real time by combining sensor data from breath and motion sensors with musical rules, creating continuous musical flows with resonance-forming patterns and energetic envelopes tailored to physiological parameters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If existing methods convert physiological parameters into music using simple tone assignment, then the implementation is straightforward, but the result is perceived as sonification of data rather than music
Solution Approach 1:
The patent segments music into hierarchical levels (tones, motifs, phrases, sections) and assigns physiological parameters to different levels. Instead of directly mapping physiology to single tones, the system uses physiology to control selection and combination of pre-composed musical segments, transforming data sonification into structured music composition.
Solution Approach 2:
The patent pre-composes multiple musical phrases and motifs before runtime. During operation, physiological data selectively triggers and combines these pre-prepared segments rather than generating tones in real-time from scratch. This preliminary preparation ensures musical quality while maintaining implementation simplicity.
2Quantity of substance
If complete music tracks are transmitted to patients during exercise, then the patient receives comprehensive audio content, but the system cannot adapt the tempo or selection of tracks in real time based on sensor data
Solution Approach 1:
The patent creates dynamically adaptable music structures where tempo, instrument selection, and phrase combination change in real-time based on physiological sensor data. The system maintains a library of pre-composed segments but assembles them dynamically during playback, allowing continuous adaptation to patient state while preserving musical coherence.
Solution Approach 2:
Instead of transmitting complete fixed music tracks, the patent transmits partial musical segments (phrases, motifs, sections) that can be selectively combined. This partial action approach provides the flexibility to adapt music content in real-time by selecting and combining appropriate segments based on current physiological state.
3Measurement precision
If EEG data are translated into music for brain activity feedback, then brain activity can be measured, but the method is very tiring and lengthy because brain activity is difficult to actively influence
Solution Approach 1:
The patent introduces breathing as an intermediary parameter between brain activity and music generation. Instead of directly using EEG data which requires complex interpretation and has delayed feedback, the system uses breathing patterns (easier to consciously control) as the primary control parameter, with EEG providing supplementary information. This intermediary approach accelerates the feedback loop and reduces therapy time.
4Device complexity
If single tones are assigned to arbitrary physiological value ranges during melody formation, then the composition process is simple, but the result lacks directed musical form and clinical effectiveness
Solution Approach 1:
The patent segments music into hierarchical levels (tones, motifs, phrases, sections) and assigns physiological parameters to different levels. Instead of directly mapping physiology to single tones, the system uses physiology to control selection and combination of pre-composed musical segments, transforming data sonification into structured music composition.
Solution Approach 2:
The patent systematically changes multiple musical parameters (tempo, instrumentation, phrase selection, section structure) based on physiological parameter ranges. Instead of simple tone assignment, the system maps physiological values to comprehensive musical parameter changes, ensuring both musical coherence and clinical effectiveness through structured parameter transformation.
Data Source
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AI summary
The invention relates to a method for outputting an acoustic signal which is made of specially produced acoustic signal sequences, and the acoustic signal is configured on the basis of physiological data. The method has the steps of: continuously detecting selected physiological data of a person, in particular such as the ratio of an inhalation duration to an exhalation duration or hand movements, using at least one sensor; discretizing, quantizing, and categorizing the curve of specified parameters of the physiological data and the trends of all of the parameters over time; assigning the parameter categories obtained in this manner to acoustic signal sequences; and combining and outputting the acoustic signal sequences according to the curve of the categorized parameters of the physiological data with supplementary consideration of at least four formed musical components and an energetic envelope curve in order to form a final acoustic signal, wherein the acoustic signal sequences are combined and output according to specific rules which are derived from the principles of European and/or non-European art music, and the final acoustic signal is formed into an acoustic pattern, the time curve of which is produced only once so as to be new each time. The invention likewise relates to a device for carrying out the method.