Sound therapy audio data generation method and electronic equipment thereof

By obtaining the user's heart sound, blood pressure and pulse data, and using the AI audio matching model to generate personalized sound therapy audio, the problem that the existing technology mid-sound therapy audio cannot be dynamically adjusted and accurately adapted is solved, and the scientificity and intelligence of sound therapy intervention is realized.

CN120376060APending Publication Date: 2025-07-25刘明德 +1
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Patent Information

Application Number
CN202510452337.4
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-04-11
Publication Date
2025-07-25

AI Technical Summary

Technical Problem

The existing audio data generation methods for sound therapy cannot dynamically adjust the individual physiological status of the user, and are difficult to accurately adapt, lacking personalization, resulting in fluctuations in the intervention effect.

Method used

By obtaining the user's heart sound data, blood pressure data and pulse data, audio feature extraction is performed, and personalized sound therapy data is generated using the trained AI audio matching model, and the adjustment is made in real time to adapt to changes in the user's physiological state.

Benefits of technology

The scientific and intelligent sound therapy intervention has been realized, the adaptability of personalized sound therapy audio has been improved, the effects of sound therapy dynamically optimized, and the accuracy and user compliance of non-pharmaceutical interventions have been improved.

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Abstract

The embodiment of the invention provides a sound therapy audio data generation method and device, and the method comprises the steps: obtaining the physiological parameters of a current user, and the physiological parameters comprise heart sound data, blood pressure data and pulse data; performing audio feature extraction on the heart sound data, the blood pressure data and the pulse data to obtain corresponding audio feature vectors; and processing the audio feature vector through a trained AI audio matching model, and outputting target sound therapy data. Through real-time detection of the physiological parameters of the user and an AI matching mechanism, personalized sound therapy audios are dynamically output to the user, the scientificity of sound therapy intervention is improved, individual differences can be adapted, and the intelligent attribute of sound therapy intervention is improved.
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