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US-12623048-B1 - AI-driven system and methods for personalized virtual medical and spiritual advisor avatars with adaptive therapeutic audio, biometric monitoring, and immersive AR/VR healthcare interfaces

US12623048B1US 12623048 B1US12623048 B1US 12623048B1US-12623048-B1

Abstract

A computer-implemented system personalizes virtual advisors for immersive healthcare by creating virtual medical and spiritual avatars that resemble trusted authority figures using deepfake technology and multimodal deep neural networks. The virtual medical advisor tailors guidance by analyzing unstructured electronic health record data with natural language processing and BERT-based techniques while adapting its communication based on real-time physiological data from sensors like EEG and photoplethysmography. Concurrently, the virtual spiritual advisor offers faith-based counseling by factoring in user-declared spiritual preferences and sacred text analysis weighted for doctrinal considerations. Additional features include gamification with cryptocurrency tokens or NFTs for health activities, blockchain-based audit trails for HIPAA compliance, and federated learning with differential privacy. The system also employs 3D anatomical simulations to visualize pharmacokinetics and uses adaptive audio treatments in augmented reality with techniques like binaural beats and haptic feedback, all optimized through reinforcement learning based on historical interactions.

Inventors

  • Michael P. Tabibian

Assignees

  • Michael P. Tabibian

Dates

Publication Date
20260512
Application Date
20250526

Claims (20)

  1. 1 . A computer-implemented method for administering adaptive therapeutic audio treatment in an augmented reality (AR) healthcare system, comprising: receiving user physiological data via biometric sensors including at least electroencephalography (EEG) and photoplethysmography (PPG); generating personalized therapeutic audio signals comprising Solfeggio frequencies combined with isochronic tones; and rendering said audio signals spatially within an AR environment via bone conduction transducers integrated into AR glasses; monitoring real-time alpha/beta wave ratios and heart rate variability (HRV) during audio delivery; and dynamically adjusting frequency amplitudes, interaural time differences, and rhythmic entrainment patterns based on changes in said physiological data.
  2. 2 . The method of claim 1 , wherein the therapeutic audio signals incorporate binaural beats with carrier frequencies between 200-900 Hz, generating third-party neural entrainment effects via dichotic auditory stimulation.
  3. 3 . The method of claim 1 , further comprising overlaying visual neurofeedback indicators in the AR field-of-view that pulse synchronously with dominant EEG frequency bands.
  4. 4 . The method of claim 1 , wherein the Solfeggio frequencies are dynamically selected from a prioritized queue based on galvanic skin response (GSR) measurements correlated with emotional valence classifications.
  5. 5 . The method of claim 1 , wherein the AR environment contextualizes audio therapy through 3D visualizations of neural oscillatory activity mapped to corresponding treatment frequencies.
  6. 6 . The method of claim 1 , further comprising triggering haptic feedback patterns in wearable devices phase-locked to theta and gamma brainwave synchronization events.
  7. 7 . The method of claim 1 , wherein the isochronic tones are dynamically modulated to maintain a phase relationship with dominant respiratory sinus arrhythmia rhythms.
  8. 8 . The method of claim 1 , further integrating the therapeutic audio with AR-guided mindfulness exercises, wherein spatialized voice prompts adapt cadence inversely proportional to real-time cortisol level estimates.
  9. 9 . The method of claim 1 , wherein the system cross-references a pharmaceutical database to audibly highlight potential interactions between current medications and specific frequency ranges.
  10. 10 . The method of claim 1 , further comprising generating blockchain-anchored treatment logs recording all audio parameter adjustments and associated biometric responses for regulatory compliance.
  11. 11 . The method of claim 1 , wherein the AR glasses implement beamforming techniques to isolate therapeutic audio signals from environmental noise.
  12. 12 . The method of claim 1 , further utilizing a generative adversarial network (GAN) to synthesize personalized binaural compositions based on music preference profiles and stress biomarker patterns.
  13. 13 . The method of claim 1 , wherein the system modulates interaural level differences to create virtual sound source movements synchronized with guided visual focus exercises.
  14. 14 . The method of claim 1 , further implementing differential privacy filters on raw EEG data during federated learning updates to audio personalization models.
  15. 15 . The method of claim 1 , wherein the AR environment renders real-time audiographic representations of autonomic nervous system balance using particle systems responsive to HRV metrics.
  16. 16 . The method of claim 1 , further comprising a gamification system awarding non-fungible tokens (NFTs) for achieving sustained gamma wave coherence during therapeutic sessions.
  17. 17 . The method of claim 1 , wherein the audio signals incorporate stochastic resonance patterns calibrated to enhance signal detection in auditory processing pathways.
  18. 18 . The method of claim 1 , wherein the system implements a closed-loop reinforcement learning architecture optimizing reward signals based on long-term neuroplasticity biomarkers.
  19. 19 . A computer-implemented method for operating a virtual spiritual advisor (VSA) system, comprising: receiving spiritual preference data comprising at least one user-selected spiritual archetype through a graphical user interface; generating a deepfake-animated VSA avatar in real-time using a graphics processing unit (GPU) implementing first-order motion models on reference images stored in non-transitory memory; outputting therapeutic audio frequencies through bone conduction headphones while simultaneously displaying the VSA avatar via a virtual reality headset; processing electroencephalogram (EEG) signals through Butterworth filters to detect alpha/beta wave ratios using a biosignal processing pipeline; modulating the VSA avatar's vocal tract parameters through a Griffin-Lim vocoder based on heart rate variability metrics derived from photoplethysmography (PPG) sensor data; synchronizing haptic feedback patterns in a wearable vest with guided meditation sequences using wireless protocols; and recording interaction timestamps and spiritual intervention types in a blockchain ledger.
  20. 20 . The method of claim 19 , further comprising training a bidirectional encoder representations from transformers (BERT) model on tokenized sacred texts using byte-pair encoding, wherein the deepfake animation utilizes facial landmark detection with facial mesh warping.

Description

The present invention claims priority to Provisional Application 63/786,563 filed Apr. 10, 2025, the content of which is incorporated by reference. BACKGROUND OF THE INVENTION Over the past decade, rapid advancements in artificial intelligence, biometric sensing technologies, and immersive digital interfaces have reshaped the landscape of healthcare delivery and wellness management. Concurrent progress in augmented and virtual reality systems has enabled unprecedented levels of user engagement, allowing for the creation of more personalized and effective health interventions that not only address physical ailments but also consider mental and spiritual well-being. These technological strides have led to a paradigm shift toward integrative care models, where real-time feedback and adaptive interfaces facilitate holistic therapeutic experiences. As the convergence of these fields continues to evolve, there is a growing focus on leveraging digital innovations to deliver comprehensive, data-driven, and individualized support in diverse healthcare environments. SUMMARY OF THE INVENTION A computer-implemented system is provided for personalized, adaptive virtual advisor functionality within immersive healthcare environments. The methods receive user preferences—including designating trusted authority figures—to generate deepfake-animated virtual medical and spiritual advisor avatars via neural network models and first-order motion algorithms. These avatars deliver tailored medical guidance by analyzing unstructured electronic health records with transformer architectures and offer spiritual content by selecting material from sacred text databases using semantic similarity matching. The system monitors real-time user physiological states via multimodal sensors such as electroencephalography, galvanic skin response, and photoplethysmography, processing these inputs with temporal convolutional networks, Butterworth filters, and reinforcement learning modules to dynamically adjust avatar speech, emotional tone, and therapeutic content. Therapeutic audio, rendered using Solfeggio frequencies and isochronic tones through bone conduction transducers, along with synchronized haptic feedback via wireless protocols, further enhances the user experience. Data privacy and personalization are maintained through federated learning frameworks, differential privacy filters, and secure blockchain ledger recording of interaction data. In another aspect, a computer-implemented method for generating and operating a virtual medical advisor (VMA) avatar in a virtual reality (VR) healthcare system comprises receiving user preferences including at least one trusted authority figure for avatar representation; generating a personalized VMA avatar using a multimodal large language model (LLM) to visually and audibly resemble the trusted authority figure; displaying the VMA avatar to a user via a VR headset within an immersive 3D environment; providing, via the VMA avatar, medical information tailored to the user's specific health condition through natural language processing (NLP) of electronic health records (EHRs); monitoring the user's physiological state in real-time via biometric sensors including at least heart rate variability and galvanic skin response; and dynamically adjusting the VMA avatar's speech patterns, emotional tone, and recommended therapeutic content based on changes in the user's physiological state and interaction history. In implementations, the method further comprises one or more of the following: generating therapeutic audio frequencies comprising Solfeggio frequencies between 174 Hz and 963 Hz, synchronized with the VMA avatar's speech output; using deepfake technology with a first-order motion model to animate the VMA avatar's facial expressions based on real-time speech synthesis; implementing a gamification system that awards cryptocurrency tokens for user completion of VMA-prescribed health activities, wherein the cryptocurrency tokens are redeemable for premium VR content or real-world medical services through smart contract verification; analyzing unstructured clinical notes from the EHRs using bidirectional encoder representations from transformers (BERT) architecture; integrating a virtual spiritual advisor (VSA) avatar that provides faith-based counseling complementary to the VMA avatar's medical guidance, wherein the VSA avatar adapts its teachings based on the user's self-identified religious affiliation stored in a spiritual profile database; including biometric sensors such as an EEG headset measuring alpha/beta wave ratios to detect anxiety states, wherein the VMA avatar initiates breathing exercises when alpha wave dominance falls below a predetermined threshold; rendering 3D anatomical models derived from the user's medical imaging data, annotated by the VMA avatar during treatment explanations, wherein the anatomical models visually demonstrate medication mechanisms at cellular resolution using