Before the ring, the watch, the AI coach, and the mood-responsive cabin, there was a design question: What if interactive software could sense more than clicks? What if it could receive biometric signals and user context, recognize a changing state, and alter the experience that came next?
A 2015 Intuit patent filing put one ambitious answer to that question on the record. U.S. Patent No. 9,891,792 B1, granted in 2018, is titled Method and system for building and utilizing interactive software system predictive models using biometric data. It names Art Tawanghar as one of eight inventors. The public bibliographic record identifies Intuit Inc. as the assignee.1
That distinction is essential. Inventorship recognizes the people named on the patent. Assignment identifies the owner of the patent rights. It is neither accurate nor necessary to collapse those roles to tell the more interesting story: a biometric, predictive, adaptive-software architecture was described years before adaptive wellness became a mainstream product category.
The public record now contains a growing field of systems that describe pieces of the same design vocabulary: wearable signals, personal baselines, state estimates, tailored sound, wellness guidance, adaptive coaching, cabin comfort, safety prompts, and later measurements or reflection. The evidence supports a careful conclusion of publicly described feature overlap and conceptual alignment. It does not establish that any named company practices a particular claim, copied Art Tawanghar, used the patent, or infringes it.
The part most people miss: the invention was not a dashboard
A dashboard reports. A closed-loop experience responds.
The architecture described in U.S. Patent No. 9,891,792 B1 is more than a request to collect a heart-rate signal and display a chart. At a high level, the claims describe an interactive system that obtains biometric data while the person is using software, correlates those signals with interaction activity and baseline data, generates predictive-model data, and changes the user experience that follows.1
That is a different intellectual move. The signal is not treated as a decorative data point. It becomes part of the decision context for the next screen, sequence, recommendation, support resource, interface density, background, or audio experience. The patent text itself gives examples that include user-interview sequence, wording, interface displays, assistance resources, recommendations, backgrounds, and background audio.1
A dated 2015 concept record adds context, not a shortcut
A public February 13, 2015 document attributed on its face to Art Tawanghar and CTG Social PR, titled HEART+HUB, provides a useful earlier point on the timeline. The document imagines a TurboTax “Heart Hub Center” built around real-time heart-pattern and mood-selection ideas, page-aware emotional context, user-selected moods, optional music or sound effects, and a “perfect filing moment.”2
That document and the later patent are not the same record. The concept document is a dated public design artifact. The patent is a separate legal document with eight named inventors and an Intuit assignment record. Together, they show that the question of using state, context, and responsive experience design was being worked through before the current vocabulary of AI wellness, readiness scores, and adaptive sound became familiar.
The eight-part idea that made the design durable
To understand why the patent remains relevant, separate its architecture into the operational questions an adaptive system has to answer:
- What signal is entering the system? The patent contemplates biometric data, with examples ranging from heart beat and respiration to skin temperature, voice, facial expression, and hardware interaction.1
- What is the person doing when that signal arrives? The design links biometric acquisition to interaction activity at defined times.
- What is the reference point? Baseline data matters because a value detached from personal context is often less meaningful than a change relative to a person’s pattern.
- What model turns data into a usable interpretation? The patent describes predictive-model data rather than mere storage.
- What changes next? The system customizes the interactive experience, not just a scorecard.
- How is the output delivered? The patent’s examples include questions, support resources, visual elements, recommendations, and audio.
- What later signal or reflection enters the record? This is where remeasurement, interaction history, self-report, or outcome review can become informative.
- What gets better over time? A credible answer requires documentation. “Personalized” can mean a simple rule, a baseline comparison, a real-time selection engine, or a genuine longitudinal learning system. Those are not interchangeable claims.
This final distinction is the line between a compelling product story and a credible technical account. Adaptive wellness is not defined by saying “AI.” It is defined by what a system actually receives, models, changes, measures again, and documents.
Where today’s public product record aligns
The table below is deliberately conservative. It reports what company materials publicly describe, then classifies the result as conceptual alignment, partial mapping, or monitoring and response only. It is not a patent claim chart and it does not make a legal finding.
| Company or system | What the public record describes | Evidence-bounded reading |
|---|---|---|
| Soaak Find My Frequency | Wearable and self-report inputs, a personalized sound-frequency session, remeasurement, session ratings, and stated future adjustment.45 | Strongest public conceptual alignment. Company materials describe an explicit measure, analyze, improve, repeat narrative, while technical learning mechanics remain undisclosed. |
| WHOOP | Continuous biometric and behavioral context, personal baselines, coaching, Journal behavior insights, breathwork results, and guidance said to become more personal over time.6 | Strong public conceptual alignment. The user-facing loop is clear; source code, model architecture, and patent-specific correspondence are not public. |
| Endel | Real-time soundscapes responsive to heart rate, motion, light, time, weather, location, and selected sleep information. A 2021 Mercedes-Benz Group Research project was described as a car-experience pilot.7 | Partial public alignment. Input-to-audio adaptation is documented, but a persistent outcome-feedback learning loop is not clearly public and the vehicle record is a pilot. |
| Google and Fitbit | Body Response signals, machine-learning or score-based analysis, individual baselines, mood/context reflection prompts, Daily Readiness, and wellness recommendations.8 | Partial public alignment. Public materials do not show that reflection labels retrain a classifier or that all features are one unified adaptive architecture. |
| Apple | Biometric and behavioral inputs, user-specific typical ranges or rolling comparisons, selected algorithms, readiness and training guidance, and user-entered context.9 | Partial public alignment. Apple publicly describes individual features, not a general feedback-trained predictive model spanning them all. |
| Oura | Personal and rolling baselines, readiness, sleep, stress and resilience estimates, tags, trend views, conversational guidance, and updated recommendations.10 | Partial public alignment. The public record supports personalization and ongoing comparison, but not a complete automatic end-to-end learning architecture. |
| Garmin | Personal baseline establishment, recalibration, intraday updates, Body Battery, sleep coaching, stress estimates, and tailored prompts.11 | Partial public alignment. Public documentation does not establish outcome-based model retraining. |
| Samsung | Wearable data, personal or longer-term trend comparison, Energy Score, Wellness Tips, and sleep coaching.12 | Partial public alignment. A score and tailored guidance are disclosed; learning from response to a tip is not. |
| Kia, Hyundai, and Hyundai Mobis | Multimodal occupant signals, real-time state analysis, Kia R.E.A.D. baseline and pattern language, plus sensory cabin or safety responses.13 | Partial public alignment. Important sources concern concepts, demos, and technology development; explicit outcome-feedback learning is not publicly described. |
| Mercedes-Benz and General Motors | Mercedes-Benz publicly described wearable-informed wellbeing recommendations, while GM describes driver-attention sensing, alerts, and response-dependent safety escalation.1415 | Different levels of alignment. Mercedes-Benz is a partial in-car wellbeing mapping. GM is best read as monitoring and safety response, not publicly documented affective personalization or longitudinal learning. |
Why the distinction between “responsive” and “adaptive” matters
A system can be responsive without learning. It can play calmer audio when a current value crosses a threshold. It can display a break reminder after a driver looks away. It can calculate a readiness score from a rolling window. Each of those functions can be useful.
A more complete adaptive architecture adds context and history. It asks whether the same signal appeared while the user was resting, concentrating, driving, following a breath practice, completing a difficult task, or interacting with an interface. It asks whether the response improved the next experience. It distinguishes a population rule from an individual baseline. And it makes the logic visible enough that a person can understand what the system is doing with their state.
This is why the 2015 patent architecture reads as more than a wearable story. It anticipates a broader shift from static interaction toward state-aware interaction. The output could be a soundscape, a recovery prompt, a more legible screen, a calm cabin setting, a support resource, or a differently paced sequence. The design principle is the same: adapt the experience to the person’s changing context rather than forcing every person through one static flow.
What this means for the next phase of frequency wellness
Frequency wellness has its own version of this question. A static session can be a deliberate and useful experience. But the more ambitious design question is no longer only, “What session should play?” It is, “What context, subjective goal, use history, comfort feedback, and self-observed response should shape the next session?”
The answer should be built with humility. Consumer wellness data can support reflection, personalization, and self-directed routine design. It does not automatically establish clinical effect, diagnose a condition, or replace medical assessment. A platform should also be transparent about what it senses, what it infers, what it changes, how long it retains data, whether a user can correct the record, and where its recommendations end.
That is why the architecture in US 9,891,792 B1 matters to the PEMF conversation. It offers a way to think beyond a static catalogue: signals, context, model, experience, feedback, and informed adjustment. It is a design framework for building more responsive wellness software, not evidence that any consumer platform has demonstrated a medical treatment outcome.
Four questions that reveal whether “adaptive” is real
- What enters the system? Look for named signals, context, and permissions, not a vague promise of AI.
- What is the personal reference point? A meaningful system should explain whether it uses a baseline, rolling history, self-report, or only a population threshold.
- What actually changes? A score alone is not an adapted experience. Does the system alter a recommendation, session, interface, prompt, environment, or support path?
- What does it learn, and how can the user see or control that process? “Personalized” has many meanings. Ask whether the product documents later measurement, user feedback, model updates, privacy controls, and limits.
What the public record establishes
It establishes that Art Tawanghar is one of eight named inventors on a 2015 Intuit patent application that later issued as US 9,891,792 B1. It establishes that Intuit is the listed assignee. It establishes that a dated 2015 Art Tawanghar concept document explored heart-pattern, mood-context, and responsive sound or experience ideas. And it establishes that contemporary companies publicly describe many pieces of an adaptive biometric wellness vocabulary.
It does not establish patent-specific conduct by any other company or correspondence to every claim limitation. The U.S. Patent and Trademark Office explains that infringement analysis primarily compares patent claims with an accused product or process, and that a federal court makes the final decision.3 That is why this article remains at the level the evidence can sustain: precise attribution, documented public features, and a clear architecture for readers to evaluate.
Explore the wider frequency-wellness ecosystem
The resources below are optional consumer tools, not medical devices or substitutes for individualized clinical care. Some links may be affiliate links, which means PEMF Magazine may earn a commission at no additional cost to the reader.
| Resource | Where it fits |
|---|---|
| Frequency Healing App | Explore self-directed frequency-wellness sessions and educational material. |
| iTorus i2 collection | Optional portable coil hardware for users who choose to add a compatible physical modality to a wellness routine. |
| iTorus i5 collection | Optional higher-capacity coil collection for compatible consumer wellness use. |
| Woojer Vest 4 | Optional haptic-audio device for a multisensory listening experience. Use code EPEMF10 at checkout. |
| Metatronic Flower of Life Dual Frequency Imprinter | Optional consumer accessory for readers exploring personal ritual and frequency-wellness contexts. |
Educational and wellness disclaimer: This article is for educational purposes only. It does not provide medical advice, diagnosis, or treatment, and it does not establish that any program, device, score, or adaptive feature will produce a particular result. Do not delay or replace licensed medical care. Consult a qualified healthcare professional for symptoms, medical conditions, pregnancy, implanted electronic devices, medication questions, or any concern about whether PEMF is appropriate for you. Follow the manufacturer’s instructions for every device.
Related articles
- Calmity vs PEMF Healing Platform: Scope, Evidence, and the Free Report
- What is Frequency Therapy?
- Heart-Brain Love Matrix: 5-Phase Neurocardiac, Autonomic & Compassion BioPhi-Harmonic Energetics
References
- U.S. Patent No. 9,891,792 B1, “Method and system for building and utilizing interactive software system predictive models using biometric data,” Google Patents. Filed October 30, 2015; granted February 13, 2018. Bibliographic record lists eight inventors including Art Tawanghar and identifies Intuit Inc. as assignee.
- HEART+HUB, Version 1.0, public Google Drive document. Document face states February 13, 2015 and attributes creation to Art Tawanghar / CTG Social PR.
- U.S. Patent and Trademark Office, “Managing a patent.” USPTO guidance on ownership, assignments, rights, and infringement analysis.
- Soaak, “Soaak + Your Wearable.” Current company product page accessed October 2026.
- Soaak Technologies, “Soaak Launches Find My Frequency,” PR Newswire. Company-provided release dated October 6, 2026.
- WHOOP, “New AI guidance from WHOOP.” See also WHOOP Journal Overview and WHOOP Stress Monitor.
- Endel, “Technology.” See also Endel and Mercedes-Benz Group Research car-experience pilot release, July 19, 2021.
- Google, “How we trained Fitbit’s Body Response feature to detect stress.” June 2, 2023. See also Fitbit Daily Readiness.
- Apple, “watchOS 11 brings powerful health and fitness insights.” June 10, 2024.
- Oura, “Readiness Score.” See also Daytime Stress and Oura Advisor.
- Garmin, “Body Battery.” See also Garmin Sleep Coach.
- Samsung Newsroom, “Samsung Collaborates with the University of Georgia to Define and Measure Energy.” Company material describing Energy Score inputs and interpretation.
- Kia, “Kia prepares for post-autonomous driving era with AI-based real-time emotion recognition technology.” December 19, 2018. See also Hyundai Health + Mobility Cockpit.
- Garmin, “Garmin collaborates with Daimler to bring connected features to Mercedes-Benz vehicles.” January 7, 2019.
- GM News, “How hands-free driving tech is shaping safer driving habits.” December 17, 2024. See also Chevrolet Driver Attention Assist.