# PROV to UTILITY 1 TOILET MOUNTED SYSTEM

Source: https://femstate.me/docs/prov-to-utility-1-toilet-mounted-system.md · Updated: 2026-09-10

---

TOILET-MOUNTED SYSTEM FOR HORMONAL ANALYSIS AND METHOD OF USING SAME

PROPOSED NONPROVISIONAL UTILITY PATENT APPLICATION - WORKING DRAFT

Based only on the uploaded provisional specification and Figures 1-14

ATTORNEY REVIEW NOTE: Priority application number, inventorship, applicant information, formal priority language, and prosecution strategy must be confirmed by patent counsel. This draft reorganizes and claims subject matter disclosed in the uploaded provisional.

# CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims the benefit of U.S. Provisional Patent Application No. [TO BE INSERTED BY COUNSEL], filed April 29, 2026, entitled “TOILET-MOUNTED SYSTEM FOR HORMONAL ANALYSIS AND METHOD OF USING SAME,” the disclosure of which is incorporated herein by reference to the extent permitted by law.

# FIELD OF THE INVENTION

The present disclosure relates to systems and methods for biological sample analysis, hormone measurement, endocrine-state modeling, and personalized wellness guidance. More particularly, the disclosure relates to toilet-mounted or toilet-associated systems capable of selectively capturing a bodily-fluid sample, conditioning and analyzing the sample for one or more hormonal biomarkers, attributing measurement data to a user, and providing the resulting data to an integrated hormonal intelligence system configured to model endocrine state and generate personalized outputs.

# BACKGROUND OF THE INVENTION

Conventional hormone-tracking solutions rely on manual test strips, blood draws, saliva sampling, laboratory testing, or wearable-derived proxy signals such as temperature or heart-rate variability. Such approaches may be intrusive, episodic, manually intensive, or indirect and may be poorly suited for high-frequency longitudinal hormone monitoring in household settings.

Existing AI-driven women’s-health platforms are often directed primarily to fertility or ovulation prediction using sparse or indirect inputs. Such systems may not adequately model endocrine-state changes associated with life-stage transitions, integrate direct hormone measurements with wearable or user-reported data, or provide adaptive closed-loop wellness interventions.

Existing smart-toilet systems may detect physiological parameters such as urine color, temperature, hydration markers, pregnancy-related markers, or stool characteristics. Repeatable hormonal analysis, however, may require controlled sample acquisition, dilution, reagent stabilization, mixing, contamination avoidance, calibration, and longitudinal consistency.

Accordingly, a need exists for an integrated system that can passively obtain valid biological-fluid samples, prepare the samples for hormonal analysis, detect hormonal biomarkers, associate measurements with a user, integrate measurements across time and optionally across multiple sources, model endocrine state, and translate the modeled state into personalized guidance or interventions.

# SUMMARY OF THE INVENTION

In one aspect, an integrated hormonal intelligence system includes a hormone-measurement interface configured to obtain hormone-measurement data from one or more sources and a processing system configured to derive hormone features, model an endocrine state, and generate a personalized output based at least in part on the modeled endocrine state.

In certain embodiments, a hormone-measurement source comprises a toilet-mounted or toilet-associated hormone analysis assembly. The assembly may selectively capture a portion of a urine stream before dilution with toilet water, assess sample quality, route a valid sample toward downstream analysis, and route an invalid sample to an automatic discard path.

In certain embodiments, a sample-preparation module conditions a captured sample by dilution, mixing, temperature regulation, stabilization, reagent activation, enzymatic inhibition, bubble mitigation, foam mitigation, or combinations thereof. A replaceable reagent cartridge may contain hormone-specific reagents and may include moisture-control structures, staged reagent release, and a microfluidic distribution structure.

In certain embodiments, hormone-measurement data is obtained from multiple sources including a toilet-mounted hormone analysis device, portable hormone testing device, user-operated assay system, laboratory-generated hormone report, wearable-integrated biosensor, or user-submitted hormone assay data. Data may be normalized, weighted, or confidence-scored according to source type, sampling frequency, historical consistency, recency, or measured reliability.

In certain embodiments, an endocrine-state modeling engine performs concentration normalization, temporal slope calculation, trend extraction, multi-hormone vectorization, relative-level analysis, rate-of-change analysis, or inter-hormone relationship analysis. Hormone-derived features may be integrated with wearable-derived physiological data, mood or symptom inputs, historical cycle information, longitudinal hormone information, or combinations thereof.

In certain embodiments, the endocrine-state modeling engine employs machine-learning models, temporal-sequence analysis, probabilistic inference, or combinations thereof to generate an inferred endocrine-state representation corresponding to fertility phases, perimenopausal transitions, menopausal states, or other hormonally defined states or transitions.

In certain embodiments, the modeled endocrine state is provided to an intervention-planning module configured to generate personalized wellness guidance, including phase-aligned supplementation guidance, stress or sleep support recommendations, metabolic or skin-health protocols, menopause-specific support plans, dose calculation, timing, frequency, or combinations thereof.

In certain embodiments, user response, adherence, subsequent hormone measurements, or user-reported outcomes are evaluated and supplied to a model-update and optimization engine, thereby forming a closed-loop system.

# BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates a schematic representation of an integrated hormonal intelligence system.

FIG. 2 illustrates a hormone analysis system overview including a toilet-mounted embodiment.

FIG. 3 illustrates selective urine capture, first-void rejection, sample-quality validation, valid-sample routing, and invalid-sample discard.

FIG. 4 illustrates a sample-preparation and reagent-mixing module.

FIG. 5 illustrates a hormone-specific reagent cartridge architecture.

FIG. 6 illustrates a sensor array for hormonal detection.

FIG. 7 illustrates a user-attribution subsystem.

FIG. 8 illustrates an AI endocrine modeling engine.

FIG. 9 illustrates a closed-loop wellness and supplement-dosing system.

FIG. 10 illustrates an exploded reagent-cartridge embodiment.

FIG. 11 illustrates a sample-preparation module embodiment.

FIG. 12 illustrates a sensor-array embodiment.

FIG. 13 illustrates a positioning guide and toilet-mounted sample-acquisition arrangement.

FIG. 14 illustrates a selective urine capture and validation arrangement.

# DETAILED DESCRIPTION OF THE INVENTION

## Integrated System Architecture

An integrated hormonal intelligence system may be configured to capture, process, analyze, and model hormone-related data. In one embodiment, the system includes a toilet and a toilet-mounted hormone analysis assembly positioned within, adjacent to, or about the toilet bowl. The assembly may be coupled to the rim, beneath the seat, to existing seat-bolt hardware, by a clip-on bracket, adhesive mounting pad, magnetic interface, latch-based mechanism, or another suitable attachment mechanism. Alignment features may position an inlet relative to an expected urine-stream location.

## Selective Sample Capture and Contamination Control

During a voiding event, the assembly may intercept and capture a predefined amount of urine or other bodily fluid. A midstream capture channel may collect a defined portion before dilution with toilet water. A first-void rejection structure may divert an initial portion until a predetermined delay, flow condition, or volume threshold is reached. Fecal-exclusion barriers, guard walls, recessed inlet placement, aerosol shields, overhangs, guide surfaces, baffles, ribs, concave guide surfaces, laminarizing ribs, or drip edges may reduce contamination, splashback, turbulence, or backflow.

## Sample Quality Validation

A captured sample may be evaluated by a sample-quality validation module including turbidity sensors, conductivity sensors, color-baseline sensors, or combinations thereof. A valid sample may be routed toward downstream preparation. An invalid sample may be routed to an automatic discard channel.

## Sample Preparation

A validated sample may be conveyed to a sample-preparation module including a sample-isolation chamber, inlet port, flow-rate control features, pre-dilution chamber, diluent reservoir, cartridge-based chamber, or sealed blister. Representative dilution ratios may range from approximately 1:1 to approximately 1:20. Representative mixing times may range from approximately 1 second to approximately 60 seconds. Sample conditioning may occur at ambient temperature or between approximately 15 C and approximately 40 C.

## Microfluidic Mixing and Stabilization

The sample-preparation module may perform dilution, mixing, temperature regulation, stabilization, reagent activation, enzymatic inhibition, bubble mitigation, foam mitigation, or combinations thereof. A microfluidic network may include serpentine channels or other passive or active mixing structures. Reagent exposure may be controlled by staged release, on-demand valve opening, or flow-activated mechanisms.

## Replaceable Reagent Cartridge

A removable or replaceable reagent cartridge may include an outer moisture-resistant housing, desiccant chamber, reagent-storage layer, staged valve assembly, microfluidic distribution plate, and cartridge outlet interface. Reagents may be associated with estrogen metabolites, progesterone metabolites, luteinizing hormone, follicle-stimulating hormone, cortisol, stress-related biomarkers, or combinations thereof. Hormone panels may be configurable based on user profile or life stage.

## Hormone Detection

A prepared sample may be analyzed using optical colorimetric sensing, electrochemical immunosensing, or hybrid sensor arrays. Optical detection may use illumination sources and photodetectors. Electrochemical detection may use working, reference, and counter electrodes. Signal conditioning may include noise filtering, baseline correction, temperature compensation, or normalization across sensing channels.

## Hormone Measurement Output

Processed sensor signals may generate quantitative or semi-quantitative measurements of one or more hormonal biomarkers and may be represented as a multi-hormone vector suitable for downstream endocrine-state modeling. An electronics and communications module may perform signal conditioning, user-attribution processing, and wireless communication.

## Multi-Source Hormone Inputs

The endocrine-state modeling engine may receive hormone-measurement data from toilet-mounted hormone analysis devices, portable hormone testing devices, user-operated assay systems, laboratory-generated hormone reports, wearable-integrated biosensors, user-submitted hormone assay data, or combinations thereof. The system may operate using partial, supplemental, or alternative hormone inputs.

## Source Weighting and Unified Representation

The engine may normalize, weight, or confidence-score data based on source type, sampling frequency, historical consistency, data recency, measured reliability, or combinations thereof. Measurements from different sources may be integrated to generate a unified endocrine-state representation. During periods of reduced data density, the system may extrapolate trends, increase uncertainty estimates, or adjust model parameters.

## Feature Extraction and Multimodal Integration

A hormone-feature extraction module may perform concentration normalization, temporal slope calculation, trend extraction, or multi-hormone vectorization. Extracted features may represent relative hormone levels, rates of change, or inter-hormone relationships. A multimodal integration module may integrate hormone-derived features with heart-rate variability, sleep metrics, mood or symptom inputs, historical cycle information, or longitudinal hormone data.

## Endocrine-State Modeling and Life-Stage Classification

An endocrine-state modeling engine may employ machine-learning models, temporal-sequence analysis, probabilistic inference, or combinations thereof to model hormone dynamics over time and generate inferred endocrine-state representations. A life-stage classification module may identify patterns corresponding to fertility phases, perimenopausal transitions, menopausal states, or combinations thereof. A confidence and uncertainty module may generate confidence scores, uncertainty estimates, or variability bands reflecting data density, signal consistency, or variability across measurement sources.

## Personalized Output and Intervention Planning

A personalized hormone-state output may include an individualized endocrine profile, inferred hormone trends, or forecasted hormone-state trajectories. An intervention-planning module may generate phase-aligned protocols, life-stage adjustments, or dosage scheduling logic. Personalized guidance may include phase-aligned supplementation, stress or sleep support, metabolic or skin-health protocols, and menopause-specific support plans.

## Dosing, Guidance, Feedback, and Adaptation

A supplement-dosing controller may determine dose, timing, and frequency subject to predefined safety constraints and may operate using rule-based logic, adaptive algorithms, or combinations thereof. It may communicate with an automated dispenser or user-guidance interface. User intake, adherence, mood, symptoms, biomarkers, or subsequent hormone measurements may be evaluated. A model-update and optimization engine may refine intervention logic, dosing parameters, or modeling assumptions and may feed updated information back to the endocrine-state modeling engine.

## User Identification and Attribution

A user-identification and attribution module may combine seat-mounted biometric sensors, uroflowmetry signatures, proximity pairing with personal devices, behavioral timing patterns, or AI-based identity inference. An attribution confidence score may be generated. Measurement data may be associated with a user when confidence satisfies a threshold and may be quarantined pending confirmation when confidence does not satisfy the threshold.

# PROPHETIC EXAMPLES

## Example 1 - Household Use

An integrated hormonal intelligence system is installed in a shared household bathroom. A toilet-mounted assembly captures a midstream urine sample after diverting an initial portion of the stream. Quality sensors determine whether the sample satisfies predefined criteria. A valid sample is diluted, mixed with hormone-specific reagents, stabilized, and delivered to a sensor array. Hormone-measurement data is transmitted to an endocrine modeling engine, which integrates historical measurements and user-provided context and generates an inferred endocrine-state representation. Personalized phase-aligned supplement guidance is presented through a user interface. Subsequent measurements and feedback are used to update the modeled state and guidance. In a multi-user environment, attribution signals may associate measurements with the appropriate user, and low-confidence measurements may be quarantined pending confirmation.

## Example 2 - Perimenopause or Menopause Modeling

Longitudinal hormone measurements may exhibit increased variability, irregular temporal patterns, or non-cyclic fluctuations. The endocrine modeling engine may extract temporal features, variability metrics, and inter-hormone relationships and generate an inferred endocrine-state representation associated with a perimenopausal or menopausal transition. Confidence or uncertainty estimates may reflect measurement variability and sampling density. The system may adjust weighting, temporal smoothing, or model assumptions and may generate phase-aligned supplementation frameworks adapted for non-cyclic endocrine patterns.

## Example 3 - Multi-Source Operation

When toilet-mounted hormone data is unavailable or intermittent, the system may receive supplemental data from portable hormone testing devices, user-submitted assays, laboratory reports, or wearable-derived physiological indicators. The system may assign confidence weights according to source type, sampling frequency, historical consistency, and recency; integrate weighted inputs into a unified endocrine-state representation; increase uncertainty when data density decreases; and refine the representation when higher-confidence data becomes available.

# CLAIMS

1. A system for hormonal health monitoring comprising: one or more processors; memory storing instructions executable by the one or more processors; and a hormone-measurement interface configured to receive hormone-measurement data from one or more hormone-measurement sources; wherein the instructions cause the one or more processors to derive one or more hormone features from the hormone-measurement data, generate an inferred endocrine-state representation based at least in part on the one or more hormone features, and generate a personalized output based at least in part on the inferred endocrine-state representation.

2. The system of claim 1, wherein the one or more hormone-measurement sources comprise at least one of a toilet-mounted hormone analysis device, a portable hormone testing device, a user-operated assay system, a laboratory-generated hormone report, a wearable-integrated biosensor, or user-submitted hormone assay data.

3. The system of claim 1, wherein deriving the one or more hormone features comprises at least one of concentration normalization, temporal slope calculation, trend extraction, multi-hormone vectorization, determination of relative hormone levels, determination of rates of change, or determination of inter-hormone relationships.

4. The system of claim 1, further configured to integrate the one or more hormone features with at least one of wearable-derived physiological data, heart-rate variability, sleep metrics, user-reported mood, user-reported symptoms, historical cycle data, or longitudinal hormone data.

5. The system of claim 1, wherein generating the inferred endocrine-state representation comprises applying at least one of a machine-learning model, temporal-sequence analysis, or probabilistic inference.

6. The system of claim 1, wherein the inferred endocrine-state representation corresponds to at least one of a fertility-related phase, a perimenopausal transition, a menopausal state, or another hormonally defined state or transition.

7. The system of claim 1, further configured to generate a confidence score, uncertainty estimate, or variability band associated with the inferred endocrine-state representation.

8. The system of claim 1, wherein the personalized output comprises at least one of phase-aligned supplementation guidance, a stress-support recommendation, a sleep-support recommendation, a metabolic-support protocol, a skin-health protocol, or a menopause-specific support plan.

9. The system of claim 1, further configured to receive outcome or adherence data and update at least one of the inferred endocrine-state representation or the personalized output based on the outcome or adherence data.

10. A toilet-associated biological-sample analysis apparatus comprising: a sample-capture assembly configured to selectively capture a portion of a urine stream before dilution with toilet water; a sample-quality validation module configured to determine whether a captured sample satisfies one or more quality criteria; and a sample-transfer path configured to route a sample satisfying the one or more quality criteria toward a downstream analysis subsystem.

11. The apparatus of claim 10, wherein the sample-capture assembly comprises a first-void rejection structure configured to divert an initial portion of the urine stream and a midstream capture channel configured to capture a subsequent portion.

12. The apparatus of claim 11, wherein the first-void rejection structure permits capture after at least one of a predetermined delay, a flow condition, or a volume threshold.

13. The apparatus of claim 10, wherein the sample-quality validation module comprises at least one of a turbidity sensor, conductivity sensor, or color-baseline sensor.

14. The apparatus of claim 10, further comprising an automatic discard channel configured to receive a sample that does not satisfy the one or more quality criteria.

15. The apparatus of claim 10, further comprising a sample-preparation module configured to perform at least one of dilution, mixing, temperature regulation, stabilization, reagent activation, enzymatic inhibition, bubble mitigation, or foam mitigation.

16. The apparatus of claim 15, wherein the sample-preparation module comprises a microfluidic mixing network and a reagent-activation zone.

17. The apparatus of claim 15, further comprising a replaceable reagent cartridge containing one or more hormone-specific reagents.

18. The apparatus of claim 17, wherein the replaceable reagent cartridge comprises a moisture-resistant housing, desiccant chamber, reagent-storage layer, staged valve assembly, microfluidic distribution plate, and cartridge outlet interface.

19. The apparatus of claim 17, wherein the one or more hormone-specific reagents are associated with at least one of estrogen metabolites, progesterone metabolites, luteinizing hormone, follicle-stimulating hormone, cortisol, or stress-related biomarkers.

20. The apparatus of claim 15, further comprising a hormone-detection subsystem configured to generate quantitative or semi-quantitative hormone-measurement data using at least one of optical detection, electrochemical detection, or a hybrid sensor array.

21. A method of personalized hormonal wellness optimization comprising: receiving hormone-measurement data from one or more hormone-measurement sources; deriving one or more temporal or multi-hormone features from the hormone-measurement data; integrating the one or more features to generate an inferred endocrine-state representation; and generating personalized wellness guidance based at least in part on the inferred endocrine-state representation.

22. The method of claim 21, further comprising assigning a confidence weight to hormone-measurement data based on at least one of source type, sampling frequency, historical consistency, data recency, or measured reliability.

23. The method of claim 21, further comprising integrating hormone-measurement data from a plurality of different sources to generate a unified endocrine-state representation.

24. The method of claim 21, further comprising generating a confidence score or uncertainty estimate associated with the inferred endocrine-state representation.

25. The method of claim 21, wherein the personalized wellness guidance comprises phase-aligned supplementation guidance corresponding to an inferred endocrine state.

26. The method of claim 21, further comprising receiving user feedback, adherence information, subsequent hormone measurements, or combinations thereof and updating the personalized wellness guidance based thereon.

27. A closed-loop hormonal wellness system comprising: an endocrine-state modeling engine configured to generate an inferred endocrine-state representation from longitudinal hormone-measurement data; an intervention-planning module configured to generate a wellness intervention based on the inferred endocrine-state representation; an outcome-evaluation module configured to evaluate at least one of subsequent hormone measurements, biomarker changes, adherence, or user-reported responses; and a model-update engine configured to update at least one of the endocrine-state modeling engine or the intervention-planning module based on an output of the outcome-evaluation module.

28. The system of claim 27, wherein the intervention-planning module determines at least one of supplement dose, timing, or frequency subject to one or more predefined safety constraints.

29. The system of claim 27, further comprising an automated supplement dispenser configured to dispense a supplement according to a determined dosing parameter.

30. The system of claim 27, further comprising a user-guidance interface configured to present a notification, reminder, educational guidance, or wellness recommendation.

31. A user-attribution system for longitudinal hormone monitoring comprising: a plurality of attribution inputs comprising at least two of a seat-mounted biometric signal, uroflowmetry signature, proximity signal from a personal device, behavioral timing pattern, or presence signal; and a processing system configured to generate an identity-confidence value from the plurality of attribution inputs and associate hormone-measurement data with a user profile based at least in part on the identity-confidence value.

32. The system of claim 31, wherein hormone-measurement data is quarantined pending user confirmation when the identity-confidence value does not satisfy a predefined threshold.

33. A replaceable reagent cartridge for hormonal analysis comprising: a moisture-resistant outer housing; a reagent-storage layer containing one or more hormone-specific reagents; a moisture-control component; a valve assembly configured to control release of the one or more hormone-specific reagents; a microfluidic distribution structure configured to meter released reagent; and an outlet interface configured to fluidly couple the cartridge to a sample-analysis subsystem.

34. The cartridge of claim 33, wherein the one or more hormone-specific reagents form a configurable hormone panel selected based at least in part on a user profile or life stage.

35. A method of operating a toilet-associated hormone analysis system comprising: diverting an initial portion of a urine stream; capturing a subsequent portion of the urine stream before dilution with toilet water; determining whether the captured portion satisfies one or more sample-quality criteria; when the captured portion satisfies the criteria, conditioning the captured portion for hormonal analysis and detecting one or more hormonal biomarkers; and when the captured portion does not satisfy the criteria, routing the captured portion to a discard path.

# ABSTRACT

An integrated hormonal intelligence system is provided for capturing, processing, and modeling hormone-related data to generate personalized wellness guidance. The system may receive hormone-measurement data from one or more sources, including toilet-mounted hormone analysis devices, portable hormone testing devices, user-operated assay systems, laboratory-generated hormone reports, wearable-integrated biosensors, or user-submitted assay data. In certain embodiments, a toilet-associated assembly selectively captures and validates a urine sample before dilution with toilet water, conditions the sample, exposes the sample to hormone-specific reagents, and detects hormonal biomarkers using optical, electrochemical, or hybrid sensing. An endocrine-state modeling engine may extract temporal and multi-hormone features, integrate multimodal inputs, generate an inferred endocrine-state representation and associated confidence information, and produce personalized wellness or supplementation guidance. User response, adherence, subsequent hormone measurements, or other outcomes may be used to update the model or intervention logic in a closed-loop framework.

# COUNSEL REVIEW ITEMS

• Insert the exact provisional application number and confirm the April 29, 2026 priority claim.

• Confirm inventorship for each claimed subject-matter group.

• Perform a written-description and new-matter audit against the filed provisional specification and Figures 1-14.

• Decide which independent claim families should remain in one application and which should be reserved for continuation or divisional practice.

• Review software/endocrine-modeling claims for patent-eligibility and technical-detail strategy.

• Review apparatus and cartridge claims against prior art and refine structural limitations without unnecessarily narrowing the commercial scope.

• Confirm formal USPTO drawing compliance and reference-numeral consistency before filing.