111234 00003USP1 Provisional Application Filed 4 29 26

Docket No.: 111234-00003USP1 1 TOILET-MOUNTED SYSTEM FOR HORMONAL ANALYSIS AND METHOD OF USING SAME FIELD OF THE INVENTION [0001] The present invention relates to system capable of performing a biological sample analysis and is directed to methods of monitoring a women’s health and providing personalized wellness systems. More specifically, the system may include an integrated hormonal intelligence systems for capturing, processing, and modeling hormone-related data. BACKGROUND OF THE INVENTION [0002] Conventional hormone-tracking solutions rely on manual test strips, blood draws, saliva sampling, or wearable-derived proxy signals such as temperature or heart rate variability. These approaches are often intrusive, episodic, or indirect, and are poorly suited for passive, daily hormone monitoring in real-world household settings. As a result, such systems fail to provide high-frequency, longitudinal hormone data necessary to characterize hormonal trends, transitions, or variability across extended periods of time. [0003] Moreover, existing AI-driven women’s health platforms are largely focused on fertility and ovulation prediction, frequently using sparse or indirect inputs and static rule-based models. These platforms generally do not model endocrine state changes associated with perimenopause or menopause, do not integrate direct urinary hormone measurements with wearable data or user-reported symptoms, and do not provide adaptive, closed-loop wellness interventions such as personalized supplementation strategies. [0004] Existing smart toilet systems are capable of detecting limited physiological parameters such as urine color, temperature, hydration markers, pregnancy hormones (e.g., hCG), or stool characteristics. Such systems typically rely on direct urine-to-strip exposure, simple dipstick deployment, optical image capture, or generalized urinalysis techniques. Docket No.: 111234-00003USP1 2 [0005] However, these approaches do not adequately support accurate, repeatable hormonal analysis, particularly for endocrine biomarkers relevant to women’s health, which require controlled dilution, reagent stabilization, precise mixing, contamination avoidance, and longitudinal consistency across repeated measurements. In addition, many existing systems are not designed to reliably isolate valid samples or to operate in environments subject to dilution, splash, or cross-contamination. [0006] Accordingly, there exists a need for an integrated system that passively captures hormonal biomarkers in a household environment, ensures sample validity, accurately attributes hormone data to individual users in multi-user settings, models endocrine state across multiple life stages, and translates such modeling into personalized, adaptive wellness guidance over time. BRIEF DESCRIPTION OF THE DRAWINGS [0007] FIG. 1 is a schematic representation of one example of an Integrated Hormonal Intelligence System. [0008] FIG. 2: Hormone analysis system overview including a toilet-mounted embodiment [0009] FIG. 3: Selective urine capture and contamination-control mechanisms [0010] FIG. 4: Sample preparation and reagent-mixing module [0011] FIG. 5: Hormone-specific cartridge architecture [0012] FIG. 6: Sensor array for hormonal detection [0013] FIG. 7: User attribution subsystem [0014] FIG. 8: AI endocrine modeling engine [0015] FIG. 9: Closed-loop wellness and supplement dosing system [0016] FIG. 10: Hormone-specific cartridge architecture [0017] FIG. 11: Sample Preparation Module Docket No.: 111234-00003USP1 3 [0018] FIG. 12: Sensor array for hormonal detection [0019] FIG. 13: Selective urine capture and contamination-control mechanisms [0020] FIG. 14: Selective urine capture and validation system DETAILED DESCRIPTION OF THE INVENTION [0021] Referring now to FIGS. 1 and 2, an integrated hormonal intelligence system (900) configured to be installed in a household environment is provided. In one embodiment, the integrated hormonal intelligence system may be configured to capture, process, analyze, and model hormone-related data. [0022] The system (900) may include a toilet (902) having a toilet bowl (102/904) and a toilet-mounted hormone analysis assembly (906) configured to be positioned within or about to the toilet bowl (102/904). The toilet-mounted hormone analysis assembly (906) may be coupled to the rim of the toilet (902), under the toilet seat , or be configured to clip on to the toilet (902) by any other suitable mechanism, as shown in FIG. 13. It should be appreciated that other attachment mechanisms are contemplated. [0023] In one embodiment, during a user voiding event, the assembly (906) is configured to intercept and capture a predefined amount of urine or other bodily fluid (104/908). The predefined amount of fluid (104/908) may be captured with a fluid capture assembly (channel 106) (106/910) positioned within the toilet-mounted hormone analysis assembly (906). [0024] In one embodiment, the fluid capture assembly (910) is a toilet-mounted urine capture assembly. The fluid capture assembly (910) may be mounted to the toilet using one or more attachment mechanisms. In some embodiments, the assembly (910) is mounted beneath a toilet seat using existing seat bolt hardware. In other embodiments, the assembly is coupled to the toilet rim using a clip-on bracket, adhesive mounting pad, magnetic interface, or latch-based Docket No.: 111234-00003USP1 4 attachment mechanism. The assembly (910) may include alignment features, such as stops or guides, configured to position the inlet geometry relative to an expected urine stream location. [0025] The urine capture assembly (106/910) may be configured as a mid-stream capture channel and may be positioned relative to the toilet bowl such that a defined portion of the amount of fluid (104/908) may be selectively captured prior to dilution with toilet water. [0026] Referring now to Fig. 3A, a urine capture assembly and contamination-control system (200) is provided for use with or as a part of the hormone analysis assembly (906). In one embodiment, the system (200) is configured to isolate a valid urine sample suitable for hormonal analysis while rejecting contaminated, diluted, or otherwise invalid samples. [0027] For example, when a urine stream (202) is emitted into a toilet bowl (204) during a user voiding event, a pre-void deflector or first-void rejection structure (206) is positioned relative to the urine stream (202) and the toilet bowl (204) to intercept and divert an initial portion of the urine stream. The first-void rejection structure (206) may be generally configured to allow urine to pass into the mid-stream collection channel (208) only after a predetermined delay, flow condition, or volume threshold is reached, thus reducing contamination from urethral debris, residual fluids, or environmental contaminants commonly present in an initial void portion. [0028] Additional contamination control structures may include fecal exclusion barriers, guard walls, or recessed inlet placement to prevent contact between the midstream collection channel (208) and regions of the toilet bowl most likely to be contaminated. Aerosol shields or overhang structures may further reduce airborne contamination during flushing or voiding. [0029] Following diversion of the initial portion of the urine stream (202), a midstream capture channel (208) is positioned to selectively capture a subsequent portion of the urine Docket No.: 111234-00003USP1 5 stream corresponding to a midstream sample. The midstream capture channel (208) is configured to collect urine prior to dilution with toilet water and prior to contact with fecal matter or splashback surfaces. The midstream capture channel (208) may include an inlet geometry positioned within the toilet bowl region having a trough-shaped or funnel-shaped inlet having a curved leading edge configured to intercept the midstream portion of a urine stream. The inlet geometry may further include a splash shield or hood structure positioned above or around the inlet to reduce aerosolization and splashback. [0030] The assembly (906) may further include flow-shaping geometries, splash and aerosol mitigation structures, fecal exclusion structures, and automated rejection of invalid samples. For example, the midstream capture channel (208) may also include one or more flow-shaping geometries, such as guide surfaces, baffles, or ribs, configured to direct urine toward the inlet while reducing turbulence. The flow-shaping geometries may include concave guide surfaces that stabilize the urine stream, laminarizing ribs that narrow stream dispersion, or drip edges configured to prevent backflow toward the toilet bowl. [0031] The isolated urine sample is then analyzed by a sample quality validation module (212), as seen in FIG. 14. The sample quality validation module (212) may include one or more sensors configured to assess sample validity, including but not limited to a turbidity sensor, a conductivity sensor, and a color baseline sensor. Data from the sample quality validation module (212) is used to determine whether the captured urine sample meets one or more predefined quality criteria for hormonal analysis. [0032] If the sample is determined to be valid, the sample is routed along a valid sample path (214) to a sample transfer path to a preparation module (218), as discussed below. The sample Docket No.: 111234-00003USP1 6 transfer path (218) conveys the validated urine sample to downstream sample preparation components for further processing. [0033] If the sample is determined to be invalid, the sample is routed along an invalid sample path (216) to an automatic discard channel (220). The automatic discard channel (220) is configured to safely dispose of invalid samples without introducing contamination into downstream components of the system. [0034] In this manner, the selective urine capture and contamination-control mechanisms illustrated in FIG. 3B enables automated isolation of valid urine samples suitable for hormonal analysis while minimizing contamination, dilution variability, and measurement error in realworld household environments. [0035] One or more quality sensors, including turbidity sensors, conductivity sensors, or colorimetric baseline sensors, may be used to determine sample validity prior to further processing. Once captured and verified for validity, the assembly (906) is configured to dilute the predefined amount of bodily fluid (908) with an amount of water to form a captured fluid sample (908a). [0036] In one embodiment, the volume of the validated captured fluid sample (908a) is between approximately 0.5 milliliters and 10 milliliters, with a preferred operating range between approximately 1 milliliter and 5 milliliters. However, other sample volumes may be used depending on assay configuration, hormone panel selection, or detection modality. [0037] Referring now to Figs. 1, 2, and 4, the validated captured fluid sample (908a) is then conveyed through an internal sample transfer path (108/912) to a sample preparation module (110/914/200) housed within or adjacent to the toilet-mounted hormone analysis assembly (906). In one embodiment, downstream of the inlet , the midstream capture channel Docket No.: 111234-00003USP1 7 (208) may transition into a covered conduit or enclosed channel that conveys the validated urine sample toward an internal sample preparation and reagent-mixing module (200) configured to condition a validated urine sample for hormonal analysis prior to detection by a hormone sensor array. [0038] In one embodiment, the module (200) includes a sample isolation chamber (210) connected to the midstream capture channel (208) via a sample inlet port (304). The sample inlet port (304) may be configured to receive the urine sample after the upstream sample isolation or validation component and may include flow-rate control features to regulate the introduction of the sample into the preparation module (200). [0039] The sample isolation chamber (212) is configured to temporarily contain the captured urine sample and to isolate the sample from external environmental exposure prior to quality assessment. In one embodiment, from the sample inlet port (304), the urine sample is directed into a pre-dilution chamber, or sample isolation chamber (212/306). The pre-dilution chamber (212/306) is configured to normalize sample volume and concentration through controlled release of a diluent released from an onboard reservoir, cartridge-based chamber, or sealed blister. In representative embodiments, the validated fluid sample is diluted at a ratio between approximately 1:1 and 1:20, although other dilution ratios may be employed. [0040] Mixing of the captured fluid sample (908a) and diluent may occur over a period ranging from approximately 1 second to 60 seconds, depending on flow rate, channel geometry, and mixing mechanism. Sample conditioning may further include temperature regulation within a range suitable for hormonal assays, including ambient temperature or regulated temperatures between approximately 15°C and 40°C. Dilution may be performed to normalize concentration variability across samples obtained from different voiding events or users, stabilize assay Docket No.: 111234-00003USP1 8 conditions, or improve measurement accuracy. The values described herein are provided as illustrative examples and do not limit the scope of the invention. [0041] The sample preparation module (914) is configured to condition the captured fluid sample (908a) for hormonal analysis by performing one or more of dilution, mixing, temperature regulation, stabilization, reagent activation, enzymatic inhibition, or bubble foam mitigation, or other preparatory operations suitable for downstream hormone detection to obtain a prepared sample (908b). [0042] The sample preparation module (914) may include microfluidic mixing channels, dilution chambers, temperature regulation elements, bubble and foam mitigation structures, and anti-enzymatic stabilization components. In one embodiment, the pre-diluted sample is conveyed to a microfluidic mixing network (308). The microfluidic mixing network (308) may include one or more serpentine channels or mixing structures configured to promote homogeneous mixing of the urine sample and diluent. Mixing within the microfluidic mixing network (308) may be achieved through passive mixing, active mixing, or combinations thereof. [0043] Following mixing, the sample enters a reagent activation zone (310). The reagent activation zone (310) is configured to introduce one or more hormone-specific reagents into the sample. In some embodiments, reagent activation is achieved through staged reagent release, ondemand valve opening, or flow-activated mechanisms that control the timing and sequence of reagent exposure. [0044] The assembly (906) may further include a removable or replaceable reagent cartridge (112/916) configured to contain one or more hormone-specific reagents. See FIGS. 5 and 10. The replaceable cartridge (916) may include desiccant-protected reagent compartments, staged or sequential reagent release mechanisms, breakable or flow-activated valves, and configurable Docket No.: 111234-00003USP1 9 hormone panels. For example, in one embodiment, once the conditioning process is complete, the prepared sample (908b) is transmitted to the replaceable reagent cartridge (112/916) where it is combined with one or more hormone-specific reagents contained within the replaceable reagent cartridge (112/916). [0045] The reagent cartridge (112/916) may include sealed reagent chambers, valving mechanisms, and moisture-control components. The cartridge (112/916) may be configured to open the chambers or valves to combine the hormone specific reagents contained therein with the prepared sample (908b). In one embodiment, As shown in FIGS. 5 and 10, the cartridge (112/916) includes an outer cartridge housing (402). The outer cartridge housing (402) provides a moisture-resistant shell configured to protect internal cartridge components from environmental exposure. In some embodiments, the outer cartridge housing (402) includes a locking or alignment interface configured to mechanically and fluidly couple the cartridge to a sample preparation module or analysis system. [0046] Within the outer cartridge housing (402) is a desiccant chamber (404). The desiccant chamber (404) is configured to control humidity within the cartridge and to preserve reagent stability over time. In some embodiments, the desiccant chamber (404) reduces moisture exposure to extend shelf life and maintain reagent performance. [0047] The cartridge may further include a reagent storage layer (406). The reagent storage layer (406) contains one or more hormone-specific reagents configured to interact with hormonal biomarkers in a prepared urine sample. In various embodiments, the reagent storage layer (406) may store reagents associated with estrogen metabolites, progesterone metabolites, luteinizing hormone (LH), follicle-stimulating hormone (FSH), cortisol, stress-related biomarkers, or Docket No.: 111234-00003USP1 10 combinations thereof. The reagent storage layer (406) may be configured to support customizable hormone panels based on user profile or life stage. [0048] Reagents stored in the reagent storage layer (406) are selectively released via a staged valve assembly (408). The staged valve assembly (408) may include one or more flow-activated valves, mechanically actuated valves, or pressure-responsive elements configured to control the timing and sequence of reagent release. In some embodiments, the staged valve assembly (408) enables sequential exposure of the prepared sample to different reagents. [0049] Released reagents are conveyed through a microfluidic distribution plate (410). The microfluidic distribution plate (410) includes channelized pathways configured to distribute reagents in a controlled and metered manner to downstream analysis components. In some embodiments, the microfluidic distribution plate (410) enables precise reagent dosing and spatial separation of different reagent streams. [0050] The cartridge includes a cartridge outlet interface (412). The cartridge outlet interface (412) is configured to fluidly couple the cartridge to a sample preparation module or analysis subsystem. In some embodiments, the cartridge outlet interface (412) includes sealing elements or gaskets configured to prevent leakage and ensure reliable transfer of reagents and samples during operation. [0051] Once the prepared sample (908b) is combined with the hormone specific reagents , assembly may also be configured to support detection of one or more hormonal biomarkers from the prepared sample (908b). Hormones detectable by the replaceable reagent cartridge (112/916) may include, but are not limited to, estrogen metabolites, progesterone metabolites, luteinizing hormone, follicle-stimulating hormone, cortisol, and related stress biomarkers. Docket No.: 111234-00003USP1 11 [0052] The sample, after reagent activation, is transferred to a stabilization and conditioning module (312). The stabilization and conditioning module (312) is configured to condition the sample for downstream hormonal detection and may include temperature regulation elements, anti-enzymatic control mechanisms, and bubble or foam mitigation structures to improve assay stability and measurement reliability. [0053] Once stabilized and conditioned, the prepared urine sample is delivered as a prepared sample output (314). The prepared sample output (314) is configured to supply the conditioned sample to a downstream hormone sensor array for detection and analysis of one or more hormonal biomarkers. One example of a sensor array may be seen in FIG. 12. [0054] The prepared sample (908b) may be analyzed using one or more detection modalities, including optical colorimetric sensing, electrochemical immunosensing, or hybrid sensor arrays. Quantitative or semi-quantitative hormone concentration data may be generated and transmitted to a processing unit for further analysis. [0055] For example, following combination with the reagent , the prepared sample (908b) is analyzed by a hormone detection subsystem (918), such as a hormone sensor array (114), which may include optical sensors, electrochemical sensors, or combinations thereof, configured to detect and generate certain signal data corresponding, for example, to concentrations of one or more hormonal biomarkers present in the sample. The signal data generated by the hormone detection subsystem (918) is then transmitted to an electronics and communications module (920) (same as the control and processing unit (116)). [0056] As shown in FIGS. 6 and 11, in one embodiment, a prepared urine sample input (502) is received from an upstream sample preparation module. The prepared urine sample input (502) is directed to a sample distribution manifold (504). The sample distribution manifold (504) is Docket No.: 111234-00003USP1 12 configured to distribute the prepared sample across one or more detection channels and may include flow-equalization structures or channel selection mechanisms to ensure consistent delivery of the sample to downstream detection subsystems. [0057] From the sample distribution manifold (504), the prepared urine sample is delivered to one or more detection subsystems, including an optical detection subsystem (506) and an electrochemical detection subsystem (508). In some embodiments, the system utilizes one detection modality; in other embodiments, multiple detection modalities are used in parallel or sequentially. [0058] The optical detection subsystem (506) is configured to perform optical analysis of the prepared sample and may include one or more illumination sources, such as light-emitting diodes, and one or more photodetectors, such as a photodiode array. The optical detection subsystem (506) may generate colorimetric, absorbance-based, or reflectance-based signals corresponding to hormone-dependent reactions occurring within the sample. [0059] The electrochemical detection subsystem (508) is configured to perform electrochemical analysis of the prepared sample and may include a working electrode, a reference electrode, and a counter electrode. The electrochemical detection subsystem (508) may generate electrical signals based on current, voltage, impedance, or related electrochemical measurements associated with hormone-specific reactions. [0060] Signal outputs from the optical detection subsystem (506) and the electrochemical detection subsystem (508) are provided to a signal conditioning and calibration module (510). The signal conditioning and calibration module (510) is configured to process raw sensor signals and may perform one or more operations including noise filtering, baseline correction, temperature compensation, or normalization across sensing channels. Docket No.: 111234-00003USP1 13 [0061] Processed signals from the signal conditioning and calibration module (510) are used to generate a hormone concentration output (512). The hormone concentration output (512) may include 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. [0062] In one embodiment, the electronics and communications module (116/920) is configured to perform signal conditioning, user attribution processing, and wireless communication with external devices or computing resources. The electronics and communications module (116/920) may be configured to communicate hormone measurement data generated from the signal data to a remote computing system or cloud-based artificial intelligence engine (922). [0063] In one example, the artificial intelligence engine is an AI endocrine engine (118). In this example, the AI endocrine engine (118) is configured to process hormone measurement data, optionally in combination with additional data inputs, to model endocrine state, identify hormonal patterns or transitions, and generate personalized hormone state outputs. The endocrine state modeling engine is configured to receive hormone measurement data from one or more sources. Such sources may include, but are not limited to, toilet-mounted hormone analysis devices, portable hormone testing devices, user-operated assay systems, laboratory-generated hormone reports, wearable-integrated biosensors, or user-submitted hormone assay data captured via an application interface. [0064] The endocrine state modeling engine may normalize, weight, or confidence-score hormone measurement data based on source type, sampling frequency, historical consistency, or Docket No.: 111234-00003USP1 14 measured reliability. Hormone measurements from different sources may be integrated to generate a unified endocrine state representation. [0065] In certain embodiments, the toilet-mounted hormone analysis system provides a primary or preferred hormone data source. However, the system is not limited to toilet-mounted data and may operate using partial, supplemental, or alternative hormone inputs to support endocrine state modeling and personalized wellness guidance. [0066] As shown in FIG. 8, hormone measurement inputs (702) are received by the AI endocrine engine (118) from one or more hormone measurement subsystems, including a hormone sensor array as described with respect to FIG. 6. The hormone measurement inputs (702) may include quantitative or semi-quantitative measurements of multiple hormonal biomarkers obtained over time. [0067] The hormone measurement inputs (702) are provided to a hormone feature extraction module (704). The hormone feature extraction module (704) is configured to derive features from the raw hormone measurement data and may perform one or more operations including concentration normalization, temporal slope calculation, trend extraction, or multi-hormone vectorization. In some embodiments, the extracted features represent relative hormone levels, rates of change, or inter-hormone relationships. [0068] Extracted hormone features are then provided to a multimodal data integration module (706). The multimodal data integration module (706) is configured to integrate hormonederived features with additional data sources, which may include wearable-derived physiological data such as heart rate variability or sleep metrics, user-reported mood or symptom inputs, and historical cycle or longitudinal hormone data. The multimodal data integration Docket No.: 111234-00003USP1 15 module (706) may align, weight, or normalize inputs from different data modalities prior to modeling. [0069] Integrated data outputs from the multimodal data integration module (706) are supplied to an endocrine state modeling engine (708). The endocrine state modeling engine (708) is configured to infer endocrine state using one or more computational models. In various embodiments, the endocrine state modeling engine (708) employs machine learning models, temporal sequence analysis, probabilistic inference techniques, or combinations thereof to model hormone dynamics over time and to generate inferred endocrine state representations. [0070] Outputs from the endocrine state modeling engine (708) are provided to a life-stage classification module (710). The life-stage classification module (710) is configured to classify or characterize endocrine states associated with different life stages or transitions. In some embodiments, the life-stage classification module (710) identifies patterns corresponding to fertility phases, perimenopausal transitions, menopausal states, or combinations thereof based on modeled hormone behavior. [0071] The modeled endocrine state and life-stage classification outputs are further processed by a confidence and uncertainty estimation module (712). The confidence and uncertainty estimation module (712) is configured to generate confidence scores, uncertainty estimates, or variability bands associated with the inferred endocrine state. In some embodiments, the confidence and uncertainty estimation module (712) reflects data density, signal consistency, or variability across measurement sources. [0072] Finally, the system generates a personalized hormone state output (714). The personalized hormone state output (714) may include an individualized endocrine profile, inferred hormone trends, or forecasted hormone state trajectories. The personalized hormone Docket No.: 111234-00003USP1 16 state output (714) is suitable for downstream use in generating personalized wellness guidance, supplementation recommendations, or closed-loop interventions. Hormonal data processed by the endocrine state modeling engine may be used to model hormone trends over time, identify reproductive or endocrine states, classify life-stage transitions including fertility, perimenopause, and menopause, and generate probabilistic hormone state representations. [0073] The personalized hormone state output may then be communicated to a user device (120/924), such as a mobile phone or tablet, via a user application interface. The user device or application interface (120) may present personalized wellness guidance, hormoneinformed insights, or supplement dosing recommendations to the user and may further collect user inputs or feedback for closed-loop system operation. The modeling engine may integrate wearable-derived data, mood and symptom inputs, historical hormone profiles, and demographic context to refine endocrine state inference. [0074] Based on the modeled endocrine state, the system generates personalized wellnessoriented interventions, including phase-aligned supplement dosing guidance, stress or sleep support recommendations, metabolic or skin health protocols, and menopause-specific support plans. For example, referring to Fig. 9, a closed-loop system may be configured to receive a personalized hormone state output (802) from an upstream artificial intelligence endocrine modeling engine, such as the engine described with respect to FIG. 8. The personalized hormone state output (802) may include an individualized endocrine profile, inferred hormone trends, or forecasted hormone state trajectories. [0075] The personalized hormone state output (802) is provided to an intervention planning module (804). The intervention planning module (804) is configured to generate wellnessoriented intervention plans based on the modeled hormone state. In some embodiments, the Docket No.: 111234-00003USP1 17 intervention planning module (804) applies phase-aligned protocols, life-stage adjustments, or dosage scheduling logic corresponding to inferred endocrine phases or transitions. [0076] Outputs from the intervention planning module (804) are supplied to a supplement dosing controller (806). The supplement dosing controller (806) is configured to determine supplement dosing parameters, including dose calculation, timing, and frequency, subject to one or more predefined safety constraints. In some embodiments, the supplement dosing controller (806) operates using rule-based logic, adaptive algorithms, or combinations thereof. [0077] The supplement dosing controller (806) may interface with one or more delivery or guidance subsystems. In some embodiments, the supplement dosing controller (806) communicates with an automated supplement dispenser system (808). The automated supplement dispenser system (808) may include one or more compartments and is configured to dispense supplements in a controlled manner according to the determined dosing parameters. [0078] In addition or alternatively, the supplement dosing controller (806) communicates with a user guidance interface (810). The user guidance interface (810) may present notifications, reminders, or educational guidance to a user via a mobile application, display, or other user-facing interface to support adherence to the wellness plan. [0079] User interaction with the closed-loop system is monitored by a user intake and behavior feedback module (812). The user intake and behavior feedback module (812) may track adherence, supplement intake events, or user-reported information such as mood or symptom logging. [0080] Data collected by the user intake and behavior feedback module (812) is provided to an outcome evaluation module (814). The outcome evaluation module (814) is configured to Docket No.: 111234-00003USP1 18 assess changes in biomarkers, trends in hormone measurements, or user-reported responses over time to evaluate the effectiveness of the wellness interventions. [0081] Outputs from the outcome evaluation module (814) are supplied to a model update and optimization engine (816). The model update and optimization engine (816) is configured to refine intervention logic, dosing parameters, or modeling assumptions based on observed outcomes and feedback. In some embodiments, the model update and optimization engine (816) performs adaptive learning or protocol refinement. [0082] The model update and optimization engine (816) provides feedback to the artificial intelligence endocrine modeling engine, thereby forming a closed-loop system in which hormone modeling, intervention planning, and outcome evaluation are continuously updated based on newly acquired data. [0083] The system may monitor user response, adherence, and subsequent hormone measurements and may feed such information back into the endocrine state modeling engine to refine future recommendations, thereby forming a closed feedback loop. [0084] In some embodiments, the personalized wellness guidance and supplementation frameworks are phase-aligned based on inferred endocrine states, including menstrual cycle phases, transitional perimenopausal patterns, or other hormonally defined phases. [0085] To ensure accurate longitudinal tracking, the system may also include a user identification and attribution module. The module may combine seat-mounted biometric sensors, uroflowmetry signatures, proximity pairing with personal devices, behavioral timing patterns, or AI-based identity inference techniques. This configuration enables hormone data to be attributed to the correct user in multi-resident or shared environments. Docket No.: 111234-00003USP1 19 PROPHETIC EXAMPLE Example 1 - Household Use of an Integrated Hormonal Intelligence System [0086] In one exemplary implementation, an integrated hormonal intelligence system is installed in a shared household bathroom environment and used by multiple users over an extended period of time. [0087] In this example, a toilet-mounted hormone analysis assembly is attached beneath a toilet seat using existing seat bolt hardware. The assembly includes a midstream urine capture channel, sample isolation chamber, in-situ sample preparation module, hormone reagent cartridge, hormone sensor array, and an electronics and communication module. [0088] During a morning voiding event, a first user initiates use of the toilet. An initial portion of the urine stream is diverted by a first-void rejection structure. A subsequent midstream portion of the urine stream is intercepted by the urine capture channel and conveyed into a sample isolation chamber. [0089] The captured urine sample is evaluated using one or more quality sensors. Upon determining that the sample satisfies predefined quality criteria, the system transfers the sample to the sample preparation module. [0090] Within the sample preparation module, the urine sample is diluted and mixed with a diluent released from an onboard reservoir. The diluted sample is exposed to one or more hormone-specific reagents contained within a replaceable reagent cartridge and stabilized prior to analysis. The prepared sample is then delivered to a hormone sensor array, which generates hormone measurement data corresponding to multiple hormonal biomarkers. [0091] The hormone measurement data is processed by the electronics module and transmitted to an artificial intelligence endocrine modeling engine. The endocrine modeling Docket No.: 111234-00003USP1 20 engine extracts hormone features, integrates historical hormone measurements and user-provided context, and generates an inferred endocrine state representation. In this example, the modeled endocrine state is associated with a cycle-related hormonal phase. [0092] The inferred endocrine state is used to generate personalized, wellness-oriented guidance, including phase-aligned supplement dosing recommendations, which are presented to the user via a mobile application interface. The mobile application also allows the user to provide feedback regarding supplement intake and subjective wellness indicators. [0093] Over subsequent days and weeks, the system continues to collect hormone measurements during additional voiding events. The endocrine modeling engine updates the inferred endocrine state based on newly acquired data and user feedback. In this manner, the system operates as a closed-loop platform that adapts wellness guidance over time based on longitudinal hormone trends. [0094] In the same household, a second user subsequently interacts with the toilet-mounted system. The system acquires multimodal attribution signals, including presence detection, uroflowmetry characteristics, and proximity to a personal device, and assigns hormone measurement data to the appropriate user profile with an associated confidence score. In instances where user attribution confidence does not exceed a predefined threshold, hormone measurement data is temporarily quarantined pending user confirmation. [0095] This example illustrates how an integrated hormonal intelligence system may operate in a real-world household environment to passively capture hormonal biomarkers, attribute hormone data to individual users, model endocrine state across time, and generate personalized wellness-oriented guidance using a closed-loop framework. Docket No.: 111234-00003USP1 21 Example 2 - Life-Stage Transition and Perimenopause / Menopause Modeling [0096] In another exemplary implementation, the integrated hormonal intelligence system is used by a user experiencing endocrine changes associated with a life-stage transition, including perimenopause or menopause. [0097] In this example, the user interacts with a toilet-mounted hormone analysis system installed in a household bathroom. Over a period of time, the system passively captures urine samples during multiple voiding events using selective midstream urine capture and in-situ sample preparation, as previously described. Hormone measurement data is generated for a plurality of hormonal biomarkers, including estrogen metabolites, progesterone metabolites, follicle-stimulating hormone (FSH), and stress-related biomarkers. [0098] The hormone measurement data collected over time exhibits increased variability, irregular temporal patterns, and non-cyclic fluctuations relative to hormone profiles associated with regular menstrual cycling. The artificial intelligence endocrine modeling engine processes the hormone measurement data and extracts temporal features, variability metrics, and interhormone relationships indicative of a life-stage transition. [0099] Based on the processed hormone features, the endocrine modeling engine generates an inferred endocrine state representation associated with a perimenopausal or menopausal transition. The system further generates confidence and uncertainty estimates reflecting variability in hormone measurements and sampling density during the transition period. [00100] The inferred endocrine state representation is provided to a life-stage classification module, which characterizes the user’s endocrine state as transitioning between reproductive life stages. The system adjusts weighting of hormone inputs, temporal smoothing parameters, and Docket No.: 111234-00003USP1 22 model assumptions to account for irregular hormone patterns commonly associated with perimenopause or menopause. [00101] Based on the modeled endocrine state, the system generates personalized, wellnessoriented guidance tailored to the inferred life-stage transition. In this example, the guidance includes phase-aligned supplementation frameworks adapted for non-cyclic endocrine patterns, along with educational insights regarding hormone variability and lifestyle considerations. The guidance is presented to the user via a mobile application interface. [00102] Over subsequent weeks or months, the system continues to collect hormone measurement data and user feedback. The artificial intelligence endocrine modeling engine updates the inferred endocrine state representation based on longitudinal hormone trends and outcome feedback. In this manner, the system adaptively refines wellness guidance during the perimenopause or menopause transition using a closed-loop modeling framework. [00103] This example illustrates how the integrated hormonal intelligence system may operate to model endocrine state transitions beyond fertility-focused use cases and to provide adaptive, personalized wellness guidance during perimenopause and menopause based on longitudinal hormone data. Example 3 - Multi-Source Hormone Input Operation with Fallback and Confidence Weighting [00104] In another exemplary implementation, the integrated hormonal intelligence system operates using hormone measurement data obtained from multiple sources, including periods in which data from a toilet-mounted hormone analysis system is unavailable or intermittent. [00105] In this example, a user primarily interacts with a toilet-mounted hormone analysis system installed in a household bathroom, as previously described. During regular use, the Docket No.: 111234-00003USP1 23 system captures urine samples, generates hormone measurement data, and models endocrine state based on longitudinal hormone trends. [00106] At certain times, however, hormone measurement data from the toilet-mounted system is unavailable. [00107] Such periods may occur when the user is traveling, when the toilet-mounted system is temporarily offline, or when urine samples are not captured with sufficient frequency. During these periods, the system receives supplemental hormone measurement data from one or more alternative sources, including portable hormone testing devices, user-submitted hormone assay data, laboratory-generated hormone reports, or wearable-derived physiological indicators. [00108] The artificial intelligence endocrine modeling engine receives hormone measurement inputs from the available sources and assigns confidence weights to each input based on source type, sampling frequency, historical consistency, and data recency. In this example, hormone measurement data obtained from the toilet-mounted system is assigned a higher confidence weight when available, while data obtained from alternative sources is assigned a corresponding confidence weight reflective of its characteristics. [00109] The endocrine modeling engine integrates the weighted hormone measurement inputs to generate a unified endocrine state representation. During periods in which toilet-mounted hormone data is unavailable, the system maintains continuity of endocrine state modeling by extrapolating trends, increasing uncertainty estimates, and adjusting model parameters to account for reduced data density. [00110] Based on the unified endocrine state representation, the system continues to generate personalized, wellness-oriented guidance for the user. In this example, the system adapts the specificity and confidence level of the guidance in response to the availability and reliability of Docket No.: 111234-00003USP1 24 hormone measurement inputs. When higher-confidence hormone data becomes available again, the system updates the endocrine state representation and refines the wellness guidance accordingly. [00111] Over time, the system dynamically transitions between primary and supplemental hormone measurement sources without requiring user intervention. In this manner, the integrated hormonal intelligence system maintains longitudinal endocrine modeling and personalized wellness guidance across variable data availability conditions using a multi-source hormone input architecture. [00112] This example illustrates how the integrated hormonal intelligence system may operate as a flexible, source-agnostic platform capable of incorporating hormone measurement data from multiple sources while preserving continuity, confidence estimation, and closed-loop adaptation. Docket No.: 111234-00003USP1 25 CLAIMS 1. A system for hormonal health monitoring comprising: a. a hormone measurement subsystem configured to obtain hormone measurement data from one or more hormone measurement sources; b. a sample preparation module configured to condition a urine sample for hormonal analysis; c. a reagent cartridge containing one or more hormone-specific reagents; d. a sensor array configured to detect a plurality of hormonal biomarkers; e. a user attribution module configured to associate hormone measurement data with a specific user; f. an artificial intelligence processing engine configured to model endocrine state based on the hormone measurement data; and g. an intervention module configured to generate personalized, wellness-oriented guidance based on the modeled endocrine state, wherein, in at least one embodiment, the hormone measurement subsystem comprises a toiletmounted urine capture device. 2. A method of personalized hormonal wellness optimization comprising: a. obtaining hormone measurement data from one or more hormone measurement sources; b. conditioning a urine sample via dilution and reagent activation for hormonal analysis; c. detecting a plurality of hormonal biomarkers; d. attributing the detected hormonal biomarkers to a specific user; e. modeling endocrine state using artificial intelligence based on the hormone measurement data; and Docket No.: 111234-00003USP1 26 f. generating personalized, wellness-oriented guidance based on the modeled endocrine state. 3. The system of claim 1, wherein the hormone measurement sources include at least one of a toilet-mounted hormone analysis device, a portable hormone testing device, or user-submitted hormone assay data. 4. The system of claim 1, wherein the hormone panels are configurable based on life stage. 5. The system of claim 1, wherein invalid samples are automatically discarded based on one or more quality metrics. 6. The system of claim 1, wherein the artificial intelligence processing engine generates confidence scores or uncertainty bands associated with the modeled endocrine state. 7. The system of claim 1, wherein the intervention module generates supplement dosing guidance that is dynamically adjusted over time. 8. The system of claim 1, wherein the artificial intelligence processing engine detects endocrine state transitions including perimenopause and menopause. 9. The system of claim 1, wherein user identity is inferred using multimodal sensor data. 10. The system of claim 1, wherein the personalized wellness-oriented guidance includes phasealigned supplementation frameworks corresponding to inferred endocrine states. Docket No.: 111234-00003USP1 27 ABSTRACT An integrated hormonal intelligence system is provided for capturing, processing, and modeling hormone-related data to generate personalized wellness guidance. The system is configured to receive hormone measurement data from one or more sources, including toiletmounted hormone analysis devices, portable hormone testing devices, or user-submitted assay data. In certain embodiments, the system captures and prepares urine samples in situ for hormonal analysis, detects multiple endocrine biomarkers, attributes hormone data to specific users, models endocrine state using artificial intelligence, and generates personalized wellness and supplement recommendations in a closed-loop feedback system. The platform supports longitudinal hormone tracking across fertility, perimenopause, and menopause life stages.