solsticestudioai/bio-pulse-pack

1# Bio-Pulse Physiological Telemetry Pack — Schema2 3One row = one physiological event sequence, end-to-end. All records share the same seven top-level fields.4 5Schema version: `1.0.0-bio-pulse-sample`6 7## Top-level fields8 9### `schema_version` — string10Schema identifier. Constant within a sample release. Used to detect pack version drift.11 12### `event` — struct13Identifier fields and the overall clinical outcome for the sequence.14 15| Field | Type | Notes |16|---|---|---|17| `id` | string | Stable episode identifier, e.g., `BIOPULSE-100000`. |18| `trace_id` | string (UUID) | Cross-links telemetry steps within the sequence. |19| `timestamp` | string (ISO-8601) | Episode start time. |20| `criticality` | string | `low`, `medium`, `high`, `life_threatening`. |21| `outcome` | string | `patient_stabilized`, `intervention_successful`, `morbidity_risk_detected`. |22| `confidence` | double | 0–1. Confidence of the outcome label. |23 24### `patient_context` — struct25Synthetic patient archetype and baseline risk factors.26 27| Field | Type | Notes |28|---|---|---|29| `phenotype` | string | One of: `pediatric_asthmatic`, `active_longevity`, `high_stress_corporate`, `sedentary_diabetic`, `geriatric_frailty`. |30| `age_group` | string | `18-30`, `31-50`, `51-70`, `70+`. |31| `existing_conditions` | list<string> | Conditions carried by the synthetic patient (e.g., `asthma`, `type-2-diabetes`). |32 33### `medical_logic` — struct34Clinical scenario driving the sequence and the biomarkers being tracked.35 36| Field | Type | Notes |37|---|---|---|38| `diagnostic_class` | string | `Drug_Interaction_Toxicity`, `Septic_Shock_Cascade`, `Nocturnal_Hypoglycemia`. |39| `causal_chain` | list<string> | Ordered causal event labels (e.g., `MEDICATION_INGESTION_A`, `LIVER_ENZYME_DRIFT_SIMULATED`, `ARRHYTHMIA_DETECTION`). |40| `prediction_window_minutes` | int | Minutes of lead time available before the terminal event. |41| `tracked_biomarkers` | list<string> | Which biomarkers are reported in `vitals_telemetry.vitals` (e.g., `glucose_mgdl`, `heart_rate_bpm`, `qt_interval_ms`). |42 43### `vitals_telemetry` — list<struct>44Ordered sensor readings for the episode. One struct per reading.45 46Reading struct:47 48| Field | Type | Notes |49|---|---|---|50| `timestamp` | string (ISO-8601) | Reading timestamp. |51| `sensor_id` | string | Synthetic sensor serial (e.g., `SENS-6ACEC5`). |52| `sensor_asset` | string | One of: `CGM_Sensor`, `Smart_Watch_V3`, `O2_Ring`, `Neural_Patch_V2`. |53| `event_name` | string | Label for what happened at this reading (matches one item in `medical_logic.causal_chain`). |54| `patient_id` | string | Synthetic patient identifier (e.g., `PAT-D884ED0A`). Not real. |55| `vitals.hr` | int | Heart rate (bpm). |56| `vitals.glucose` | double | Blood glucose (mg/dL). |57| `vitals.spo2` | int | Peripheral oxygen saturation (%). |58| `vitals.temp_c` | double | Body temperature (°C). |59| `vitals.cortisol_ugdl` | double | Cortisol (µg/dL). |60| `vitals.systolic_bp` | int | Systolic blood pressure (mmHg). |61| `vitals.qt_interval_ms` | int | QT interval (ms). |62 63### `detection_logic` — struct64Anomaly-signature metadata describing why this sequence is flagged.65 66| Field | Type | Notes |67|---|---|---|68| `signature` | string | Human-readable signature name (e.g., `Predictive Drug_Interaction_Toxicity for pediatric_asthmatic`). |69| `anomaly_score` | double | 0–1. Higher = more anomalous. |70| `baseline_deviation` | string | Short English description of the deviation pattern. |71 72### `simulation` — struct73Simulation engine provenance.74 75| Field | Type | Notes |76|---|---|---|77| `synthetic` | bool | Always `true`. |78| `model` | string | Simulation engine label (`bio_pulse_sim_v1` in this sample). |79| `fidelity` | string | `Clinical_Grade`. |80| `target_diagnoses` | list<string> | Diagnoses this engine can produce (e.g., `Hypoglycemic_Event`, `Septic_Shock`). |81 82## Distribution of this sample83 84- 10,000 sequences total.85- Criticality: balanced across `low` / `medium` / `high` / `life_threatening` (~2,500 each).86- Diagnostic class: balanced across 3 classes (~3,300 each).87- Phenotype: balanced across 5 archetypes (~2,000 each).88- Age group: skewed toward `70+` (~3,200) to reflect chronic-care monitoring use cases.89- Simulation engine label constant (`bio_pulse_sim_v1`) after sanitization.90 91## Sanitization notes92 93- Internal identifier prefix (`SIMA-V4-BIO-*`) has been normalized to `BIOPULSE-*`.94- Internal engine code name has been normalized to `bio_pulse_sim_v1`.95- Wearable device name previously labeled `Neural_Link_Beta` has been renamed to `Neural_Patch_V2` to avoid collision with an unrelated company trademark.96- No real patient IDs, names, clinic names, device serials, or health records are present. All identifiers are synthetic.97- Dataset is HIPAA-safe by construction: no covered data is present.98 99## Relationship to the full pack100 101The production pack scales to 1M+ sequences with wider phenotype coverage, additional diagnostic classes (atrial fibrillation, asthma exacerbation, hypertensive crisis, post-op recovery, stroke precursors), richer biomarker panels, device-specific fidelity variants, longer causal chains, and FHIR-aligned delivery. See the pack card for commercial access.102