PerimeterLog — the spec

A client portal for midlife women navigating perimenopause. PerimeterLog captures morning biometric readings via phone camera, tracks triggers and mood across the day, and surfaces weekly pattern reports that connect lifestyle exposures to symptom events. The goal is to give women concrete, exportable evidence of their own symptom cycles — useful for self-management and for conversations with clinicians.

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Decisions locked

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The core loop

1. Morning check-in. User opens the app and completes a 60-second biometric scan using the phone's front camera or rear flash, capturing resting signal proxies (skin flush, heart-rate estimate). She then rates overnight symptoms: hot flashes, night sweats, fatigue, mood, brain fog.
2. Symptom severity rating. She sets a severity slider for each symptom and adds optional free-text notes before closing the check-in.
3. Daytime trigger logging. Throughout the day she logs potential triggers — caffeine, alcohol, stress events, heat exposure, sleep quality, exercise — via quick-tap entries on the dashboard.
4. Mood and energy micro-logs. Brief prompted check-ins (mid-day, evening) capture mood shifts and energy dips in under 30 seconds.
5. Weekly pattern report. Every Sunday the app generates a correlation report linking trigger exposure to symptom severity across the prior seven days, surfacing the strongest associations in plain language.
6. Export for clinical use. Before an appointment, she exports a structured PDF or CSV summary to share with her doctor.

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v1 scope

Daily symptom check-in with camera flash biometric. Uses the device's front camera or rear flash to capture a resting signal reading as part of the morning routine. Lives on the Home screen as the first action of the day.

Trigger logging and mood tracking throughout the day. A persistent quick-log tray lets users tap common triggers or add custom ones at any point. Mood and energy micro-logs are prompted at midday and evening. Lives on the Dashboard and as a persistent bottom-bar shortcut.

Weekly pattern report with trigger correlations. Aggregates seven days of symptom and trigger data into a readable report that ranks which exposures most closely precede symptom spikes. Lives on the Reports screen, delivered every Monday.

Symptom severity slider and free-text notes. Each symptom (hot flashes, night sweats, fatigue, mood shifts, brain fog) has a 1–10 slider and an open text field for context. Lives inside the morning check-in flow and can be edited retroactively on the Log screen.

Export data for doctor conversations. Generates a dated PDF or CSV of all symptom, biometric, and trigger records within a user-selected date range. Lives on the Profile/Settings screen under "My Health Data."

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Deliberately later

• Predictive algorithm flagging high-risk symptom days — needs a minimum of 60–90 days of user data per person to be accurate; shipping it before that baseline exists undermines trust.
• Smart notification system for predicted events — depends on the predictive model; premature notifications without reliable predictions will drive churn.
• Private, encrypted symptom and health data — encryption at rest and in transit should be baseline infrastructure from day one, not a feature; the v2 framing here is adding user-facing privacy controls, audit logs, and HIPAA-alignment documentation for clinical partnerships.

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Data model sketch

• users — id, email, name, date_of_birth, onboarding_complete, created_at
• checkins — id, user_id, checkin_date, biometric_raw_data, checkin_type (morning/midday/evening)
• symptoms — id, checkin_id, symptom_type (hot_flash/night_sweat/fatigue/mood/brain_fog), severity_score (1–10), notes_text
• triggers — id, user_id, logged_at, trigger_type, trigger_label, custom_flag
• mood_logs — id, user_id, logged_at, mood_score, energy_score, free_text
• weekly_reports — id, user_id, week_start_date, generated_at, top_correlations_json, report_pdf_url
• exports — id, user_id, date_range_start, date_range_end, format (pdf/csv), generated_at, download_url

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Screens

• Home / Morning Check-in — biometric scan entry point and daily symptom rating flow
• Dashboard — today's trigger log tray, mood micro-log prompts, and symptom summary at a glance
• Log — scrollable history of all check-ins, editable symptom entries with sliders and notes
• Reports — weekly pattern reports with trigger-symptom correlation charts
• Export — date-range selector and download controls for PDF or CSV
• Profile / Settings — account management, notification preferences, onboarding data

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How to use this document

• Bring it into Mind Palace, where the guided platform and its AI coach pick up from exactly this document and build the product with you step by step.
• Hand it to a developer as the complete v1 brief — scope, data model, and screen list are fully defined.
• Keep it as the single source of truth to prevent scope creep while you build.