Wearables, fitness & longevity

Importing wearable data

Import a wearable export file into Ojava through the Ingestion page. Supported sources include Apple Health XML exports, and CSV exports from Oura, Fitbit, Garmin, Whoop, Withings, Samsung, Polar, connected fitness apps, smart scales, CGMs, sleep apps, HRV apps, hydration sensors, and similar vendors. Ojava auto-detects the file type, normalizes the data into your private metrics, and deduplicates re-imports so importing the same file twice never double-counts your readings. Ojava maps the full General-Wellness range Apple Health and other wearables record, including heart rate and HRV, readiness, recovery, sleep scores and sleep stages, steps and activity, heart-zone minutes, training load, respiratory rate and blood oxygen, body composition (weight, body fat, lean mass, visceral fat, BMI, metabolic age), blood pressure, skin temperature, room or bed temperature when a sleep source provides it, snoring minutes, time in daylight, environmental sound exposure, headphone audio exposure, sweat and electrolyte exports, mobility, source-provided running and cycling power, source scores such as Body Battery or Strain, and mindfulness minutes.

The source catalog now covers 175+ device and app sources across rings, watches, straps, CGMs, smart scales, blood-pressure devices, sleep systems, HRV and recovery apps, connected fitness, nutrition logs, hydration sensors, body-temperature sensors, and bridge apps. A source appears only when it has a truthful read-only lane: file import today, Apple Health or Health Connect in the native apps, or cloud sync through the aggregator roadmap.

The connected-fitness catalog includes the MyFitnessPal-adjacent app set too: Polar Flow, TrainingPeaks, MapMyFitness, MapMyRun, MapMyWalk, MapMyRide, Renpho Health, Strava, Garmin, Fitbit, Withings, Dexcom, Apple Health, Google Fit, and Health Connect. Ojava keeps these as setup and import paths, not writeback or live account-control claims.

For public device-specific prep pages, open the Wearables hub. Each page explains what a device can contribute, what Ojava can organize from exports or accepted rows, and which live sync claims remain gated.

When you ask Coach how to connect a source, Ojava turns that catalog into a setup-readiness answer: already imported, file import ready today, native health-hub path still gated, cloud or partner path still gated, or unsupported and requestable. This is import guidance only. Ojava does not open vendor OAuth, store external credentials, write data back to source apps, control devices, monitor in real time, or send alerts.

Settings health-data packages also include wearable lifecycle evidence when native health or connected wearable rows have been ingested. The package summarizes connection status, sync freshness, ingest status, payload type, and staged row counts with package-local references, while omitting connection IDs, external event IDs, raw errors, device identifiers, credentials, tokens, and raw wearable values. This is portability provenance only, not live sync activation, source accuracy proof, device control, real-time monitoring, alerts, diagnosis, prescribing, or care decisions.

The normalization process handles the different column names and formats each device uses, extracting your actual measurements and storing them in a unified table keyed by measurement type, date, and source. This means all your data (no matter the original device) is comparable on your dashboard, and you can switch wearables without losing history. Composite vendor scores are stored only as scores, never as raw physiology, so a proprietary recovery or sleep score does not get mistaken for a heart-rate, oxygen, or temperature reading.

Body composition summaries

If your smart scale, Apple Health, Health Connect, or file export includes body-composition rows, Ojava summarizes source-provided weight, BMI, body fat, lean mass, muscle mass, body water, visceral fat, fat mass, bone mass, metabolic age, and basal metabolic rate when those readings are present. Ojava normalizes obvious unit differences, compares only with your own recent logged readings, and leaves missing signals blank instead of guessing. This is personal trend context only. Ojava does not diagnose body-composition status, prescribe weight-loss treatment, set medical targets, or replace clinical body-composition testing. When you ask Ojava Coach about body composition, the same source-provided rows can join accepted body measurements, BMI, body-fat range context, body-shape indices, weight trend, and missing inputs in one bounded readiness packet.

Hydration and sweat summaries

If your wearable, workout app, hydration sensor, or Apple Health / Health Connect export includes source-provided fluid intake, fluid loss, sweat rate, sodium loss, sodium concentration, or electrolyte-loss rows, Ojava summarizes those readings in the same readiness card. This covers export paths from sources such as Garmin, Nix Hydration, FLOWBIO, and similar training or recovery tools when the data is present. Ojava normalizes common volume, rate, and sodium units, compares only with your own recent logged readings, and leaves the section blank when the source does not provide those signals.

These readings are training and recovery context only. Ojava does not detect dehydration, prescribe electrolyte or fluid replacement, set medical fluid targets, send alerts, or monitor emergencies.

When a source provides explicit adaptive mobility rows such as wheelchair pushes, wheelchair distance, seated-workout, chair-workout, or adaptive-workout context, Ojava can use those rows as source context for adaptive movement and nutrition prep. It does not infer disability from low activity, reverse-engineer a device formula, prescribe exercise, or clear activity.

Running and cycling power

If your Apple Health, Health Connect, cycling app, power meter, or training-platform export includes running power, cycling power, or cycling FTP, Ojava summarizes the latest watts next to your other readiness context. The summary compares each source-provided power signal with your own recent logged readings, keeps FTP separate from session power, and leaves the section blank when those rows are not present.

Power rows are training context only. Ojava does not set pacing, predict race performance, clear workouts, or replace your coach, training platform, or clinician.

Heart-rate training zones

Ojava works out your personal five training zones (recovery, aerobic base, tempo, threshold, and VO2 max) the same way most training watches do. It estimates your maximum heart rate from your age using a well-established formula, and when your wearable has shared a resting heart rate it uses the heart-rate-reserve method so the ranges fit your own fitness rather than a generic chart. If your export includes heart-rate readings, Ojava can also show roughly where your recent efforts have been sitting, a simple reminder that easy aerobic-base time is where endurance is built.

These zones are a general-wellness training reference built from your own data. They are not a clinical target, a claim that any heart rate is safe for you, a real-time alert, or a way to detect an irregular heartbeat. For anything that feels off with your heart, talk to your clinician.

Strength volume progression

If you log strength sets, Ojava adds up your weekly training volume (sets times reps times weight) and compares your most recent week with your recent average, so you can see whether your lifting is trending up, holding steady, or running lighter, which often lines up with a deload or a busier week. Ojava Coach can reference this trend when you ask about your progress.

This is encouragement and context from your own logged sets, not a prescribed program, a load or volume target, a deload instruction, an overtraining diagnosis, or exercise clearance.

Blood-pressure summaries

If your export includes paired systolic and diastolic readings from a connected cuff or health app, Ojava summarizes the latest pair and compares it with your own recent logged average. This is source-provided trend context for visit prep and personal recordkeeping. Ojava does not assign blood-pressure categories, send alerts, monitor you for a condition, or recommend treatment changes.

Glucose summaries

If your Apple Health, Health Connect, CGM, or glucose-app export includes blood-glucose readings, Ojava summarizes the latest value, the latest-day average, and your recent logged range. It can also say whether those imported rows and timestamped meals are ready for metabolic pattern review, or which source input is still missing. It is source-provided context for food, activity, sleep, visit prep, and Ojava Coach scaffold readiness after accepted review. Ojava Coach also fetches blood-glucose rows through a dedicated source query so high-frequency recovery, heart-rate, or sleep rows cannot crowd glucose rows out of a CGM source-path answer. Ojava also keeps glucose source governance separate from interpretation: a CGM or glucose export needs source provenance, user confirmation, food, activity, sleep, medication context, and clinician-review status before it is source-ready, while alert policies stay forced disabled. Ojava does not connect directly to glucose devices, score glucose control, send glucose alerts, manage diabetes, recommend insulin or medication changes, provide medical nutrition therapy, detect emergencies, or escalate care.

If you ask whether a home glucose log is ready to review, Coach can also count source glucose reading days, morning and later-day timestamp coverage, meter or app source labels, missing clinician-provided schedule or personal range context, and review questions. The packet cites ADA, CDC, NIDDK, and FDA source material but still does not diagnose diabetes or prediabetes, grade glucose control, define personal ranges, watch for emergencies, or decide care.

Oxygen and breathing summaries

If your wearable or health-app export includes blood-oxygen or respiratory-rate readings, Ojava summarizes the latest source-provided values and compares them with your own recent logged averages. This is sleep and recovery context only. Ojava does not screen for breathing conditions, detect sleep-breathing events, send alerts, monitor emergencies, or recommend treatment.

Arterial stiffness and source cardiovascular age

If a source exports pulse wave velocity, PWV, cardiovascular age, vascular age, or arterial age, Ojava can summarize the latest logged value and compare it with your own recent logged average. The sources stay visible beside the readiness card: pulse-wave-velocity reference values and a large individual-participant meta-analysis support context about arterial stiffness, but Ojava does not turn those rows into ASCVD, PREVENT, MESA, plaque, event-risk, diagnosis, monitoring, alerting, treatment, or care-decision output.

Sweat and electrolyte summaries

If a sweat sensor, hydration sensor, or workout export includes fluid-loss, sweat-rate, sodium, or electrolyte-loss rows, Ojava summarizes the latest source-provided readings and compares them with your own recent logged values. This is training and recovery context only. Logged water intake remains handled by the separate hydration score, and Ojava does not use these rows to detect dehydration, set fluid or electrolyte targets, send alerts, or recommend treatment.

Source-provided scores

Some devices export their own proprietary scores, such as Body Battery, Training Readiness, recovery, readiness, sleep, Strain, stress, energy, or Movement Index. Ojava now summarizes those in the readiness card when they are present, but keeps them separate from Ojava’s own calculations. They are source-provided context only: Ojava does not reverse-engineer the vendor formula, treat a vendor score as raw physiology, or use it as a clinical score.

When a source provides Strain plus recovery, readiness, or training-readiness scores on the same recent days, Ojava Coach can compare the pattern before answering training questions. It may say strain is running ahead of recovery, roughly matched, or leaving capacity, but it stays inside source-score context. Ojava does not clear workouts, prescribe training, or infer the vendor formula.

If a source exports recovery time in hours, Ojava summarizes the latest value and recent average as planning context for training and rest. It does not calculate the vendor formula, clear a workout, send an alert, or turn that row into clinical advice.

Daily readiness & recovery

Ojava calculates a daily readiness and recovery score based on your heart rate variability (HRV), resting heart rate, sleep duration and quality, and respiratory rate. The score is shown against your own baseline so you can see your typical range, and Ojava surfaces the contributors that drove today’s score. High readiness suggests you’re recovered and ready to train hard; lower scores suggest easy training or rest might serve you better. This is wellness guidance, not a clinical assessment.

When Ojava shows its own readiness score, it also links the research sources behind the HRV, adult sleep-duration, and consumer-wearable trend context. When you ask Coach about the evidence or sources behind a wearable score, it receives the same source links with the finished score so it can cite the deterministic value instead of re-deriving or inventing a recovery calculation.

If you also log cycle, symptom, mood, and stress rows, Ojava Coach can place recent readiness, sleep, HRV, symptoms, energy, and stress beside your logged cycle or hormone-context window. It describes whether the pattern looks easier, strained, or mixed in your own data. It does not predict fertility, diagnose hormone conditions, give pregnancy or contraception guidance, recommend hormone therapy, clear training, or monitor you clinically.

Ojava Coach also receives a deterministic recovery habit ranking when enough context is present. It ranks one to three general-wellness actions such as protecting sleep opportunity, choosing easy training, hydrating steadily, keeping a light walk, or logging mood and stress. The ranking cites finished readiness, sleep debt, training load, HRV, mood and stress, hydration, and goal values from the shared wearable summary instead of recalculating them, and names missing inputs when the context is thin. It is not a clinical alert, workout clearance, diagnosis, medical advice, or a rigid plan.

Stress resilience context is medium-term recovery framing over those same finished values. Ojava combines recent stress and energy check-ins, source stress or energy rows, readiness, HRV, sleep debt, and training load into a bounded packet that says whether recovery support looks limited, adequate, solid, strong, or exceptional. It is not a copied wearable formula, device score, clinical monitor, diagnosis, treatment plan, or workout clearance.

Recovery signal consistency is the source-review layer before Coach or Reports summarize those same facts. It compares readiness, HRV, sleep debt, training load, resting-heart-rate recovery, temperature, strain-recovery balance, and stress-energy context so mixed signals are named together instead of collapsed into one confident headline. It does not diagnose, monitor in real time, send alerts, clear activity, prescribe recovery, or decide care.

Fitness age (VO2max-based)

Ojava estimates your fitness age from your VO2max (aerobic capacity), either provided by your wearable or derived from your training data. This is how old someone of your fitness level typically is, giving you a longevity-focused view independent of your actual age. Improving VO2max is one of the strongest drivers of healthspan and longevity, so tracking fitness age over time as it trends younger (or maintains) reflects real improvements in cardiovascular fitness.

The fitness-age line carries cardiorespiratory-fitness and estimated-fitness source links beside the result. It is a transparent wellness estimate from VO2max context, not a validated biological-age score, personal mortality prediction, exercise clearance, or diagnosis.

Sleep score, efficiency, latency, debt & consistency

Ojava calculates a 0 to 100 sleep score from duration, regularity, and the most recent tracked night. It also tracks your sleep debt as a running balance: how much sleep you’ve owed or banked over a rolling window. Sleep consistency shows whether your sleep times are stable night-to-night, which is often a better predictor of well-being than sleep duration alone. These metrics help you see patterns over time and understand how uneven sleep or chronic undershoot affects readiness and recovery. Sleep score, sleep debt, and sleep consistency each carry public source links for adult sleep duration, multidimensional sleep health, and sleep regularity where those sources apply.

When a source provides sleep efficiency directly, or provides enough asleep and time-in-bed context to calculate it, Ojava summarizes the latest efficiency percentage and recent average in the same readiness card. When a source provides sleep-stage rows, Ojava also summarizes the latest staged night with deep, REM, light, awake, and restorative minutes. Sources that only provide total sleep still work normally, and Ojava leaves the efficiency and stage detail blank instead of guessing.

When a source provides sleep latency, Ojava shows the latest minutes to fall asleep and the recent average next to the other sleep context. Sleep efficiency, latency, and stage details are wellness context from your own tracker only. Ojava does not screen for sleep conditions, replace a sleep study, send real-time warnings, or recommend care changes.

When sleep rows include usable timestamps, Ojava also summarizes timing regularity: how much the sleep midpoint moves across recent nights, plus a weekday/weekend midpoint gap when both sides have enough rows. This stays in the recovery routine lane, useful beside travel, training, and energy notes.

Ojava Coach also receives a Daily Sleep Review packet when enough sleep context is present. It composes sleep score or sleep debt, efficiency, latency, timing regularity, stages, environment rows, readiness, and HRV trend into one headline with focus areas, strengths, missing inputs, and the next review prompt. This is general-wellness sleep context only: Ojava does not diagnose sleep conditions, replace a sleep study, control devices, send alerts, prescribe care, or change a treatment plan.

Sleep routine readiness for Coach summarizes source-provided or saved bedtime target, wake target, alarm time, sleep goal, timing regularity, sleep debt, latency, efficiency, sleep score, and available environment signals before Coach uses that context. It is visit-prep and general-wellness context only. Ojava does not set alarms, schedule notifications, wake you, automate temperature, control a bed, recommend exact bed or wake times, diagnose insomnia or circadian disorders, replace a sleep study, send alerts, prescribe, or change treatment.

Ojava also builds an annual sleep recap from your own source-backed sleep rows. When enough nights are present for the current year, the readiness card and Ojava Coach can summarize tracked nights, average sleep, total source-backed sleep, longest tracked night, short-night count, highest-average tracked month, and available source sleep score, HRV, or resting-heart-rate context. The recap includes shareable text you can review, but Ojava does not post it publicly, control a sleep device, diagnose sleep quality, replace a sleep study, send alerts, or recommend treatment.

There is a matching annual activity recap built from your own logged workouts and strength sets. When enough activity is present for the year, Ojava Coach can summarize logged workouts, active days, total logged active time and distance, your longest active streak, the busiest tracked month, your most logged activity, and total logged strength volume, falling back to last year early in a new one. It is a general wellness year-in-review only, not a training prescription, performance prediction, workout clearance, exercise plan, or medical advice.

When a sleep system, wearable, or sleep-app export includes room temperature, bed temperature, skin temperature, respiratory rate, oxygen saturation, snoring minutes, or breathing-variation rows, Ojava summarizes which source rows are present and which are missing before Coach uses them. This is sleep-environment and recovery context only. Ojava does not infer apnea, illness, temperature-control needs, device automation, alerts, or care changes from those rows.

Ojava also prepares a sleep blueprint readiness packet when the record has enough supporting inputs. The packet checks whether age, profile sex if you have provided it, sleep stages, REM score or REM minutes, preferred sleep temperature, and source-provided room or bed temperature are present before Coach uses the line named “Sleep blueprint readiness.” It names present and missing inputs only, so a thin record stays thin instead of being filled in by guesses. Ojava does not control a sleep device, automate temperature, diagnose sleep quality, replace a sleep study, send sleep alerts, or recommend care changes.

For explicit smart-bed, temperature-schedule, smart-alarm, or sleep-automation questions, Ojava Coach can prepare a sleep-device automation readiness packet. It inventories source bed temperature, room temperature, preferred sleep temperature, sleep routine targets, and recent sleep outcome rows, then keeps activation gaps visible. It is not device control: Ojava does not schedule alarms, change settings, automate temperature, recommend exact temperature settings, diagnose sleep conditions, monitor in real time, send alerts, or replace a sleep study.

For shared-bed, bed-partner, side-of-bed, dual-zone, or sleep-system attribution questions, Coach can prepare a separate sleep-system attribution readiness packet. It checks whether source rows appear labeled by side, user label, or shared sleep-system export before those rows are discussed. If the export has shared sleep context but no side or user label, the packet says attribution is missing instead of mixing rows together. Ojava does not infer a partner health pattern, merge partner data into your record, share data, control a bed, automate temperature, diagnose sleep conditions, send alerts, or replace a sleep study.

When Apple Health or another source includes time in daylight, environmental sound, or headphone audio rows, Ojava summarizes the 7 and 14 day coverage windows and names missing exposure days. Coach can use those facts as association-only routine and recovery context. Ojava does not infer cause, hearing status, sleep quality, care needs, hearing screening, clinical monitoring, alerts, or care advice from those rows.

When you ask about your body clock, circadian rhythm, sleep schedule, daylight, shift work, food timing, late caffeine, late meals, or fasting window, Ojava Coach can now prepare a body-clock readiness packet from source sleep timing, daylight exposure, reviewed food timestamps, later food or drink clues, fasting windows, and recovery context. It organizes the rows that are ready for review and the inputs still missing. It does not recommend exact bed or wake times, set alarms, schedule notifications, diagnose circadian or sleep disorders, prescribe fasting or diet changes, treat sleep conditions, monitor in real time, or control devices.

Training load (acute vs. chronic)

Training load compares your acute training load (short-term effort, typically the last 7 days) to your chronic load (your typical level, usually 4 weeks), giving you the classic strain ratio. A high acute-to-chronic ratio suggests you may be ramping up too fast (risk of overtraining or injury), while a low ratio means you’re below your typical baseline (good recovery opportunity, or a sign you’re building a new fitness base). This is the training balance most wearables surface, and Ojava carries it forward.

The training-load result links to the acute:chronic workload-ratio source context used for strain discussions. Ojava keeps that as training-context education only, not injury prediction, workout clearance, or a prescribed training plan.

Resting heart rate & cardio recovery

Ojava tracks your resting heart rate (RHR) trend and how quickly it recovers after exercise (the beats-per-minute drop in the first few minutes after a workout). Both are indicators of cardiovascular fitness and recovery. A lower RHR and faster recovery generally reflect good aerobic fitness and parasympathetic tone. Ojava shows these as trends so you can see if they’re improving over months.

When you ask Ojava Coach how your vitals are looking (or about a specific reading trending), it pulls a combined recent-vitals summary from your own logged data: blood pressure, resting heart rate, body temperature, oxygen saturation, and respiratory rate, each with its latest value, recent-vs-earlier trend, and how many days it covers, plus a note of anything you haven’t logged lately. This is your own data organized for a conversation with your clinician; Ojava never diagnoses high blood pressure or a fever, never scores clinical risk, and never monitors or alerts.

If you ask whether a home blood-pressure log is ready to discuss, Coach can also count paired systolic and diastolic days, morning and evening timestamp coverage, source labels, missing cuff or setup notes, and questions to take to a clinician. The packet cites AHA, USPSTF, ACC/AHA, and MedlinePlus context, while avoiding blood-pressure categories, targets, diagnosis, treatment, monitoring, or alerts.

Heart rate variability (HRV) trend

HRV is the millisecond-to-millisecond variation in the time between heartbeats, and it correlates with nervous-system balance, recovery, and stress resilience. Ojava tracks your HRV trend relative to your own baseline, not against population averages, so you see whether YOUR HRV is improving, stable, or trending down. Low HRV typically signals fatigue, stress, or illness, while higher HRV suggests better recovery and resilience.

Activity streak

A simple counter of consecutive days you’ve logged activity (from your wearable or manual logs), which can be a useful motivation tool and a way to see consistency at a glance.

Mobility signals

When Apple Health or another source provides mobility rows, Ojava summarizes the latest walking steadiness score, walking speed, step length, double support, walking asymmetry, six-minute walk distance, and stair speed in the same readiness card. These are your own wearable mobility signals for trend context only. Ojava does not classify fall risk, diagnose a gait issue, clear activity, or send mobility alerts.

When you ask Coach about physical function, functional reserve, grip strength, gait speed, chair stand, SPPB, SARC-F, stair climbing, balance, mobility, rehab, or physical therapy, those mobility rows can join accepted grip, gait, chair-stand, balance, symptom, body, rehab, and goal context in a source-backed prep packet with SPPB, PURE grip-strength, SARC-F, and EWGSOP2 references. It is clinician, physical therapist, or trainer conversation prep only: no frailty or sarcopenia diagnosis, SPPB or SARC-F score, disability prediction, activity clearance, exercise prescription, test order, referral, or clinician-review claim.

Temperature trend

If your wearable tracks body temperature, Ojava shows the trend over time. Temperature can signal infection, recovery stress, or (in women) menstrual-cycle phase. Ojava doesn’t interpret these, it just surfaces the trend so you can correlate it with how you feel.

This week vs. last week digest

Ojava generates a plain-language weekly summary showing how this week’s key metrics (sleep, activity, readiness, HRV, HR recovery, training load) compare to the prior week. It highlights the biggest changes and puts them in context: is your fitness improving, are you recovered, do you need more rest?

Trend charts

Per-metric charts let you scroll through months of data for heart rate variability, resting heart rate, total sleep, VO2max, blood oxygen saturation (SpO2), respiratory rate, daily steps, source-provided body composition, hydration and sweat readings, and other measurements. See your own data without an account on the public sample page.

General-wellness guidance

When your readiness is low, Ojava might suggest prioritizing easy training, sleep, and recovery. When it’s high, pushing harder in training is more likely to pay off. Training load and HRV trends can inform your weekly plan: build gradually to avoid overtraining, spike recovery days when you need them, and pay attention to sleep consistency because it’s often under your control and drives downstream metrics. This is general fitness and wellness coaching, grounded in your own data trends.

Native HealthKit and Health Connect sync

Manual export import is live today on web. The native app code now includes a foreground sync action for Apple HealthKit on iOS and Android Health Connect on Android: after device permission, Ojava can read the last 30 days of supported health and wearable categories, normalize them into the same private wearable table as exports, and refresh your readiness, sleep, training, body, glucose, oxygen, blood-pressure, total-energy, basal-temperature, nutrition-app, and recovery views. The same native path also reads workout sessions when permission is granted, turning duration, active energy, and distance into the existing exercise-minute, active-calorie, distance, and cycling-distance rows. The locked native adapter does not expose dietary macro or water-intake samples, so those stay on reviewed file imports, nutrition-app imports, hydration sensors, and manual Water Log rows until an adapter or provider can truthfully read them. Public activation still waits on the store-signed native build and real-device permission proof.

Ojava Coach also receives a fitness source reconciliation packet when recent workout or wearable activity rows are present. It keeps active minutes, steps, and active calories in separate source lanes, prefers wearable exercise minutes and wearable steps over reviewed workout-import fallbacks, and names same-day overlaps so Coach does not add the same movement twice. This is review-only source context, not proof that any device or app source is accurate.

The release gate is read-only by design. iOS declares HealthKit sharing copy, Android strips Health Connect write permissions and links Health Connect permission review to the Ojava privacy page, and Ojava keeps native activation flags off until store-signed device testing and privacy review are complete. While those flags are off, the foreground sync action fails closed before requesting HealthKit or Health Connect permissions. The native path does not write data back, run continuous monitoring, send clinical alerts, or make care decisions.

A separate Google Health cloud connector is also built behind an activation gate. After the production migration, Ojava-owned OAuth client, consent screen, server-only configuration, and live verification are complete, it can read supported activity, body, heart, oxygen, temperature, glucose, respiratory, sleep, and fitness rows into the same private wearable pipeline. It supports reconnect, manual and scheduled refresh, provider-first disconnect, account deletion, resumable full-history backfill, and token-free connection export with initial progress. Only data types covered by the access you grant are requested. The connection card shows shared and unavailable rails, and reconnecting to add access restarts full-history import for the expanded set. Each authorized data type keeps a private continuation cursor, so a dense history resumes instead of restarting. If Google rejects a saved continuation token, Ojava replays that same window once. A second rejection pauses the connection without advancing its coverage point, exposes the recovery code in the token-free export, and asks you to reconnect. Reconnect clears the stalled cursor and starts a fresh deduplicated history import. It is unavailable until those external activation checks pass, and it never writes to Google Health or sends clinical alerts. Pausing activation hides new connection and sync actions but preserves status and disconnect for an existing authorization.

Terra remains a possible future paid cloud adapter for broad wearable coverage, not a current primary path or live dependency. Ojava pins a server-side activation contract for its hosted connect route, webhook target, signature check, patient reference binding, supported payloads, and review rails, but Terra-backed catalog entries are not available connections today. File import is live, while signed-app native sync and any future cloud adapter stay read-only, consent-gated, and activation-gated until their required proof is complete.

The source catalog now also covers more specialized devices and bridge apps, including Kardia, Hilo/Aktiia, Empatica, Wellue/Viatom, Masimo, MedM Health, Diabetes:M, FatSecret, FoodNoms, YAZIO, Lifesum, Zero, Fastic, Concept2 ErgData, Hydrow, Tonal, Ergatta, Aviron, Technogym, TrainerRoad, Runalyze, Xert, MySwimPro, Tacx, Wattbike, Favero Assioma, 4iiii, Quarq, Ride with GPS, Gaia GPS, OHealth, and Health Sync. Ojava treats those as user-owned measurements, workouts, or record context only. It does not interpret ECG waveforms, monitor you in real time, or turn connected-device readings into clinical decisions.

Ojava Coach can now separate source setup from source-account activation. Source setup answers which import path fits a device. Source-account activation names what must be ready before Oura, WHOOP, Eight Sleep, Apple Health, Health Connect, or Terra can move beyond planning: provider contracts or native entitlements, user consent scope, privacy and security review, source-quality checks, and webhook or import audit trails. Until those rails are active, Ojava does not claim live account sync, store source credentials, write back to sources, control devices, monitor in real time, or send alerts.

For glucose-specific source questions, Coach narrows that same setup model to the CGM path: current imported glucose rows, timestamped meal readiness, file-ready Apple Health, Health Connect, or CSV exports, and gated Dexcom, Libre, native, or partner connector work. It can explain which path is ready for review without claiming live CGM connectivity or glucose monitoring.

Science references

Wearable resources show the HRV, sleep, training-load, cardiorespiratory-fitness, and device validity sources behind Ojava’s general-wellness calculator language. They also link the pulse-wave-velocity reference and cohort-association sources used when an export provides arterial-stiffness or cardiovascular-age rows. Score cards keep those source links beside Ojava-computed readiness, sleep, fitness age, training-load results, and source-provided arterial-stiffness context, and Coach can include them when you ask about evidence or sources.