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LifeFromData

Collection possibilities

Start with an example.
Make it your study.

From DNA and bloodwork to a meal photo, a voice note or a night of sleep. Combine clinical tests, device signals and everyday logs around your research question.

Illustrative study designs, not available inventory. Source access, integrations and clinical collection are scoped for each study.

Inputs to scope

Heart rate · HRV · Sleep · Activity · Temperature · Weight · Blood pressure · Glucose · SpO₂

4 illustrative designs · Original illustrative photography

Example / Time-series modeling

Heart rate. HRV. Context.

Pair wearable heart-rate and HRV observations with activity, rest and reported events.

Inputs, labels & delivery
Inputs
Source-defined HR and HRV metrics, device metadata, coverage, event logs
Reference labels
Measured or vendor-derived metrics with method and window retained
Delivery concept
Parquet + device and coverage manifest

Example / Multimodal modeling

Sleep, with the next morning.

Pair device sleep summaries with next-day self-reported energy and routines.

Inputs, labels & delivery
Inputs
Device summaries, coverage, sleep diaries and daily check-ins
Reference labels
Vendor-estimated sleep metrics and separate reported ratings
Delivery concept
Parquet + data dictionary

Example / Time-series research

Temperature, in sequence.

Scope a repeated-temperature study with capture timing and relevant cycle context.

Inputs, labels & delivery
Inputs
Device measurements, method, timing, optional cycle self-reports
Reference labels
Measured temperature; reported events, not confirmed ovulation
Delivery concept
Parquet + device manifest

Example / Longitudinal modeling

Weight, with the routine.

Follow repeated weight measurements alongside food, activity and participant context.

Inputs, labels & delivery
Inputs
Scale measurements or manual entries, units, timing and device metadata
Reference labels
Source-tagged measurements; derived trends kept separate
Delivery concept
Parquet + time-indexed event logs

What does your model need to learn?

Start with the task. Define the collection together.

Scope a pilot