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EnaResearch
Use case

Collect activity data with its source, without double counting

In physical activity and sports studies, EnaResearch collects activity, heart and sleep data from the participant’s phone and watch together with its source. Cumulative metrics such as steps and active energy are collected as 5-minute buckets, so overlapping phone and watch samples are not counted twice.

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Stored with its source

Each measurement keeps its source type, device or app, time at the source and transformation version; the same metric from several sources is not merged.

5-minute buckets

Steps and active energy are collected as 5-minute buckets through the platform’s de-duplicating aggregate query.

Plan first, results second

Test, variables, significance level and hypothesis are approved; approval freezes the dataset version and cut-off.

Common challenges

  • The phone and the watch both write the same steps, and totals are inflated.
  • Data from different devices and apps gets mixed, and nobody knows where a value came from.
  • Before-and-after training comparisons are recomputed by hand every time.
  • The analysis method can change after the results have been seen.

Data kept together

  • Steps, distance, floors climbed, active energy
  • Workouts (22 common types)
  • Heart rate, resting heart rate, heart rate variability
  • VO₂max and respiratory rate
  • Sleep stages
  • Perceived exertion (Borg 6–20, manual entry)

Phone and watch data

On iOS, data written to Apple Health by Apple Watch and other sources is read through HealthKit; on Android, data from apps and devices that write to Health Connect. The researcher picks the metrics for the study; the permitted sources follow from that choice, and metrics that are not selected are not collected.

The participant apps are built and await store release. A path for Chileaf wearables, through the phone or through one hub listening to several participants, is in development; no capability that is not in the vendor’s documentation is assumed.

Quality flags and completeness

Invalid values are rejected at ingestion. Suspicious values such as out of range, sudden jump, source conflict and low wear time are flagged but never changed. The data quality page shows completeness per participant and metric.

Variables and statistics

Variables such as the mean heart rate over the first 14 days of participation, a metric summarized over a window around an anchor, are versioned. No result is produced before the analysis plan is approved; tests are computed deterministically with established open-source libraries such as SciPy and statsmodels, and library versions are stored with each result.

Variable datasets can be exported as CSV, Excel, a labeled SPSS (.sav) file and an R script; participants appear only under their pseudonym.

  • Descriptive statistics
  • t-tests
  • Nonparametric tests
  • Correlation and regression

Physical activity and sports studies

Activity, heart and sleep data; 5-minute buckets, variables and pre-approved analyses.

  1. 01

    Pick metrics

    Select activity, heart and sleep metrics in the protocol.

  2. 02

    Collect data

    The participant activates the app and grants permissions.

  3. 03

    Approve the plan

    Approve the analysis plan before seeing results.

  4. 04

    Export

    Take the variable dataset into your statistics software.

Related pages

Related use cases

Frequently asked questions

Which watches and bands are supported?
Data from devices that write to Apple Health or Health Connect is collected through the phone app. Support for the Chileaf CL837 and CL900 hub is in development. Other third-party devices connecting directly are out of scope.
Do the phone and watch count the same steps twice?
Steps and active energy are collected as 5-minute buckets through the platform’s de-duplicating aggregate query, so overlapping phone and watch samples are not counted twice.
Can we monitor athletes’ performance live?
No. EnaResearch is a research data platform; it offers no real-time monitoring or alarms.

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We'll show what EnaResearch does today, share the roadmap openly and look at your studies and data sources together.

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