Management unit
Experiment · event · participant
Connect each file to the study, measurement event, and participant code.
Platforms · Biosignal Datahub
Biosignal Datahub
A research data platform that connects biosignal files with experiment, participant, event, and device context for search, analysis, and collaboration.
Product overview
What does it measure and what do you get?
Data flow
Collect→standardize→search
Organize uploaded data into a common structure and find it by conditions and metadata.
Use
Analyze · share · reuse
Review biomarkers and visualizations and collaborate within an appropriate access scope.
Designed for these workflows
Research data managers
Use it to organize multiple studies consistently and preserve context through staff changes.
Data analysts
Use participant, signal, device, and event conditions to find comparable data.
Collaborative research teams
Work from the same data structure and an access scope appropriate for each partner.
How to use
Manage your first experiment in five steps
Create the experiment and measurement conditions first so that search and analysis retain the study context.
Before you start · Define the research structure before upload
Experiment details
Prepare the objective, protocol, recording period, owner, and access scope.
Participant codes
Avoid direct personal data in filenames and prepare only coded identifiers and attributes required for analysis.
Signal and device details
Record signal types, channels, units, sampling conditions, and measurement equipment.
Events and files
Define event rules such as Baseline, Task, and Recovery and prepare source and result files.
- STEP 1
Sign up and create an experiment
Sign in to Datahub and register the study name, objective, period, and owner. Review private or shared access according to the collaboration scope.
- Use study codes instead of personal data
- Record the objective and protocol
- Confirm access roles and owner
Start with sign up, create experiment, then upload and review the summary. - STEP 2
Configure measurement events and participants
Separate Baseline, Task, Recovery, or other changes in analytical condition into events and connect participant codes and repeated sessions.
- Use consistent event names and order
- Connect participant, group, and session
- Compare the structure with the study protocol
- STEP 3
Upload signal files and metadata
Connect PPG, IMU, and other files to the correct participant and event, then record signal type, channel, unit, device, and sampling conditions.
- Check supported file type and size
- Match file and participant code
- Record signal unit and sampling condition
Use the summary to confirm that files and research context are connected. - STEP 4
Search by condition and metadata
Narrow datasets by experiment, participant, signal, event, and keyword, then inspect the files in the results.
- Review filters and result count
- Compare matching event and signal conditions
- Confirm the source-file and metadata relationship
Find data through structured conditions rather than filenames alone. - STEP 5
Analyze summaries and share within scope
Review biomarkers and visualizations, then trace results back to the participant, event, device, and source file. Set sharing according to consent and privacy requirements.
- Confirm signal and units in each visualization
- Trace results back to source conditions
- Review recipients and access roles
Review summaries together with the source data and experiment context.
Download
Review a sample file first
Check the file structure, columns, and units before measuring so that you can prepare your analysis pipeline in advance.
Datahub metadata planning sample
Use this reference CSV to organize experiment, event, participant, signal, device, and file relationships before upload.
Included fields
experiment_code · event · participant_code · session · signal_type · device · unit · sampling_rate_hz · file_name · access_scope
This is an anonymous planning reference, not an official Datahub automatic-import template.
Download metadata planning CSVData example
These values are stored in the CSV
The anonymous values below demonstrate the file structure. Scroll horizontally to review every sensor column.
Experiment structure
Keep objective, protocol, period, owner, and access scope.
Event data package
Connect participant, session, signal, device, and files within each event.
Searchable metadata
Find the required dataset by conditions and keywords.
Analysis summaries
Review biomarkers and signal characteristics and trace them back to source files.
Collaboration scope
Separate private, invited, and eligible public datasets.
Research metadata planning example
Separating Baseline and Task files by event and signal preserves the conditions required for search and comparison.
| experiment_code | event | participant_code | session | signal_type | device | unit | sampling_rate_hz | file_name | access_scope |
|---|---|---|---|---|---|---|---|---|---|
| DEMO-STUDY-01 | Baseline | P001 | S01 | PPG | EmoConnect | dB | 50 | P001_S01_baseline_ppg.csv | private |
| DEMO-STUDY-01 | Task | P001 | S01 | PPG | EmoConnect | dB | 50 | P001_S01_task_ppg.csv | team |
| DEMO-STUDY-01 | Task | P001 | S01 | ACC | EmoConnect | m/s² | 50 | P001_S01_task_imu.csv | team |
Before contacting support
Check these items in order
A file does not upload
- 1.Check sign-in and experiment access.
- 2.Check file type and size.
- 3.Check network connectivity.
- 4.Review filename and participant or event mapping.
An uploaded file is missing from search results
- 1.Confirm the correct experiment and event.
- 2.Review signal and participant metadata.
- 3.Clear filters and date ranges.
- 4.Review processing or standardization status.
It is hard to compare matching conditions
- 1.Standardize event names and order.
- 2.Review signal units and sampling conditions.
- 3.Separate participant groups and repeated sessions.
- 4.Complete missing metadata on existing files.
Frequently asked questions
Can I upload files first and create the experiment later?
We recommend creating the experiment and event structure first, then connecting files so that the research context is not lost.
Should I register participant names directly?
Use coded identifiers and attributes required for analysis and follow privacy and consent rules. Do not place direct identifiers in public views or filenames.
Must events be named only Baseline, Task, and Recovery?
No. Names and fields can match your protocol. The important rule is to keep files and measurement conditions connected within the same event.
Must every dataset be public?
No. Set private, invited, or public access according to the research stage, collaboration purpose, consent, and privacy requirements.
Prepare these details for a Datahub inquiry
Send the experiment structure and file status together so upload, search, or access issues can be checked quickly.
Contact us about Datahub