Elara Research Platform · Clinics & institutes
Capture what happens
between visits.
Elara is the research infrastructure for longitudinal real-world data: patient-reported outcomes, symptoms, activity, context and wearables — collected in one place, read as individual trajectories and exported research-ready.
Elara Health works with the ME/CFS research group at the Department of Anaesthesiology of Universitätsklinikum Regensburg as part of the ME/CFS TRACK study.
The study longitudinally investigates autonomic, functional and subjective parameters in patients with Myalgic Encephalomyelitis / Chronic Fatigue Syndrome (ME/CFS). The aim is to better understand the course of the disease and possible relationships between different health parameters. Elara Health is used here as a digital research instrument for capturing patient-reported health data in everyday life.
Collect. Understand. Study.
Longitudinal Capture
Real-world data collection between visits
Prospective collection where the trajectory actually forms: in participants’ everyday lives, between study visits, with no manual transfer into the dashboard.
Validated instruments right inside the app: Canadian Consensus Criteria, FUNCAP-27, SF-36 and fibromyalgia ACR — with per-study schedules and reminders.
Longitudinal Intelligence
Within-person trajectories
Patient-reported, behavioural and wearable data become interpretable per-person trajectories: within-person modelling, temporal feature extraction and multimodal integration, ML-supported. The statistical methods behind it are implemented, not announced — validated prediction models are something we explicitly do not claim.
Each person is their own control: deviations are measured against that person’s own baseline, not against a group mean.
Research Dashboard
Cohort monitoring and research exports
Not a CSV hand-off, but the environment in which your team actually runs the study: responses flow automatically into cohorts, time series and analyses — collection monitored, datasets exported analysis-ready.
Participants, groups and study arms in one overview — with drill-down to the individual person.
How research teams work
The platform is condition-agnostic. These four designs come from the area we know best — and show how far the longitudinal axis carries.
Longitudinal trajectories in ME/CFS
Canadian Consensus Criteria at inclusion, FUNCAP-27 at follow-up, plus daily PEM and pacing tracking against passively collected wearable data. Exertion and delayed symptom response sit on one shared timeline — precisely the sequence a cross-sectional questionnaire structurally cannot capture.
- Inclusion
- Canadian Consensus Criteria
- Endpoint
- FUNCAP-27 · functional capacity
- Exposure
- activity load in MET
- Design
- within-person, longitudinal
In the ME/CFS TRACK study, Elara Health is used as a digital research instrument: symptoms, exertion and wearable signals are collected in participants’ everyday lives and enter the analysis in standards-conformant coding.
Regensburg University Hospital · Department of Anesthesiology, ME/CFS research group — ongoing research collaboration
- Citizen Science
In an ongoing citizen science study, people affected collect their own longitudinal data together with a patient organization via Elara Health — collection sits with the participants themselves, not with a study center.
Patient organization · citizen science study — ongoing collaboration, name to follow once cleared
- Centi Health
Aggregated trajectories appear in the Centi Health patient record — code-based, GDPR-compliant, revocable at any time. Collection stays with those affected; interpretation happens in the consultation.
Centi Health · trajectories between visits — existing integration
- Health Connect
Works with the devices your participants already own.
Elara reads the common wearables and health platforms — participants need no extra device and no second app. The passive signals land time-coupled next to questionnaires and the symptom diary, on one shared timeline.
Documents to read up on
Common questions
Answers to the key questions research teams ask before a collaboration.
How can I take part?
Use our contact form. In a personal conversation we clarify which features make sense for your research question. You then receive access credentials for your personal dashboard, where you can configure questionnaires and schedules and invite new participants to your study.
Is Elara limited to ME/CFS, Long COVID and fibromyalgia?
No. The platform collects and analyses longitudinal real-world data — questionnaires, symptoms, events, activity, context and wearables — independently of the condition. Instruments, frequencies and endpoints are configured per study. Post-infectious and chronic conditions are where we have gone deepest; that is our focus, not the limit of what the platform covers.
Is data on Elara secure?
Yes. Data protection is our highest priority. We use modern security standards and encryption technologies for data transmission and storage. Servers are located in Frankfurt (EU-West-1), and a DPA is available.
How quickly can a study start?
Pilot preparation typically covers questionnaire setup, schedules, reminders, exports and team onboarding — go-live usually within two weeks.
What does Elara contribute methodologically to a study?
The longitudinal axis that many ME/CFS and Long-COVID studies lack: exertion, delayed symptom response, recovery and pacing dynamics captured in everyday life on one shared timeline. Each person acts as their own control (within-person), so the temporal sequence of exposure and delayed reaction — as with post-exertional malaise — becomes visible in a way a cross-sectional questionnaire structurally cannot capture. Severely affected, housebound patients also become reachable through passive, at-home monitoring.
What does the analytical layer do — and what is validated?
The analytical layer supports within-person modelling, temporal feature extraction, multimodal integration and cohort statistics; machine learning works as a technology underneath it. What we explicitly do not claim: validated diagnostic or prognostic prediction models. Models are developed on the data collected — validating them is study work, and it is reported as such.
Can you analyse longitudinal data we have already collected?
The analytical layer is not tied to our own collection. Whether your existing PRO, symptom or wearable data can be connected is something we assess case by case on a sample extract — get in touch.
Is the data research-grade and standards-compliant?
Yes. No free-text tracking and no ad-hoc dumps: the core streams are mapped to recognized clinical and research standards — symptoms to SNOMED CT (plus HPO and ICD-10-GM), lab values to LOINC, activities to metabolic equivalents (MET). Vital data can be exported as FHIR R4 / Open mHealth with LOINC and UCUM — including provenance and GDPR pseudonymization, integrable without weeks of recoding.
Collaborate
Ready for the
next study?
We start fast. Pilot setup in under two weeks, with personal support throughout the entire study design.