For teams running studies & trials

Build Your EMA and Biometrics Research Apps

Custom iOS + Android apps for studies and trials — ecological momentary assessment, wearable & phone biometric data, weekly progress emails, and integration with REDCap and other research tools — built to your protocol and owned by you.

Whether you run studies, trials, or validations — across academia, industry, healthcare, or the non-profit world — the app adapts to your protocol, not the other way around.

We’re not a platform you rent and bend your study to fit. We’re a development partner that builds the research app you need — with the transparency, provenance, and reproducibility research demands. 15+ years of ethically-approved, IRB-ready clinical-trial apps — including a one-year, 165-participant EMA deployment at the McGill University Health Centre.

Used in studies & trials at

McGill · Dalhousie · Saskatchewan · Oxford · Oxford Brookes · Exeter · Mayo Clinic Arizona

Book a scoping call
How we scope a study

Founded by Professor Nancy Mayo, PhD — James McGill Professor, Department of Medicine and School of Physical & Occupational Therapy, McGill University; Research Scientist at the Research Institute of the McGill University Health Centre (RI-MUHC), leading programs on function, disability, and quality of life. Her research anchors the science behind our apps.

What do you need for your research or clinical trial?

Mix and match the building blocks your protocol needs — momentary assessment, wearable & phone biometrics, and participant engagement — in one app you own.

EMA & timed-survey apps

Bring the questionnaire to the participant as a native app on their phone — in their natural environment, at the right moment — and record exactly when each response was given.

Flexible instruments — multiple choice, Likert (5/7/10-pt & custom), bounded numeric, free text — with answer-driven branching & skip logic; validated scales encode cleanly.
Precise scheduling — fixed-interval prompts (minutes→days) and multi-phase designs, with time-windowed availability that prevents retrospective back-filling.
Self-healing reminders — three-stage, reboot-safe notifications that deep-link into the active survey.
Automatic compliance — every prompt tracked (completed / missed / expired); adherence & response timing as exportable data.
Supports classic EMA, experience sampling (ESM), ambulatory assessment, and daily diaries.

Biometrics — wearable & phone data

Turn the phones and wearables your participants already own into research-grade activity and physiological data — unified, deduplicated, and fully traceable.

Daily summaries on the phone — e.g., end-of-day heart rate and steps from a Garmin (or Apple Watch, Fitbit, Pixel Watch).
One unified model across Apple Health, Google Health Connect, the phone sensor and wearables — with source + device on every record.
Deduplication done right — the aggregate API and documented rules, never naïve summing that doubles step counts.
Reliable background sync that keeps collecting even for weeks-idle participants — future-proofed for Google Fit’s 2026 shutdown.
Deterministic, reproducible processing with research-grade exports.

Engagement & integrations

Keep participants engaged and your data clean — and connect to the research tools you already use.

Weekly progress emails — each participant’s week summarised into personalised graphs and emailed out (SendGrid); feedback that drives retention.
Compliance & data-quality flags — low adherence and data-threshold breaches flagged automatically, so you act early.
Two-way survey integration — remind participants and confirm completion with REDCap, Qualtrics, and other tools.
Demonstrated end-to-end in the McGill one-year study.

Why build with us, not rent a platform

Custom-built and yours

Tailored to your protocol — instruments, schedule, cohorts, branding, consent — and you own the result.

Transparency & reproducibility by design

Published, tunable rules; documented deduplication and source precedence; provenance on every record. You know exactly how each data point was measured — and can reproduce it.

Deep phone-platform integration

Apple Health and Google Health Connect done right — including the failure modes most teams discover too late.

A real track record

15+ years of ethically-approved, IRB-ready clinical-trial mobile apps and research data pipelines, in production today.

Step capture, done properly

“Step count” sounds simple. It isn’t — the same participant produces different totals depending on the phone they carry and the watch they wear. Here’s where our step data actually comes from, and why customizable, transparent, multi-source capture beats single-device or rent-a-platform.

The phone is the hub — not the watch

Data flows wearable → manufacturer’s app → Apple Health (iOS) / Health Connect (Android) → our app → export. We read the health store the phone already runs — so one app ingests whichever device a participant wears, plus the phone itself. No per-brand cloud integration (Garmin Health API, Fitbit Web API) to license and maintain, and no lock-in to one brand.

iOS and Android count differently — we model both

Both stores hold what a source wrote and count nothing themselves, so a phone and watch both writing can double the same steps. We use each platform’s aggregate API and documented deduplication with explicit source precedence — never naïve summing — and stamp source + device on every record.

A watch is only usable if its app feeds both health stores

Device	Serves a mixed iPhone + Android cohort?
Garmin	Yes — years-stable, no Garmin API needed
Fitbit / Google Health	Yes — Apple Health native since 2026
Withings	Yes — medical-grade HR
Apple Watch	iPhone only — no Android path
Samsung Galaxy Watch	Android only — no Apple Health path

And when there’s no wearable at all, our app becomes its own collector from the phone’s hardware step sensor — no account, zero setup — closing the silent gaps that wreck longitudinal data.

Device-agnostic — Garmin, Fitbit, Withings or the phone sensor, together; no single-brand lock-in.
Transparent, not a black box — published deduplication and precedence rules you can defend to a reviewer.

Customizable — precedence order, aggregation window and thresholds set to your protocol.
Reproducible — deterministic, versioned processing; the same inputs always yield the same steps.

In the field

A one-year study at the McGill University Health Centre

Researchers at the McGill University Health Centre used our two apps — StepCatcher for passive daily step capture and HandHeld Monitoring for a daily symptom rating — to follow a cohort with post-COVID syndrome for a full year. Most EMA activity-and-symptom studies run two weeks; this one ran 52 — captured entirely remotely under an ethics-approved protocol.

1 year

of daily capture per participant

165

participants on both apps

~88,000

person-days captured

Everything this page promises is visible in that deployment — smartwatch deduplication, long-horizon continuous capture that survives months without a clinic visit, deterministic documented processing, weekly progress emails to participants, and REDCap completion tracking. StepCatcher also pairs with Heel2Toe, our clinical gait-training wearable, for biomechanical gait-quality and fall-risk metrics.

How we scope your study

Tell us your protocol and we’ll turn it into a working app. We’d discuss:

Instruments — your questionnaires and item types (we encode validated scales).
Schedule — prompt frequency, time windows, study duration, phase structure.
Sampling strategy — fixed-interval, signal-contingent, or event-contingent.

Data sources — Apple Health, Health Connect, wearables, or app-collected.
Cohorts — study arms and assignment.
Data, compliance & consent — exports, adherence metrics, and your institution’s IRB/ethics requirements.

If you can describe your protocol, we can build it.

Who gets prompted, when, how often, with what questions, and from which devices — tell us, and we’ll scope and cost it.

Book a scoping call

sales@physiobiometrics.com · physiobiometrics.com