AI-enabled wearable · launching 2026

Reimagining rehab, one rep at a time.

A wearable sensor and app that learns what correct exercise form looks like — then tells patients, in real time, whether they're doing it right. Physios finally see what happens after the patient leaves the room.

Get early access See how it works

Currently piloting with a major private hospital's rehabilitation ward, private physiotherapists & real patients, Melbourne.

30%

Typical adherence to prescribed rehab exercises — patients are largely unsupervised and unsure if they're doing it right.

$10K

Added annual cost per patient when recovery is delayed by poor exercise adherence.

Lost revenue

A significant, recurring source of lost income for physiotherapists — patients who don't recover on schedule mean fewer sessions, referrals and outcomes to point to.

How it works

One sensor. Two people who finally see the same thing.

The physio sets the standard once. The patient gets feedback every rep, at home. Nobody has to guess anymore.

▸ Watch the demo

Learn the form

During a supervised session, the physio prescribes an exercise while the patient wears the sensor. ExerWatch's AI learns what "correct" looks like — personalised to that patient.

Practise at home

The patient wears the strap and opens the app unsupervised. No camera, no clinic visit required.

Get instant feedback

Green means correct, amber means partial, coral means the exercise wasn't done correctly or the range of motion wasn't complete — every single rep, in real time.

Physio sees the data

Objective adherence and technique reports land in the physio's app between visits — a feedback loop that doesn't exist today.

Built for both sides of the room

For the clinic. For the patient.

Physiotherapists & clinics

Prescribe once, then see exactly how patients are doing between visits — without relying on self-reported diaries.

Objective adherence & technique reports per patient
Set a personalised "correct form" or a gold-standard for a condition
Works with private practices, sports clubs and hospital rehab wards

Patients

Know you're doing it right, without a clinician in the room. No camera pointed at your living room.

Real-time green / amber / coral feedback on every rep
A wearable strap, not a webcam — private by design
Confidence to recover on schedule, at home

Why not just use video, or a fitness watch?

Sensors see what cameras and step-counters can't.

Video tools like Kemtai and Sword Health need a clear line of sight and raise privacy concerns at home. Consumer wearables like Apple Watch or Whoop track movement — but none of them can learn a prescribed exercise and grade its form.

Approach	Judges exercise form	Works unsupervised at home	No camera in the room
ExerWatch	Yes	Yes	Yes
Self-reported diaries / apps	— no verification	Yes	Yes
Video-based coaching (e.g. Kemtai, Sword Health)	Yes, angle-dependent	Needs clear sightline	Camera required
Consumer wearables (Apple Watch, Garmin, Whoop)	Not built for this	Yes	Yes

Traction

Early, and already in the clinic.

ExerWatch is pre-launch — currently piloting with real physios and real patients ahead of a 2026 launch.

Hospital pilot

Major private hospital, Melbourne

Piloting exercise adherence and form monitoring for patients recovering from knee surgery in the rehabilitation ward.

Physio pilot

Private physiotherapists, real patients

Physios comparing ExerWatch's detection and UI against their current technology, in daily practice.

Accelerator

MedTech Actuator, Cohort 9

Refining ExerWatch's pathway to market as part of a leading medtech accelerator programme.

The team

Built by the researchers who found the gap.

ExerWatch grew out of University of Melbourne PhD research into AI-driven exercise detection, done in collaboration with practising physiotherapists.

Dr Mahtab Mirmomeni

Founder & CEO

PhD in AI for remote exercise monitoring. 20 years in tech leadership, including global roles at IBM Research.

Dr Gabriele Marini

Senior Software Engineer

PhD in human-computer interaction, experienced in monitoring patients via wearable sensors.

Advisors

A/Prof. Mark Merolli

Physiotherapy & digital health

Associate Professor of Physiotherapy at the University of Melbourne, practising physiotherapist and digital health innovator.

Dr Richard Lunz

Rural health & telemedicine

Medical doctor and telemedicine expert advising on clinical rollout.

Launching 2026

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Early access for physiotherapists, clinics and patients — plus updates as we roll out from our Melbourne pilots.

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