About us

Making clinical-grade movement assessment available to everyone

DigiTherapix is a deep tech digital health company built on a decade of R&D. We combine AI, computer vision, biomechanics and rehabilitation science to measure how well people move, using the devices they already have, so that objective movement assessment can become part of everyday care.

The team

The people behind DigiTherapix

DigiTherapix was founded by clinicians, scientists and engineers who have worked together for more than a decade where rehabilitation, AI and digital health meet. Between us we bring clinical research and practice, biomechanics and computer vision, healthcare innovation and commercial leadership. What unites us is a simple belief: everyone deserves care that is guided by objective measurement of how they move, wherever they live.

Our vision

A future where precision movement analysis is available to every healthcare professional and every patient, regardless of location or resources. Rehabilitation technology breaks free from specialist labs and expensive equipment, and personalised, data-driven care becomes the standard.

Our mission

To transform rehabilitation by giving healthcare professionals intelligent, evidence-based tools that improve clinical decisions, patient outcomes and care delivery. Every product is co-created with clinicians, researchers and people with lived experience.

For patients

Rehabilitation that fits into life

What DigiTherapix looks like for the people we're building it for.

DigiTherapix for patients · 1 min 16 s

What guides us

Our values

01

Patient first

Every feature and algorithm starts with one question: how does this improve a person's recovery and quality of life?

02

Evidence-based

Science guides what we build. Our methods are validated through clinical research and real-world testing.

03

Accessible to all

Quality care should not depend on postcode or equipment. Everyday devices remove the cost barrier.

04

Privacy and trust

Health data is personal. We design for privacy and security from the start.

05

Co-created

We build with clinicians, researchers and patients, so our tools fit real practice.

06

Relentless innovation

We bring the newest AI research into practical tools that clinicians can use today.

Science and validation

Built on a decade of research

Our methods have been developed over more than ten years of interdisciplinary research, evaluated with real-world patient groups, and published in peer-reviewed journals.

See our publications

  • Stroke
  • Parkinson's
  • Multiple sclerosis
  • MSK conditions
  • Total knee replacement
10+years of interdisciplinary research
5clinical populations in validation studies
6products on one movement engine
LiveMVP with active pilot partners and clinical studies

Funding and grants

Supported by Innovate UK ICURe Explore and NIHR-funded research collaborations, including OCTive and Knee4Life.

Clinical validation

Evaluated across complex, real-world patient groups, with peer-reviewed publications.

Pilots and product

Active pilot partners and ongoing clinical studies. Our MVP is live and designed for lab-grade biomechanical accuracy.

Publications

Peer-reviewed research behind the DigiTherapix movement engine.

  1. 2026JMIR Rehabilitation and Assistive TechnologiesJournal article

    Validity and reliability of the Track-UL algorithm compared with Kinovea software for measuring upper-limb functional range of motion in people after stroke

    Lazem H, Harris D, Hall A, Richards TC, Leveridge P, Mansoubi M, et al.

    Read the paper (opens in a new tab)
  2. 2025International Journal of StrokeConference abstract

    Markerless motion capture system (MediaPipe) for measuring upper limb range of motion in people with stroke

    Lazem H, Hall A, Mansoubi M, Harris D, Richards T, Xu X, et al.

    Abstract in print supplement
  3. 2024SensorsStudy protocol

    Knee4Life: empowering knee recovery after total knee replacement through digital health protocol

    Mansoubi M, Leveridge P, Smith M, Fox A, Massey G, Lamb SE, et al.

    Read the paper (opens in a new tab)
  4. 2023Clinical RehabilitationJournal article

    Accuracy of a computer vision system for estimating biomechanical measures of body function in axial spondyloarthropathy patients and healthy subjects

    Cronin NJ, Mansoubi M, Hannink E, Waller B, Dawes H.

    Read the paper (opens in a new tab)
  5. 2022Healthcare Technology LettersJournal article

    Validity and feasibility of remote measurement systems for functional movement and posture assessments in people with axial spondylarthritis

    Hannink E, Mansoubi M, Cronin N, Wilkins B, Najafi AA, Waller B, et al.

    Read the paper (opens in a new tab)