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Making rehabilitation smarter, simpler, and more accessible

Our mission is to improve the way patients complete rehab at home by combining guided exercise, interactive technology, and remote progress tracking.

Our Features

What’s Our Speciality

AI Rehab was created to improve the way patients complete rehabilitation at home. Traditional physiotherapy is often difficult to monitor once a patient leaves the clinic, leaving clinicians with limited visibility and patients with the challenge of staying motivated on their own.

Our platform bridges that gap by combining guided exercises, interactive games, and remote progress tracking into one connected rehabilitation experience.

By making home-based rehabilitation easier to follow and more engaging to complete, AI Rehab helps patients stay consistent while giving healthcare professionals clearer insight into their recovery journey.

Guided home rehabilitation

Helping patients complete structured exercises safely and consistently from home.

Patient engagement

Using interactive games to make rehabilitation more motivating and less repetitive.

Remote monitoring

Remote exercise review — allowing authorised healthcare professionals to review exercise participation and progress trends between appointments

Clinical visibility

Exercise activity visibility — providing supplementary information about recorded movement, exercise activity and progress trends

Scalable care delivery

Supporting healthcare providers with a more efficient way to manage rehabilitation beyond the clinic.

40+ Years Of Experience

Our Mission

Our mission is to make rehabilitation more accessible, engaging, and trackable.

We believe patients should feel supported throughout their recovery, not just during appointments. By using smart technology and recording exercise participation and progress trends so healthcare professionals can review home exercise activity between appointments.

For healthcare providers, this means better visibility of patient progress. For patients, it means a more motivating and confidence-building recovery experience.

Leadership Team

Meet Our Expert Team and Advisory Board

Shameem Sampath MD FRCS

Founder and CEO
Visiting Professor Manchester Metropolitan
Oxford and Harvard trained
Over 2000 knee replacements

Mikail Aktas MD MRes (First Class) MRCS

Business Lead
Medical doctor
Imperial College

Professor Mohamed Medhat Gaber 

PhD in AI (Monash University)

250+ AI publications with ~14,000 citations

Top 1% in AI and Image Processing (Stanford University/Elsevier)

Mark Ghee HPC , Grad Dip Phys, AACP

Chartered Physiotherapist with over 20 years experience

 

 

 

Szymon Manduk

MBA, MSc
Software Engineer
20+ years experience

Claire McGarvey

BSc
Neuroscientist
Fund raising and Investor Relations

Mark Seed

Patient advocate
Previous multiple knee injuries and surgery

Publications we feature in

Research notice: These publications report research studies and, in some cases, prototype or investigational analyses. Publication titles and study outcomes do not describe additional measuring functions of the currently marketed Slider device. Slider records heel displacement and calculates an estimated knee range-of-motion value for exercise feedback and progress tracking. It does not directly measure joint angle or muscle strength, diagnose complications or recommend treatment changes.

A Device for Prehabilitation of Total Knee Replacement Surgery (Slider): Usability Study

Islam R, Gooch D, Karlakki S, Price B

JMIR Form Res 2023;7:e48055

https://formative.jmir.org/2023/1/e48055

DOI: 10.2196/48055

QUIT: Quadriceps Inhibition Trends after Knee Arthroplasty, Sampath SACM, Aktas M, Presented at the 24th Annual Meeting of the International Society for Computer Assisted Orthopaedic Surgery (CAOS 2024).

Published in EPiC Series in Health Sciences, Vol. 7, pp. 197–201. DOI:

10.29007/ltm7 https://easychair.org/publications/paper/dPPg

Kinetic Pattern Recognition in Home-Based Knee Rehabilitation Using Machine Learning Clustering Methods on the Slider Digital Physiotherapy Device

Prospective Observational Study,  Aktas M, Santoni N, JMIR Formative Research. March 18, 2025; 9:e69150. DOI: 10.2196/69150 | PMID: 40100262 | PMCID: PMC11962318

https://pubmed.ncbi.nlm.nih.gov/40100262

Comparison of Clinical Outcomes Between the Slider Device and Standard Physiotherapy for Knee Osteoarthritis Patients Undergoing Knee Replacement Surgery

A Pilot Study, McDonald S, Lim JW, Shanmugan K, Johnston AT, Bidwell JP,Podium Presentation at CAOS 2025, Davos, Switzerland., Affiliations: Norfolk & Norwich University Hospital; Woodend Hospital, NHS Grampian,

https://easychair.org/publications/paper/HHJd

Supporting guided home knee rehabilitation and progress tracking

Contact Us

contact@airehab.com