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    • Home
    • Exercises & Games
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    • The Team
    • Testimonials
    • What's new
    • Contact us
    • Privacy Policy
    • Sustainability
ai Rehab Ltd
  • Home
  • Exercises & Games
  • About us
  • The Team
  • Testimonials
  • What's new
  • Contact us
  • Privacy Policy
  • Sustainability

About us

AI Rehab is a digital rehabilitation company focused on one thing: making home knee-replacement recovery measurable.

Slider® is our patented at-home rehabilitation device and app for use before and after knee replacement surgery. It captures force and motion during prescribed exercises, giving patients immediate feedback and giving clinicians objective data on performance, progress, and recovery at home.

Most home rehabilitation still relies heavily on self-report, generic exercise content, and delayed follow-up. AI Rehab is building a better model: objective exercise measurement, remote clinical visibility, and earlier identification of patients who may need intervention.

Our starting point is the perioperative knee pathway, where adherence, recovery quality, and timely oversight matter. Our longer-term goal is to build a measurement-led musculoskeletal rehabilitation platform that helps providers improve outcomes and use clinical resources more efficiently.


Published early evidence in home knee rehabilitation, including usability, early postoperative outcome signals, and remote-monitoring research.

1.  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

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

DOI: 10.2196/48055

2.  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

3.  Kinetic Pattern Recognition in Home-Based Knee Rehabilitation Using Machine Learning Clustering Methods on the Slider Digital Physiotherapy Device: Prospective Observational Study, Twumasi C, 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

4.  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

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