What if good rehabilitation didn't mean three hospital trips a week? It already doesn't, for 250+ patients a month.
NeuronFRAMES is an AI-assisted rehabilitation platform, computer vision, gamified therapy, sensor-based exercises, and speech tools, in clinical use at King Chulalongkorn Memorial Hospital across Physical, Occupational & Speech Therapy, delivering measurable outcomes in the clinic and at home.
β Improvement and cost figures are from pilot trials and field deployments. See the evidence.
Department of Physical Medicine and Rehabilitation: 250+ patients per month across Physical, Occupational, and Speech Therapy.
View partnership βNeuronFRAMES combines computer-vision pose detection, gamified exercises, sensor-based tasks, and speech therapy in one browser-based platform. At King Chulalongkorn Memorial Hospital it's used in Physical Therapy, Occupational Therapy, and Speech Therapy, for both inpatient and outpatient care, and continues at home.
It doesn't just track therapy; it lightens the load on everyone involved.
Sessions and metrics are logged automatically, far less paperwork. Therapists guide more patients with less repetitive supervision, and decide from objective data instead of memory and notes.
Much of the therapy happens at home: fewer hospital visits, less travel time and expense, less time off work for family. Engaging, family-supported therapy means steadier progress, too.
Shifting routine practice home means smoother throughput, lower cost per patient (β47% in pilot data), and the same staff and space serving more people, and reaching beyond the hospital walls.
Range, repetitions, form — captured automatically as the patient moves.
The site is split into focused pages: here's what's inside each one.
What NeuronFRAMES is, and how it actually works, clinic and home.
The results, the clinical use, and what changes for staff and patients.
Peer-reviewed work, the roadmap, the team, and answers to common questions.
Recognition for accessible rehabilitation technology.
A small team of researchers and engineers working hand-in-hand with rehabilitation clinicians, and the authors behind our peer-reviewed publications.
Leads the research direction and the work on interactive therapeutic systems presented at ACM/IEEE HRI 2025.
Connects the platform with clinical partners, coordinates hospital deployments, and works across system design, data, and product.
Builds the sensor integration and gamified interfaces, including the force-sensitive hand-rehabilitation work published with Springer.
Advises on AI-driven rehabilitation, biomechatronics, and collaborative robotics via the University of Agder partnership.
Supported by rehabilitation professionals at King Chulalongkorn Memorial Hospital, Burapha University Hospital, and Bangkok International Hospital, and academic partners at the University of Agder and Chulalongkorn University. More on the Research page β
2.6 billion people worldwide need rehabilitation, and most never get consistent care. Starting from Thailand's hospitals and communities, we're building toward a future where good rehab is affordable, engaging, and available wherever a patient is.