All projects

Confidential (healthcare) · Healthcare

Full-stack AI platform for adaptive rehabilitation.

Private deployment, client project

Category

AI

Year

2024

Capabilities

AI, Full-Stack

Industry

Healthcare

AI Physiotherapy Assistant on a laptop
AI Physiotherapy Assistant on a phone

The problem

The rehabilitation journey was fragmented across manual intake, movement assessment, generic exercise plans and infrequent follow-up. Patients had little guidance between supervised sessions, and plans did not respond quickly to performance.

Our approach

We built the journey around an intake agent, guided movement assessment and automatic exercise plan generation. Daily logs drive plan progression or regression, while uploaded exercise videos receive AI feedback and injury articles inform future plans.

Inside the product

More than one screen.

3 more screens from AI Physiotherapy Assistant, captured at device size.

AI Physiotherapy Assistant: Movement assessment on a laptop

Movement assessment

Pose analysis on an uploaded clip, with joint angles and form feedback.

AI Physiotherapy Assistant: Eight-week plan on a laptop

Eight-week plan

Phases, this week’s sessions and every adaptation with its reason.

AI Physiotherapy Assistant: Clinician view on a laptop

Clinician view

Patients by attention needed and AI plan changes waiting for approval.

On the phone

AI Physiotherapy Assistant: Home on a phone

Home

AI Physiotherapy Assistant: Movement assessment on a phone

Movement assessment

AI Physiotherapy Assistant: Eight-week plan on a phone

Eight-week plan

AI Physiotherapy Assistant: Clinician view on a phone

Clinician view

How it is built

Architecture

A React frontend connects to a Python and FastAPI backend. LangChain coordinates intake, assessment context and plan generation, with OpenAI producing adaptive guidance. Video uploads feed the form-analysis workflow, and uploaded injury articles provide source material for plan generation.

Key features

Intake agent starting the patient journey
Movement assessment with instructional videos and tutorials
Automatic exercise plan generation
Daily logging with automatic plan progression or regression
Uploaded-video form analysis with AI feedback
Plan generation informed by uploaded injury articles

Challenges & solutions

Where it got hard.

Challenge

Static exercise plans could not respond when a patient’s daily performance improved or declined.

Solution

Connected daily logs to progression and regression rules so the plan adapts automatically instead of waiting for manual review.

Challenge

Plan generation needed injury-specific context rather than relying on generic model knowledge.

Solution

Made uploaded articles on common injuries available to the generation workflow so recommendations can use relevant source material.

Results

What shipping it changed.

90%+accuracy on AI-assisted movement and form assessment.

Daily plan progression and regression automated from patient performance.

Stack

  • Frontend

    • React
  • Backend

    • Python
    • FastAPI
  • AI

    • LangChain
    • OpenAI

Let's talk

We can usually tell within one call whether the approach above transfers to your problem, and what would need to change.