RehabOS combines clinical data, biomechanical sensor measurements, and machine learning to predict patient recovery, personalise treatment, and automate administration across every specialty and site.
Rehabilitation is data-rich, outcome-variable, and clinician-intensive. Every patient follows a different recovery curve. AI closes the gap between what data exists and what clinicians can act on.
Problem
A 67-year-old post-stroke patient and a 42-year-old post-ACL patient both need plans — but their trajectories, risks, and optimal protocols are fundamentally different. Rule-based software fails here. Pattern-matching AI thrives.
Opportunity
Every discharge summary, FIM score, gait measurement, and session note is a training signal. RehabOS uses similarity matching across historical patient cohorts to predict what will work — before the clinician commits to a protocol.
Clinical value
The more patients go through RehabOS, the better its predictions become. An isolated clinic has 500 stroke cases. RehabOS has 100,000 — matched by age, comorbidity, diagnosis subtype, and treatment modality.
Clinician time
An experienced physio takes 45–90 minutes to construct a comprehensive ICF-aligned therapy plan. RehabOS generates one in under 5 minutes — with confidence scoring, contraindication flags, and home programme — for the clinician to review and approve.
Administrative burden
Scheduling, documentation, billing coding, MDT coordination, and compliance reporting account for the majority of non-clinical time. RehabOS automates each of these — freeing clinicians to treat and managers to manage, not administrate.
ROI & compliance
For health ministries, AI in rehab is not just about one patient — it's about understanding which interventions produce the best outcomes across a population, how to allocate beds and resources, and how to demonstrate WHO and ICF compliance at audit.
RehabOS processes every step of the patient journey. The clinician reviews and approves. The AI handles the computation, prediction, and documentation.
TPS — Therapy Planning System
Steps 1–5
Diagnosis → modality → patient data → ML prediction → outcome display. Fully AI-driven clinical decision support.
RMS — Rehab Management System
Steps 6–7
Plan execution, scheduling, MDT coordination, compliance documentation, and discharge reporting. AI-automated administration.
Common Shell — RehabOS
All steps
TPS and RMS share one patient record, one identity, one AI engine. No silos. No re-entry. One operating system.
This is not a rule engine. It is a trained ensemble model that learns from historical rehabilitation outcomes, matched to the current patient by diagnosis, age, biomechanics, and treatment modality.
The system captures age, gender, diagnosis subtype, treatment duration, initial stance and swing phase percentages, walking velocity, cadence, stride length, and cycle duration. These become the input feature vector for the ML model.
Raw inputs are normalised, missing values imputed using population averages by diagnosis cohort, and engineered features generated — including functional deficit indices, recovery velocity proxies, and comorbidity interaction terms.
The model retrieves the k nearest historical patients — matched by diagnosis, age band, treatment modality, and initial gait profile — and weights their outcomes to form a prior. This is the core of the prediction: learning from patients who looked like this one.
Prediction outputs are generated by a stacked ensemble of Linear Regression (baseline), Random Forest (non-linear interactions), LightGBM (gradient-boosted learning), and XGBoost (high-performance boosting). Outputs are blended for maximum accuracy.
Predicted outcomes are mapped back to ICF activity and participation goals. The system generates a structured therapy plan with session frequency, modality selection, goal milestones, and a 12-week recovery projection — ready for MDT review in under 5 minutes.
Predicted gait parameters — Week 12 vs baseline
Model ensemble confidence
The clinical is only half the story. RehabOS applies the same intelligence to scheduling, billing, MDT coordination, and compliance analytics - eliminating the administrative overhead that consumes 40–48% of rehab facility operating cost.
Scheduling
RehabOS schedules beds, treatment slots, and equipment across the whole facility — balancing therapist availability, patient intensity prescriptions, and MDT dependencies automatically. Cancellations backfill themselves; conflicts surface before they happen, not after.
Documentation
Structured session notes, progress summaries, and MDT case presentations are drafted from therapist input and device data — in the facility's own templates. Clinicians review and sign; they no longer type from scratch after every session.
Billing
Every documented session maps to the correct tariff and procedure codes as it happens. Claims are assembled with complete supporting evidence, cutting rejections from missing documentation and capturing charges that manual coding routinely leaves behind.
Compliance
Outcome measures, MDT conference records, and programme evaluation data accumulate in audit-ready form as a by-product of daily work. When accreditation or ministry reporting comes due, the evidence pack already exists.
The ML engine is not a generic model. Each diagnosis has its own feature set, training cohort, and outcome targets — specific to the biomechanics, treatment modalities, and recovery trajectory of that condition.
Neurological · Stroke / TBI
Musculoskeletal · Post-Surgery / Sports
Cardiac & Pulmonary
XGBoost
94.2%
Primary boosting model — gait prediction
LightGBM
93.1%
Fast gradient boosting — large cohort matching
Random Forest
89.7%
Non-linear interactions — comorbidity patterns
Ensemble blend
92%
Blended output — clinical plan confidence score
Rehab Software is an AI-powered rehabilitation platform that makes recovery intelligent, measurable, and accessible. Developed by clinicians and technology experts, it streamlines therapy planning, operational workflows, and analytics through a flexible subscription model. The platform is designed for rehabilitation clinics, hospital groups, enterprise healthcare organizations, and Ministries of Health.
WHO ICD-11 | ICHI Compliant | CARF Accreditation policy | GDPR compliant
World’s first rehabilitation software fully compliant with WHO & CARF
© 2026 STRATECH VENTURES PRIVATE LIMITED. All rights reserved. Rehab Software is a product of STRATECH VENTURES.
