Middleware-first · Device-agnostic architecture
Connected device layerLive
Robotic gait system
Lower limb · treadmill-based
Overground exoskeleton
Lower limb · ambulatory
RehabOS common shell
All device data flows into one AI patient record.
Ambient Device Sync

Every rehab device.
One intelligent
data layer.

RehabOS connects gait robotics, exoskeletons, brain-computer interfaces, wearable sensors, gait labs, bed monitors, and diagnostics — streaming real data into a single AI-powered clinical record. No manual transcription. No data silos. One operating system for the entire therapy floor.

Connected device layer API connected
Robotic gait system Lower limbStreaming
Overground exoskeleton AmbulatoryStreaming
Upper limb robot Arm / handActive
Gait analysis lab Force platesSyncing
EEG neurofeedback Cortical signalSyncing
Device types

6

Robotic gait, exoskeleton, upper limb robot, gait lab, EEG neurofeedback, bed/vitals monitor.

Common shell

1

All device data flows into one AI patient record — the RehabOS common shell.

Gait robotics Exoskeletons BCI / neurofeedback FES devices Gait labs IoT / wearables HL7 FHIR
RehabOS — Connected Devices, Every Workflow Covered

Why rehab technology changes outcomes

Devices produce data. Only connected devices produce outcomes.

The global robotic rehabilitation market reaches USD 9.47 billion by 2035. Every major rehab centre is investing in gait robotics, exoskeletons, and neurotech. The problem is not access to devices — it is that device data almost never reaches the patient's clinical record in a usable form.

01 · The device data problem

Devices generate data. Therapists retype it by hand.

A robotic gait system produces over 2,000 data points per minute of therapy. In most facilities, a therapist transcribes a handful of numbers into a paper sheet. The rest is lost. RehabOS captures everything — automatically, in real time, directly into the clinical record.

2,000+
data points per minute from a single gait robot session
02 · The AI data problem

AI can only predict outcomes from data it can see.

RehabOS's ML prediction engine needs biomechanical inputs — gait velocity, stance phase, swing phase, ROM, force output — to generate accurate recovery projections. Without device integration, the AI is working blind. With it, model confidence rises from 68% to 92%.

+24%
prediction accuracy gain with live device data vs clinical notes alone
03 · The compliance problem

Device-assisted sessions need ICHI-coded documentation.

Every robotic therapy session must be ICHI-coded at the point of delivery for WHO compliance and CARF accreditation. RehabOS assigns the correct ICHI intervention code automatically at session close — no manual coding, no end-of-day reconciliation.

0
manual coding steps per device-assisted session
04 · The therapist burden

Setting up, running, and documenting a device session takes 3 people.

Without integration, a robotic session requires: one therapist to set up the device, one to run it, and another to document in a separate system. RehabOS reduces this to one; the device streams to the record, the plan adjusts automatically, and the session note is pre-populated for review.

65%
reduction in per-session documentation burden with full device integration
05 · The outcome visibility problem

CEOs can't see device utilisation ROI without integration.

High-end robotics represents a major capital investment. Without integration, hospital leadership cannot see session volume, patient throughput, or equipment utilisation rates. RehabOS turns every device into a tracked, reportable asset on the executive dashboard.

USD 500K
average enterprise rehab robotics investment — now fully tracked in RehabOS
06 · The middleware gap

Every device manufacturer uses a different protocol.

Major rehabilitation device manufacturers use proprietary APIs, CSV exports, Bluetooth BLE, DICOM streams, and CAN bus. Most facilities run each device in complete isolation. RehabOS acts as the universal middleware layer — translating every format into a unified, AI-readable data stream.

20+
device manufacturers integrated or in active development
Clinical documentation

Every clinical workflow, covered

From the patient chart before the visit to the final code submitted, RehabOS supports every step of the clinical documentation journey.

Ambient Documentation

Captures the natural conversation between clinician and patient, structuring it into a clean clinical note without anyone touching a keyboard mid-session.

Dictation

Speak a session summary in plain language and get a structured, formatted note back in seconds — ready to review, edit, and sign off.

Coding

E/M and ICD-10 coding suggestions grounded in clinical documentation and AMA guidelines — with every final decision in the clinician's hands.

RehabOS — The automation continuum

From paper intake to full robotics

The automation continuum — zero manual intervention

RehabOS removes manual touchpoints at every stage of the patient journey — front desk, therapy floor, discharge. Each step feeds the next. Each device feeds the AI. The target: under 10% human intervention across the entire administrative and data-capture workflow.

  • Front desk check-in
  • Referral letters
  • Prescriptions
  • Clinical notes
  • Therapy robotics
  • Wearables
  • Gait labs
STEP 01

Visual registration

Facial ID or QR check-in. Zero paper at the front desk.

STEP 02

OCR intake

Referral letters and prescriptions → structured data instantly.

STEP 03

AI data structuring

Unstructured clinical text → ICD-11 coded, ICF-aligned record.

STEP 04

Clinical assessment

FIM, Barthel, DASH scores captured at point of care.

STEP 05

AI therapy planning

ICF plan generated in 5 minutes. The MDT approves, not constructs.

STEP 06

Device capture

Robotics, wearables, gait labs stream directly into the record.

STEP 07

Progress tracking

AI updates the recovery curve after every session, in real time.

STEP 08

Outcome analytics

WHO ICD-11 and CARF–MOH reports generated at discharge, automatically.

Coded records, no transcription
Live recovery curves
Discharge reports on demand
Manual intervention target across full episode, including device sessions < 10%
RehabOS — Device Categories
Device categories RehabOS connects

Six categories of world-leading
rehabilitation technology

RehabOS integrates with the world's leading rehabilitation devices across six technology categories — all streaming into one shared clinical record, all feeding the AI engine, all producing ICHI-coded documentation automatically.

RehabOS — Integration Architecture

How RehabOS connects every protocol, every device

Rehabilitation devices speak 12 different data languages. RehabOS acts as the universal middleware layer — translating proprietary APIs, DICOM streams, HL7 messages, Bluetooth BLE packets, and raw sensor data into a single, structured, AI-readable patient record.

1
Proprietary device API integration
RehabOS maintains native SDK integrations with major rehabilitation device manufacturers. Session data streams directly from device firmware to the RehabOS patient record without intermediary software, manual export, or data transformation by the clinical team.
Native SDKsReal-time streamingNo export step
2
HL7 FHIR R4 — hospital system integration
All therapy device sessions are mapped to HL7 FHIR Observation and Procedure resources and pushed to the hospital HIS in real time. ICHI intervention codes are assigned at session close and included in the FHIR message. Bidirectional — RehabOS also pulls patient demographics from the HIS automatically.
HL7 FHIR R4BidirectionalICHI auto-coded
3
DICOM — imaging, PACS & gait lab integration
Gait labs and diagnostic systems produce DICOM-compatible outputs — pressure maps, force vector images, motion capture renders. RehabOS pulls DICOM studies into the patient record, making biomechanical imaging available to the MDT alongside the clinical record without switching systems.
DICOM pullPACS viewerGait lab render
4
Bluetooth BLE & wireless sensor ingestion
Wearable sensors communicate via Bluetooth Low Energy. The RehabOS device gateway — running on a tablet or bedside unit — bridges BLE sensor streams to the cloud patient record. No WiFi infrastructure changes required. Encrypted end-to-end with AES-256.
BLE gatewayTablet bridgeAES-256 encrypted
5
CSV / proprietary format normalisation
Some devices export only CSV or proprietary binary formats. RehabOS provides per-device parsers that normalise these exports into structured FHIR Observation resources within seconds — eliminating manual data entry while preserving full parameter granularity.
Per-device parsersAuto-normalisationFHIR conversion
6
Open API for new device onboarding
Any device manufacturer or rehab centre IT team can connect a new device using our open device integration API. Full documentation, sandbox environment, and integration certification programme available. New integrations typically validated in 4–8 weeks from API access request.
Open APISDK documentation4–8 wk onboarding
See how it works →
Live data flow — device to patient record
Robotic gait system
Kinematic output
Gait parameters · AI engine
Upper limb robot
Force / ROM sensors
Motor function record
EEG / BCI device
Neural signal stream
Cortical activity log
Gait lab / force plates
DICOM + CSV
Biomechanical baseline
FES device
Stimulation log
FES session record
Wearable sensor
BLE continuous
Activity & vitals stream
All above
Auto-normalised
AI prediction · 92% confidence
What happens automatically at session close
ICHI intervention code assigned — no manual coding
Session note pre-populated for clinician review
AI recovery curve updated with new data points
FHIR Observation pushed to hospital HIS
CARF evidence file updated — audit trail maintained
RehabOS — Supported devices
Connected device ecosystem

Supported devices —
live, certified, and in development

RehabOS maintains a growing catalogue of certified device integrations. The table covers confirmed live integrations, active development pipeline, and the open API programme for new devices.

Device category / typeRehab applicationData captured by RehabOSProtocolStatus
Treadmill robotic gait system
Lower limb · neurological
Stroke, SCI, TBI — body-weight supported gait trainingGait kinematics · torque · weight bearing · step count · assistance levelNative APILive
Overground exoskeleton
Lower limb · ambulatory
Stroke, SCI — real-world gait training with GaitCoach analyticsStep metrics · left/right symmetry · assistive force · GaitCoach scoresNative APILive
Full-arm neurorehabilitation robot
Upper limb · sensor-based
Post-stroke arm paresis, TBI upper limb — high-rep motor trainingROM · force · VR performance · assistance percentage · session complianceNative APILive
Five-finger hand rehabilitation robot
Hand / finger · robotics
Hand paresis — individual digit force and ROM rehabilitationIndividual finger force · passive/active ROM · spasticity grade · session logCSV → FHIRLive
Upper limb assessment system
Upper limb · biofeedback
Grip, wrist, and shoulder assessment and trainingGrip strength · ROM · wrist force profiles · task scores · tremor indexCSV → FHIRLive
Soft robotic ankle exosuit
Lower limb · FES + robotics
Post-stroke hemiparesis — plantarflexion and dorsiflexion assistAssist timing · walking speed · trial outcomes · session durationBluetoothLive
Assistance-as-needed arm robot
Upper limb · neuro · AAN
Neurological arm rehabilitation with real-time biofeedbackActive ROM · movement smoothness · velocity · error rate · assistance levelHL7 FHIRLive
Force distribution gait platform
Biomechanics · gait lab
Gait symmetry, COP, and balance assessmentCOP trajectory · gait symmetry · step width · temporal parameters · balance scoresDICOM / CSVLive
Anti-gravity unweighted treadmill
Gait · orthopaedic / neuro
Early weight-bearing gait rehabilitation post-surgery and neuroBody weight % · walking speed · session time · gait mechanicsCSV → FHIRLive
Wireless FES foot drop device
FES · foot drop · daily wear
Foot drop correction — stroke and MS — in clinic and homeStep detection events · stimulation parameters · daily wear time · compliance logBluetoothLive
Research-grade IMU wearable
Wearable · motion · IoT
Free-living activity monitoring and biomechanical assessmentAcceleration · angular velocity · orientation · activity classification · cadenceBLE gatewayLive
Ward vitals monitor
IoT · ward · inpatient
Continuous inpatient vitals monitoring with alarm integrationHR · SpO2 · BP · RR · ECG trend · alarm events · bedside time seriesHL7 v2 / FHIRLive
VR neurorehabilitation platform
BCI · VR · neurotech
VR-based motor rehabilitation with neural feedback integrationVR task scores · movement quality · engagement index · motor learning curvesREST APIIn dev
3D motion capture system
Biomechanics · gait lab
Gold-standard 3D kinematic and kinetic gait analysisFull 3D joint kinematics · kinetics · EMG · segment angles · gait cycle timingDICOM / C3DIn dev
Hybrid assistive limb
BCI · exoskeleton · neuro
Bioelectrical signal-driven exoskeleton for SCI rehabilitationBioelectrical signals · joint angle assist · walk training log · session metricsOpen APIIn dev
Wearable EEG / BCI system
BCI · EEG · neurofeedback
Motor imagery EEG training, neurofeedback, cortical monitoringEEG band power · motor imagery accuracy · P300 event · BCI trial outcomesOpen APIIn dev
Your device
Any category
Any rehabilitation technology — we build the parser with youAny structured parameter set agreed with your device teamOpen APIOpen programme
No devices match your search. Try a different term or filter.
RehabOS — Device integration

What device integration delivers

Rehab tech connected. Outcomes measured.

Connecting devices to RehabOS turns expensive rehabilitation equipment from isolated therapy tools into fully tracked, AI-powered, outcome-producing clinical assets — visible to clinicians, management, and compliance teams at the same time.

20+
Device integrations

Live or in active development across 6 device categories.

0
Manual steps

From device session end to ICD-coded clinical record update.

92%
AI confidence

ML prediction accuracy with full device data vs clinical notes alone.

USD 9.5B
Market by 2033

Rehab robotics market — RehabOS is the data intelligence layer.

CEO / COO

Every device is a tracked, reportable clinical asset — not just a cost line.

Investment decisions run on actual ROI, not anecdote. Four figures land in the executive dashboard for every machine on the floor.

Device utilisation
Patient throughput per machine
Outcome improvement per device type
Revenue per session
Executive demo

Rehab clinicians

The session note is written before you look up from the robot.

RehabOS pulls every parameter straight from the device — gait metrics, force outputs, assistance levels, VR performance scores. You review and approve. The recovery curve updates itself.

Pre-populated
GAITSymmetry index 0.87 — up 6% on last session.
FORCEPeak 142 N left / 158 N right, no drop-off.
PLANAssistance level 3 → 2, reassess in 2 weeks.
Clinical demo

IT / integration lead

One middleware layer. Every device. Every protocol.

No custom development per device. No per-integration maintenance. Connectors ship and stay maintained as part of the platform subscription — add a device, we add the connector.

HL7
DICOM
BLE
API / CSV
Technical integration docs

Rehab Software

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.

Platform & Scope Notification

Website content reflects RehabOS's vision and intended platform capabilities. All features, outcomes, and integrations described are indicative and subject to client-specific scope and mutually agreed SLAs and KRAs. No clinical outcome is assured unless expressly committed in a signed agreement.

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