Digital Twin Smart Educational Platform for Visually Impaired Navigation Training
8 juni 2026 uppdaterad av: Abdellah Ibrahim Mohammed Elfeky, King Salman Center for Disability Research
A Digital Twin Smart Educational Platform for Simulating Physical Obstacles and Safe Navigation Training for the Saudi Visually Impaired
This study evaluates a novel digital twin smart educational platform designed to train visually impaired individuals on safe navigation in Saudi urban environments.
Independent mobility is challenging for visually impaired people due to dynamic hazards and architectural changes.
This interventional study utilizes an advanced computer simulation (digital twin) modeled after real streets in Jeddah, Saudi Arabia.
Participants are randomly assigned to either the experimental group (receiving training via the adaptive digital twin platform with 3D spatial audio and wearable haptic feedback) or the control group (receiving traditional orientation and mobility instruction).
The training consists of 10 structured sessions over 5 weeks.
The primary goal is to determine…
Studieöversikt
Status
Avslutad
Betingelser
Intervention / Behandling
Detaljerad beskrivning
The purpose of this study is to examine the engineering validity and pedagogical efficacy of the Adaptive Multi-modal Reality Learning Environment (AMRLE) for visually impaired orientation and mobility (O&M) training.
The platform features a three-tier architecture: Data Acquisition Tier: Utilizing Mobile Laser Scanning (MLS) and LiDAR point clouds to generate high-fidelity 3D environments compliant with the Saudi Building Code (SBC 201) universal access standards.
Processing Tier: Running a custom 3D simulation engine embedded with an AI-driven adaptive algorithm.
The algorithm dynamically adjusts environmental complexity and obstacle density based on the user's real-time collision metrics and path deviation speeds.
Human Interaction Tier: Delivering sensory...
Studietyp
Interventionell
Inskrivning (Faktisk)
30
Fas
- Inte tillämpbar
Kontakter och platser
Det här avsnittet innehåller kontaktuppgifter för dem som genomför studien och information om var denna studie genomförs.
Studieorter
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Cairo, Egypten
- Special Education Resource Rooms
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Deltagandekriterier
Forskare letar efter personer som passar en viss beskrivning, så kallade behörighetskriterier. Några exempel på dessa kriterier är en persons allmänna hälsotillstånd eller tidigare behandlingar.
Urvalskriterier
Åldrar som är berättigade till studier
- Vuxen
Tar emot friska volontärer
Nej
Beskrivning
Inclusion Criteria:
- Certified clinical diagnosis of severe visual impairment or legal blindness.
- Aged between 18 and 60 years old.
- Physical ability to walk independently and unassisted for at least 15 continuous minutes.
- Cognitive and neurological competence to comprehend and interact with multi-modal software telemetry.
- Baseline proficiency in using accessibility screen-reader features on mobile devices.
Exclusion Criteria:
- Profound sensorineural hearing loss or auditory dysfunction that prevents 3D spatial binaural sound localization.
- Active upper or lower-limb motor neuropathies that disrupt the perception of haptic micro-actuator vibrations.
- History of severe vestibular disorders, severe motion sickness, or inner ear syndromes causing chronic dizziness.
- Current participation in concurrent physical orientation and mobility clinical trials.
Studieplan
Det här avsnittet ger detaljer om studieplanen, inklusive hur studien är utformad och vad studien mäter.
Hur är studien utformad?
Designdetaljer
- Primärt syfte: Stödjande vård
- Tilldelning: Randomiserad
- Interventionsmodell: Parallellt uppdrag
- Maskning: Dubbel
Vapen och interventioner
Deltagargrupp / Arm |
Intervention / Behandling |
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Experimentell: Experimental: AMRLE Group
Participants assigned to this group will undergo orientation and mobility (O&M) training within the Adaptive Multi-modal Reality Learning Environment (AMRLE) powered by a dynamic Digital Twin simulation engine.
Over a 5-week curriculum comprising 10 structured sessions (25 minutes per session), trainees interact with virtual replicas of real-world Saudi urban layouts.
The system delivers non-visual feedback using low-latency 3D spatial binaural audio and localized directional haptic/vibrotactile device telemetry.
An AI-driven optimization model automatically scales environmental complexity and obstacle generation based on real-time participant performance loops.
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A structured 10-session orientation and mobility (O&M) curriculum distributed over 5 weeks (2 sessions/week, 25 minutes/session).
The intervention leverages a dynamic digital twin simulation engine of Saudi urban spaces to proactively train visually impaired users on hazard mitigation.
Trainees navigate via non-visual multi-modal feedback loops: 3D spatialized binaural audio (HRTF) pings indicating structural pathways, combined with directional haptic/vibrotactile vest telemetry for real-time proximity boundaries.
An AI optimization model continuously adjusts environmental complexity and obstacle generation (static, semi-dynamic, and crowded scenarios) matching the real-time collision metrics of the participant to prevent learning plateaus and optimize cognitive mapping.
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Aktiv komparator: Active Control: Conventional O&M Group
Participants assigned to this control group will undergo standard, conventional orientation and mobility (O&M) rehabilitation instructions.
Over a 5-week period consisting of 10 structured training sessions (25 minutes per session), trainees practice navigation along fixed real-world paths using traditional white canes.
The instruction relies entirely on conventional tactile maps, physical paving cues, and static verbal orientation scripts provided by an O&M instructor.
No virtual reality simulators, adaptive AI algorithms, or high-fidelity digital twin interventions are utilized.
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A structured 10-session orientation and mobility (O&M) curriculum distributed over 5 weeks (2 sessions/week, 25 minutes/session).
The intervention leverages a dynamic digital twin simulation engine of Saudi urban spaces to proactively train visually impaired users on hazard mitigation.
Trainees navigate via non-visual multi-modal feedback loops: 3D spatialized binaural audio (HRTF) pings indicating structural pathways, combined with directional haptic/vibrotactile vest telemetry for real-time proximity boundaries.
An AI optimization model continuously adjusts environmental complexity and obstacle generation (static, semi-dynamic, and crowded scenarios) matching the real-time collision metrics of the participant to prevent learning plateaus and optimize cognitive mapping.
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Vad mäter studien?
Primära resultatmått
Resultatmått |
Åtgärdsbeskrivning |
Tidsram |
|---|---|---|
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Real-world Collision Rate (RCR)
Tidsram: At the completion of the 10-session training curriculum (Week 5).
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The cumulative number of physical obstacle impacts or structural contact errors recorded per 100 meters during the final real-world post-test field navigation trial.
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At the completion of the 10-session training curriculum (Week 5).
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Samarbetspartners och utredare
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Studieavstämningsdatum
Dessa datum spårar framstegen för inlämningar av studieposter och sammanfattande resultat till ClinicalTrials.gov. Studieposter och rapporterade resultat granskas av National Library of Medicine (NLM) för att säkerställa att de uppfyller specifika kvalitetskontrollstandarder innan de publiceras på den offentliga webbplatsen.
Studera stora datum
Studiestart (Faktisk)
7 januari 2026
Primärt slutförande (Faktisk)
29 april 2026
Avslutad studie (Faktisk)
19 maj 2026
Studieregistreringsdatum
Först inskickad
4 juni 2026
Först inskickad som uppfyllde QC-kriterierna
8 juni 2026
Första postat (Faktisk)
11 juni 2026
Uppdateringar av studier
Senaste uppdatering publicerad (Faktisk)
11 juni 2026
Senaste inskickade uppdateringen som uppfyllde QC-kriterierna
8 juni 2026
Senast verifierad
1 juni 2026
Mer information
Termer relaterade till denna studie
Nyckelord
Ytterligare relevanta MeSH-villkor
Andra studie-ID-nummer
- KSRG-2026-053-3
- KSRG-2026-053 (King Salman center for Disability Research)
Plan för individuella deltagardata (IPD)
Planerar du att dela individuella deltagardata (IPD)?
JA
Läkemedels- och apparatinformation, studiedokument
Studerar en amerikansk FDA-reglerad läkemedelsprodukt
Nej
Studerar en amerikansk FDA-reglerad produktprodukt
Nej
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