Digital Twin Smart Educational Platform for Visually Impaired Navigation Training

King Salman Center for Disability Research30 enrolled

Overview

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…

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...

Study Type

INTERVENTIONAL

Allocation

RANDOMIZED

Purpose

SUPPORTIVE_CARE

Masking

DOUBLE

Enrollment

Conditions

Interventions

Adaptive Multi-modal Digital Twin Navigation TrainingBEHAVIORAL

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.

Eligibility

Sex: ALLMin age: 18 YearsMax age: 60 Years

Medical Language ↔ Plain English

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.

Digital Twin Smart Educational Platform for Visually Impaired Navigation Training

Overview

Conditions

Interventions

Eligibility

Locations (1)

Outcomes

Primary Outcomes