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Digital Twin Smart Educational Platform for Visually Impaired Navigation Training

2026年6月8日 更新者：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…

研究概览

地位

完全的

条件

干预/治疗

详细说明

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...

研究类型

介入性

注册 (实际的)

30

阶段

  • 不适用

联系人和位置

本节提供了进行研究的人员的详细联系信息，以及有关进行该研究的地点的信息。

学习地点

  • 埃及
      • Cairo、埃及
        • Special Education Resource Rooms

参与标准

研究人员寻找符合特定描述的人，称为资格标准。这些标准的一些例子是一个人的一般健康状况或先前的治疗。

资格标准

适合学习的年龄

  • 成人

接受健康志愿者

不

描述

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.

学习计划

本节提供研究计划的详细信息，包括研究的设计方式和研究的衡量标准。

研究是如何设计的？

设计细节

  • 主要用途：支持治疗
  • 分配：随机化
  • 介入模型：并行分配
  • 屏蔽：双倍的

武器和干预

参与者组/臂
干预/治疗
实验性的：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.
行为的：Adaptive Multi-modal Digital Twin Navigation Training
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.
有源比较器：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.
行为的：Adaptive Multi-modal Digital Twin Navigation Training
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.

研究衡量的是什么？

主要结果指标

结果测量
措施说明
大体时间
Real-world Collision Rate (RCR)
大体时间：At the completion of the 10-session training curriculum (Week 5).
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.
At the completion of the 10-session training curriculum (Week 5).

合作者和调查者

在这里您可以找到参与这项研究的人员和组织。

赞助

King Salman Center for Disability Research

研究记录日期

这些日期跟踪向 ClinicalTrials.gov 提交研究记录和摘要结果的进度。研究记录和报告的结果由国家医学图书馆 (NLM) 审查，以确保它们在发布到公共网站之前符合特定的质量控制标准。

研究主要日期

学习开始 (实际的)

2026年1月7日

初级完成 (实际的)

2026年4月29日

研究完成 (实际的)

2026年5月19日

研究注册日期

首次提交

2026年6月4日

首先提交符合 QC 标准的

2026年6月8日

首次发布 (实际的)

2026年6月11日

研究记录更新

最后更新发布 (实际的)

2026年6月11日

上次提交的符合 QC 标准的更新

2026年6月8日

最后验证

2026年6月1日

更多信息

与本研究相关的术语

关键字

其他相关的 MeSH 术语

其他研究编号

  • KSRG-2026-053-3
  • KSRG-2026-053 (King Salman center for Disability Research)

计划个人参与者数据 (IPD)

计划共享个人参与者数据 (IPD)？

是的

药物和器械信息、研究文件

研究美国 FDA 监管的药品

不

研究美国 FDA 监管的设备产品

不

此信息直接从 clinicaltrials.gov 网站检索，没有任何更改。如果您有任何更改、删除或更新研究详细信息的请求，请联系 register@clinicaltrials.gov. clinicaltrials.gov 上实施更改，我们的网站上也会自动更新.

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