A Smart Service System for Spatial Intelligence and Onboard Navigation for Individuals with Visual Impairment (VIS4ION Thailand): study protocol of a randomized controlled trial of visually impaired students at the Ratchasuda College, Thailand

Abstract

Background: Blind/low vision (BLV) severely limits information about our three-dimensional world, leading to poor spatial cognition and impaired navigation. BLV engenders mobility losses, debility, illness, and premature mortality. These mobility losses have been associated with unemployment and severe compromises in quality of life. VI not only eviscerates mobility and safety but also, creates barriers to inclusive higher education. Although true in almost every high-income country, these startling facts are even more severe in low- and middle-income countries, such as Thailand. We aim to use VIS⁴ION (Visually Impaired Smart Service System for Spatial Intelligence and Onboard Navigation), an advanced wearable technology, to enable real-time access to microservices, providing a potential solution to close this gap and deliver consistent and reliable access to critical spatial information needed for mobility and orientation during navigation.

Methods: We are leveraging 3D reconstruction and semantic segmentation techniques to create a digital twin of the campus that houses Mahidol University's disability college. We will do cross-over randomization, and two groups of randomized VI students will deploy this augmented platform in two phases: a passive phase, during which the wearable will only record location, and an active phase, in which end users receive orientation cueing during location recording. A group will perform the active phase first, then the passive, and the other group will experiment reciprocally. We will assess for acceptability, appropriateness, and feasibility, focusing on experiences with VIS⁴ION. In addition, we will test another cohort of students for navigational, health, and well-being improvements, comparing weeks 1 to 4. We will also conduct a process evaluation according to the Saunders Framework. Finally, we will extend our computer vision and digital twinning technique to a 12-block spatial grid in Bangkok, providing aid in a more complex environment.

Discussion: Although electronic navigation aids seem like an attractive solution, there are several barriers to their use; chief among them is their dependence on either environmental (sensor-based) infrastructure or WiFi/cell "connectivity" infrastructure or both. These barriers limit their widespread adoption, particularly in low-and-middle-income countries. Here we propose a navigation solution that operates independently of both environmental and Wi-Fi/cell infrastructure. We predict the proposed platform supports spatial cognition in BLV populations, augmenting personal freedom and agency, and promoting health and well-being.

Trial registration: ClinicalTrials.gov under the identifier: NCT03174314, Registered 2017.06.02.

Keywords: Accessibility; Adaptive mobility device; Assistive technology; Blind/low vision; Low- and/or middle-income countries; Navigation; Visual impairment.

Fig. 1

(Top) a simulated view of a scene decomposed into capture fields that spatiotopically correspond to actuators in the haptic interface; (bottom) color-coded depiction demonstrating the scene decomposed into a segmented grid for belt-based vibratory warnings of various threat levels based on proximity and spatial position (note: 12 tactors correspond to 12 capture fields)

Fig. 2

Aerial map of Ratchasuda College (RC) at Mahidol University. A route between two on-campus locations is delineated

Fig. 3

Overview of a stereotypical route that may be navigated by a VI end user in Bangkok, using VIS⁴ION with expanded location microservices

Fig. 4

Correlations between ground truth positions and those computed from Pos-Net and Loc-Net (left) and corresponding 2D errors (right)

Fig. 5

2D posterior distributions over differences ($\mathrm{\Delta }$) and sums ($\mathrm{\Sigma }$) of the two poisson rate parameters ($\varsigma$), separated along the $\mathrm{\Delta }=0$ axis. Marginalizing over this 2D posterior either along the $\mathrm{\Delta }=0$ axis $\left(M_{\mathrm{\Delta }=0}\right)$, or for all portions of the posterior that exclude the $\mathrm{\Delta }=0$ axis $\left(M_{\mathrm{\Delta }\ne 0}\right)$, underlie the model comparison between the equal rates $\left(M_{\mathrm{\Delta }=0}\right)$ and unequal-rate $\left(M_{\mathrm{\Delta }\ne 0}\right)$ models