Evidence map›Paper›PMID 41263249›Full record

ArticleDisability and rehabilitation. Assistive technology2026

Re-imagining sensory substitution through gestural control: Point-To-Tell 2.

Ligao Ruan, Giles Hamilton-Fletcher, Mahya Beheshti, Todd E Hudson, Maurizio Porfiri, John-Ross Rizzo

Abstract read
In one paragraph

Article in Disability and rehabilitation. Assistive technology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Ligao RuanDepartment of Mechanical and Aerospace Engineering, NYU Tandon School of Engineering, Brooklyn, NY, USA.
Giles Hamilton-FletcherDepartment of Rehabilitation Medicine, NYU Grossman School of Medicine, New York, NY, USA.
Mahya BeheshtiDepartment of Mechanical and Aerospace Engineering, NYU Tandon School of Engineering, Brooklyn, NY, USA.
Todd E HudsonDepartment of Rehabilitation Medicine, NYU Grossman School of Medicine, New York, NY, USA.
Maurizio PorfiriDepartment of Mechanical and Aerospace Engineering, NYU Tandon School of Engineering, Brooklyn, NY, USA.
John-Ross RizzoDepartment of Mechanical and Aerospace Engineering, NYU Tandon School of Engineering, Brooklyn, NY, USA.

Funding

Addressing Ableism through Accommodations for Blindness and Low vision to achieve Equity (AAABLE) in HealthcareR01EY036667 · NEI · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI Megan A Morris, John Ross Rizzo · 2024 to 2026
$2.2M
VIS4ION (Visually Impaired Smart Service System for Spatial Intelligence and Onboard Navigation) R33EY033689 · NEI · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI RIZZO, JOHN ROSS, VEDANTHAN, RAJESH · 2023 to 2025
$773k
NEI NIH HHS R01 EY036667NEI NIH HHS R33 EY033689
6 · The paper itself

Abstract

aimSensory substitution devices (SSDs) can convert environmental information into an accessible format for people who are blind or have low vision (pBLV). Yet, current SSDs often passively deliver all of the information available with limited user control, potentially leading to confusion and/or cognitive overload. To address this issue, this work proposes a selective, gesture-controlled system intended to improve information relevance and reduce cognitive overload.

methodsWe present Point-To-Tell 2, a system that enables pBLV to privately and efficiently select which information to convey through simple pointing-based gestural control. By integrating a monocular camera with AI-driven pipelines for depth estimation, hand pose tracking, and object detection/segmentation, the system identifies the users' 3D pointing direction and announces the names and distances of objects as they are pointed at, thereby connecting an object's spatial position and identity through hand proprioception.

resultsValidation tests in controlled indoor environments show high hand pose tracking accuracy, ensuring reliable ray-casting and object selection despite declining object recognition at longer distances. Distance estimates are stable at close range, though a systematic bias is present.

conclusionThis work introduces and technically validates an assistive system designed to improve the usability of assistive technologies by focusing system feedback-potentially reducing users' cognitive load and enhancing their spatial comprehension by leveraging concurrent hand proprioception. Future work will involve user testing and expanding system features to further enhance its practicality across more diverse scenarios.

Indexed as

BlindnessGesturesPersons with Visual DisabilitiesSelf-Help DevicesSensory AidsHumansIntelligent SystemsProprioceptionUser-Computer InterfaceAssistive technologyhuman–computer interactionobject detectionsensory substitutionvisual impairment

Identifiers

PMID41263249
PMCPMC12767285

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.