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Wayfinding Information Access System for People With Vision Loss

Wayfinding Information Access System for People With Vision Loss

Status
Completed
Phases
NA
Study type
Interventional
Source
ClinicalTrials.gov
Registry ID
NCT00829036
Enrollment
24
Registered
2009-01-26
Start date
2012-10-31
Completion date
2012-12-31
Last updated
2014-04-02

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Blindness

Keywords

Rehabilitation, Sensory Aid

Brief summary

The purpose of the project is to find out what kinds of information are most useful to visually impaired people when they are moving around indoors and what kinds of controls will make it easy for visually impaired people to control a device to help orient them to an unfamiliar indoor space.

Detailed description

The greatest mobility problems for people with severe visual impairment are caused by gaps in available information about the environment -- environmental cues needed for orienting to salient landmarks in the surrounding environment and for wayfinding. Such informational cues are of great import because persons with severe visual impairment can become hopelessly lost if they cannot keep track of where they are at any given moment as they move along. A newly developed long-range Radio Frequency Identification (RFID) tag reader might completely solve this problem. Previously, passive (i.e., not battery powered) RFID tags could only be read from a distance of 16 inches or less. This new tag reader can read multiple tags up to 18 feet away, and indicate the direction and range of each tag. At a cost of under 10 each, 250 RFID tags would have to be placed around an environment to equal the cost of 1 Braille sign ($25), yet the value-added in terms of available information at a distance is incredible: every object (landmark, door, water fountain, exit sign, chair, table, etc.) within a range of 18 feet would be able to announce its presence. Visible signage equivalency could be achieved overnight. Further, Interface, Inc., a commercial floor manufacturer is now adhering RFID tags to the protected underside their 50X50 cm floor tiles. Using such flooring and the new long-range readers, a very elegant and affordable indoor GPS-like guidance system can be realized through triangulation of these RFID floor tiles. In the long run, as this RFID flooring infrastructure fills in, the most ideal solution could result, as it would enable the development of easily-managed building databases containing everything users would need to know to orient to new buildings and find their way around with ease. Users would never be lost, as they would always know their current location and heading. In addition, such a building database would be much easier to maintain, as opposed to updating individual RFID tags, when building tenants move or renovations take place. Interface is very interested in supporting our research, and is donating 2500 square feet of their RFID flooring to the VA for this purpose. The Research Questions to be answered by the herein proposed research are: 1. How should environmental information be organized and parsed according to actual needs so that persons can be provided with needed information without inundating them with useless and/or distracting information in the process? 2. How should a user interface be structured to offer needed information in an easily controlled and useable fashion? To address these Questions, the following Research Objectives have been established: 1. Determine what kinds of information are needed according to (a) a characterization of individual needs, O&M abilities, and degree of useful residual vision; 2. Develop a structured database of information parsed and organized according to information associated with specific participant characterization clusters as associated with individual needs, residual vision, etc.; 3. Develop an optimal user interface for the control and delivery of needed information adaptable to the individual needs of the participants; 4. Develop an RFID reader antenna that can triangulate RFID tags in flooring to determine the user's current location and heading, as well as identify the information and location of other tags of interest on objects in the surround; and 5. Construct and Evaluate a Wayfinding Prototype as specified by the results of the above objectives.

Interventions

DEVICEWayfinding Prototype

A Wayfinding Prototype is used by subjects to determine any advantages over current standard of rehabilitation.

Sponsors

US Department of Veterans Affairs
Lead SponsorFED

Study design

Allocation
NA
Intervention model
SINGLE_GROUP
Masking
NONE

Eligibility

Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No

Inclusion criteria

* Must be blind with no better vision than light perception and must be able to do 3 hours of walking (with many breaks)

Exclusion criteria

* N/A

Design outcomes

Primary

MeasureTime frameDescription
Mean Percent (Prototype / Baseline) Time2 hoursThe outcome measure for each subject is the mean of the (Prototype Time / Baseline Time) across 12 trials. The outcome measure for the experiment is the mean of 24 individual subject mean scores. This mean outcome measure is expressed as a percentage of the mean Baseline Time, where improved performance is represented by a percentage that is less than 100 percent of the Baseline Time. The lower the percentage, the better the performance improvement.

Countries

United States

Participant flow

Participants by arm

ArmCount
Baseline Wayfinding Performance
An Orientation and Mobility specialist teaches subjects (1) how to find each of 4 specific locations in an open space from a random starting location, and (2) how to navigate hallways from a known starting location to find each of 8 specific locations in the hallways of the Atlanta VA Medical Center. Subjects are then (1) brought to a random start point in the open space and asked to walk to the same 4 specific locations they were taught to find and (2) brought to a known starting point in the hallways of the VA Medical Center and asked to walk to the same 8 specific locations they were taught to find.
24
Total24

Baseline characteristics

CharacteristicBaseline Wayfinding Performance
Age, Continuous50.9 years
STANDARD_DEVIATION 13.4
Ethnicity (NIH/OMB)
Hispanic or Latino
1 Participants
Ethnicity (NIH/OMB)
Not Hispanic or Latino
23 Participants
Ethnicity (NIH/OMB)
Unknown or Not Reported
0 Participants
Race (NIH/OMB)
American Indian or Alaska Native
0 Participants
Race (NIH/OMB)
Asian
0 Participants
Race (NIH/OMB)
Black or African American
14 Participants
Race (NIH/OMB)
More than one race
0 Participants
Race (NIH/OMB)
Native Hawaiian or Other Pacific Islander
1 Participants
Race (NIH/OMB)
Unknown or Not Reported
0 Participants
Race (NIH/OMB)
White
9 Participants
Region of Enrollment
United States
24 participants
Sex: Female, Male
Female
12 Participants
Sex: Female, Male
Male
12 Participants

Adverse events

Event typeEG000
affected / at risk
deaths
Total, all-cause mortality
— / —
other
Total, other adverse events
0 / 24
serious
Total, serious adverse events
0 / 24

Outcome results

Primary

Mean Percent (Prototype / Baseline) Time

The outcome measure for each subject is the mean of the (Prototype Time / Baseline Time) across 12 trials. The outcome measure for the experiment is the mean of 24 individual subject mean scores. This mean outcome measure is expressed as a percentage of the mean Baseline Time, where improved performance is represented by a percentage that is less than 100 percent of the Baseline Time. The lower the percentage, the better the performance improvement.

Time frame: 2 hours

Population: Power Analysis: Using Repeated Measures ANOVA for the 24 participants assuming a minimum correlation between repeated measures of .7, we chose our analyses will be sensitive to a medium between factor effect size of f=.33 with power set to .80 and alpha level set to .05.

ArmMeasureValue (MEAN)Dispersion
Prototype vs. BaselineMean Percent (Prototype / Baseline) Time78.7 Percentage of Baseline Performance TimeStandard Deviation 68.6

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026