Artificial Intelligence and Augmentative and Alternative Communication AAC (AIinAAC)

May 28, 2025 updated by: Krista Wilkinson, Penn State University

Application of Artificial Intelligence to Improve Access to Augmentative and Alternative Communication

The overarching objective of this project is to transform access to assistive communication technologies (augmentative and alternative communication) for individuals with motor disabilities and/or visual impairment, for whom natural speech is not meeting their communicative needs. These individuals often cannot access traditional augmentative and alternative communication because of their restricted movement or visual function. However, most such individuals have idiosyncratic body-based means of communication that is reliably interpreted by familiar communication partners. The project will test artificial intelligence algorithms that gather information from sensors or camera feeds about these idiosyncratic movement patterns of the individual with motor/visual impairments. Based on the sensor or camera feed information, the artificial intelligence algorithms will interpret the individual's gestures and translate the interpretation into speech output. For instance, if an individual waves their hand as their means of communicating "I want", the artificial intelligence algorithm will detect that gesture and prompt the speech-generating technology to produce the spoken message "I want." This will allow individuals with restricted but idiosyncratic movements to access the augmentative and alternative communication technologies that are otherwise out of reach.

Study Overview

Detailed Description

As noted in the Communication Bill of Rights from the National Joint Committee on the Communication Needs of Persons with Severe Disabilities, "All people with a disability of any extent or severity have a basic right to affect, through communication, the conditions of their existence." Access to speech-language therapies that promote optimal communication outcomes is also noted to be a fundamental right by the United Nation's Article 19 of the Convention on the Rights of Persons with Disabilities. Yet many individuals with physical or intellectual disabilities have language limitations that prevent them from using speech as their primary mode of communication. For these individuals, assistive communication technologies (augmentative and alternative communication) offer an important set of supports for realizing this critical human right.

Although augmentative and alternative communication is widely-used and evidence-based, there are particular challenges in designing augmentative and alternative communication for individuals with visual and concomitant motor impairments. Unlike spoken language, in much of aided augmentative and alternative communication the vocabulary items are visual (letters, words, symbols) and only a limited number of items can be displayed at a time, since they must be presented on an external device (such as a tablet or a dedicated device). To maximize available vocabulary, clinicians often place many symbols onto the small display. Although this strategy can be useful for some people - and does maximize vocabulary visible on any given page - it is a substantial problem for individuals with visual impairments who cannot either see (ocular) or process (cortical) the visual information. In addition, access to these vocabulary items often involves use of a finger or eye gaze to select a symbol or a limb to activate a switch. These types of repetitive selections may be difficult and fatiguing for individuals with motor disabilities. As a consequence, traditional methods of accessing augmentative and alternative communication that work for other individuals are selectively more difficult for those with visual impairment and motor disabilities. There is an urgent need to develop augmentative and alternative communication technologies that reduce the visual and motoric burden for such individuals.

This project seeks to substantially increase the flexibility of aided augmentative and alternative communication access in part through a reconsideration of the traditional distinction made between aided (i.e., technology assisted) and unaided (i.e., body-based) communication modes. Aided communication modes offer the power of symbolic communication that is readily understood by many communication partners, even those who are unfamiliar with the individual using augmentative and alternative communication. However, aided modes can be quite limiting in terms of the vocabulary available, speed of message preparation, environmental constraints, and ability to support natural conversations. Unaided communication modes, on the other hand, can involve a diverse range of natural movements that are well within the skill set of the user, and can be rapidly produced with low effort. The drawback of unaided modes is that they are often difficult for unfamiliar partners to understand, thus limiting the range of potential communication partners and necessitating the proximity of a communication partner to the augmentative and alternative communication user to observe the body-based communication.

Given contemporary technology, it is both theoretically and practically possible to substantially increase access to aided augmentative and alternative communication by leveraging the ability of technology to sense and interpret unaided input ranging from natural air gestures to facial expressions and/or other intentional movement patterns. Harnessing unaided inputs as a supplemental means for access to technology will marry the power of the aided symbolic communication with the ease, speed, and unique movements employed by individual users. In so doing, it will shift the burden of access from the user (at least in part) onto the aided augmentative and alternative communication technologies themselves. Indeed, building flexible technologies that are tailored to the motor and visual skills of individuals with disabilities is well within the capabilities of modern devices and is an active area of research in Human-Computer Interaction and accessible computing.

This project will test artificial intelligence algorithms that are capable of interpreting idiosyncratic, individual-specific unaided gestures for augmentative and alternative communication access. This proposed system is intended to be human-centered, use-inspired, and readily-programmed, to empower both the user and their communication partners who may be involved in augmentative and alternative communication services. The project will solicit individuals with a wide range of motor disabilities to ensure the algorithms are widely applicable.

Study Type

Interventional

Enrollment (Actual)

6

Phase

  • Not Applicable

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

    • Pennsylvania
      • University Park, Pennsylvania, United States, 16802
        • The Pennsylvania State University

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Adult
  • Older Adult

Accepts Healthy Volunteers

No

Description

Inclusion Criteria:

  • Have motor impairment, which can present in diverse/multiple ways, including spasticity, ataxia, or dystonia (these types of movement disorders are different from one another, and can result from diverse genetic conditions or injury to the brain before or shortly after birth, and generally all fall under the umbrella term cerebral palsy or movement disorder). Note: Presence of intellectual disability in addition to motor disability is not an exclusionary criteria, meaning that we will include both individuals with intact intellectual ability as well as those with intellectual disability
  • Can/will tolerate a small biosensor (about the size of a medallion) attached to a limb (for instance, wrist or elbow) embedded within a soft wrist band

Exclusion Criteria:

  • Do not have motor disabilities
  • Cannot tolerate a small biosensor (about the size of a medallion) attached to a limb (for instance, wrist or elbow) with a soft wrist band

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Primary Purpose: Device Feasibility
  • Allocation: N/A
  • Interventional Model: Single Group Assignment
  • Masking: None (Open Label)

Arms and Interventions

Participant Group / Arm
Intervention / Treatment
Experimental: Evaluation of learnability and utility of artificial intelligence algorithm
Participants will be learning to use the artificial intelligence algorithms and testing them for ease of use and efficiency
The effectiveness of artificial intelligence algorithms for detecting and interpreting body-based gestures by individuals who have motor/visual impairments will be evaluated.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Time taken for Programming of artificial intelligence algorithms by users/personal care aides
Time Frame: average of 12 months
How long it takes participants learn to program the algorithms (number of minutes taken)
average of 12 months
Number of messages programmed by users/personal care aides
Time Frame: average of 12 months
How many messages the user/personal care aide can program in the session
average of 12 months

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

September 24, 2024

Primary Completion (Actual)

May 1, 2025

Study Completion (Actual)

May 1, 2025

Study Registration Dates

First Submitted

August 29, 2024

First Submitted That Met QC Criteria

September 12, 2024

First Posted (Actual)

September 19, 2024

Study Record Updates

Last Update Posted (Actual)

June 3, 2025

Last Update Submitted That Met QC Criteria

May 28, 2025

Last Verified

May 1, 2025

More Information

Terms related to this study

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

UNDECIDED

IPD Plan Description

The "Databrary" repository will be used specifically because it (a) was developed for video sharing in particular, and (b) it allows for differential level of access, and only to members, all of which requires approval from the Study Investigator. The study Investigator will set up an access level where only the deidentified information about movement and algorithm function are available (for instance, the x-y-z coordinates that came from the sensor). The study Investigator will also set up a more restricted access level where an investigator who would like to see the original video of the movement could apply to obtain that level of access. The consent form notes that this type of sharing will occur.

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

product manufactured in and exported from the U.S.

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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