# Simplified Ultrasound Biofeedback for Speech Remediation

> **NIH NIH R01** · UNIVERSITY OF CINCINNATI · 2020 · $505,507

## Abstract

Project Summary
Ultrasound biofeedback therapy (UBT), offering a real-time view of the tongue during speech, has shown promise
in treating residual speech sound disorders. However, the clinical utility of UBT is limited by the inherent difficulty
of interpreting real-time ultrasound images of rapidly changing tongue deformations during speech. For patients
to receive effective feedback from these images, clinicians must provide extensive explanation and orientation
over multiple sessions. Especially for younger patients, this rich, complex visual feedback directs attention
internally, a direction known to reduce performance and impulse force control during limb and oral movement
tasks. Further, since speech sound disorders often coexist with cognitive or behavioral difficulties, many patients
never master interpretation of tongue ultrasound images. Thus, the tremendous promise of UBT has not been
realized because its feedback is too complex, misdirected, and ambiguous.
 Scientific studies on implicit motor learning suggest UBT would be improved if (1) speakers are guided by
simpler visual feedback and (2) the simplification engages an external attentional focus. Feedback with these
qualities is known to facilitate rapid, robust sensorimotor skill learning. Application of these principles into UBT
is expected to provide great benefits to those with speech-sound disorders. The major goal of this project is to
translate these recent advances in UBT and motor learning into a new simplified ultrasound biofeedback system
for better clinical treatment of residual speech sound disorders.
 Our proposed system will transform the complex tongue movements captured by ultrasound into simplified
real-time feedback displays, customized for each user to drive tongue movements closer to goal movement
patterns. We will concentrate on remediation of /r/ and /l/, the most complex and frustrating sounds in clinical
speech therapy. Using a novel method for tongue motion tracking based on processing of real-time ultrasound
images, we will automatically characterize differentiated motion of tongue parts during /r/ and /l/ production. We
will employ statistical cluster analysis to identify multiple biofeedback targets indicating correct production. These
targets will be employed in a prototype simplified UBT system employing simple, engaging visual feedback to
guide patients toward correct tongue movement, presented by a highly motivating, gamified interface. Our
simplified UBT system will be validated in a pilot clinical trial, testing the hypotheses that simplified UBT is more
effective than standard UBT, and that the most effective biofeedback targets will be those promoting greater
differentiation of tongue motion. The end result will be translation of recent advances in ultrasound imaging of
speech, real-time image processing, and biofeedback-based motor learning into a novel clinical UBT tool that
will greatly advance treatment of residual speech sound disorders.

## Key facts

- **NIH application ID:** 10000057
- **Project number:** 5R01DC017301-03
- **Recipient organization:** UNIVERSITY OF CINCINNATI
- **Principal Investigator:** SUZANNE Elizabeth BOYCE
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $505,507
- **Award type:** 5
- **Project period:** 2018-08-10 → 2023-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10000057

## Citation

> US National Institutes of Health, RePORTER application 10000057, Simplified Ultrasound Biofeedback for Speech Remediation (5R01DC017301-03). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10000057. Licensed CC0.

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