Literature DB >> 33285082

Quantitative Assessment of Learning and Retention in Virtual Vocal Function Exercises.

Jarrad H Van Stan1,2,3, Se-Woong Park4, Matthew Jarvis5, Joseph Stemple6, Robert E Hillman1,2,3, Dagmar Sternad7.   

Abstract

Purpose Successful voice therapy requires the patient to learn new vocal behaviors, but little is currently known regarding how vocal motor skills are improved and retained. To quantitatively characterize the motor learning process in a clinically meaningful context, a virtual task was developed based on the Vocal Function Exercises. In the virtual task, subjects control a computational model of a ball floating on a column of airflow via modifications to mean airflow (L/s) and intensity (dB-C) to keep the ball within a target range representing a normative ratio (dB × s/L). Method One vocally healthy female and one female with nonphonotraumatic vocal hyperfunction practiced the task for 11 days and completed retention testing 1 and 6 months later. The mapping between the two execution variables (airflow and intensity) and one error measure (proximity to the normative ratio) was evaluated by quantifying distributional variability (tolerance cost and noise cost) and temporal variability (scaling index of detrended fluctuation analysis). Results Both subjects reduced their error over practice and retained their performance 6 months later. Tolerance cost and noise cost were positively correlated with decreases in error during early practice and late practice, respectively. After extended practice, temporal variability was modulated to align with the task's solution manifold. Conclusions These case studies illustrated, in a healthy control and a patient with nonphonotraumatic vocal hyperfunction, that the virtual floating ball task produces quantitative measures characterizing the learning process. Future work will further investigate the task's potential to enhance clinical assessment and treatments involving voice control. Supplemental Material https://doi.org/10.23641/asha.13322891.

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Year:  2020        PMID: 33285082      PMCID: PMC8608156          DOI: 10.1044/2020_JSLHR-20-00357

Source DB:  PubMed          Journal:  J Speech Lang Hear Res        ISSN: 1092-4388            Impact factor:   2.297


  62 in total

1.  Decomposition of variability in the execution of goal-oriented tasks: three components of skill improvement.

Authors:  Hermann Müller; Dagmar Sternad
Journal:  J Exp Psychol Hum Percept Perform       Date:  2004-02       Impact factor: 3.332

2.  Preliminary data on two voice therapy interventions in the treatment of presbyphonia.

Authors:  Aaron Ziegler; Katherine Verdolini Abbott; Michael Johns; Adam Klein; Edie R Hapner
Journal:  Laryngoscope       Date:  2014-01-29       Impact factor: 3.325

3.  Objective assessment of vocal hyperfunction: an experimental framework and initial results.

Authors:  R E Hillman; E B Holmberg; J S Perkell; M Walsh; C Vaughan
Journal:  J Speech Hear Res       Date:  1989-06

4.  High variability impairs motor learning regardless of whether it affects task performance.

Authors:  Marco Cardis; Maura Casadio; Rajiv Ranganathan
Journal:  J Neurophysiol       Date:  2017-09-27       Impact factor: 2.714

5.  Evidence for Auditory-Motor Impairment in Individuals With Hyperfunctional Voice Disorders.

Authors:  Cara E Stepp; Rosemary A Lester-Smith; Defne Abur; Ayoub Daliri; J Pieter Noordzij; Ashling A Lupiani
Journal:  J Speech Lang Hear Res       Date:  2017-06-10       Impact factor: 2.297

6.  The effect of vocal function exercises on the voices of aging community choral singers.

Authors:  Evelyn Ya Lian Tay; Debra Jean Phyland; Jennifer Oates
Journal:  J Voice       Date:  2012-06-19       Impact factor: 2.009

7.  A Randomized Controlled Trial of Two Semi-Occluded Vocal Tract Voice Therapy Protocols.

Authors:  Mara R Kapsner-Smith; Eric J Hunter; Kimberly Kirkham; Karin Cox; Ingo R Titze
Journal:  J Speech Lang Hear Res       Date:  2015-06       Impact factor: 2.297

8.  Variability in motor learning: relocating, channeling and reducing noise.

Authors:  R G Cohen; D Sternad
Journal:  Exp Brain Res       Date:  2008-10-25       Impact factor: 1.972

9.  The Statistical Determinants of the Speed of Motor Learning.

Authors:  Kang He; You Liang; Farnaz Abdollahi; Moria Fisher Bittmann; Konrad Kording; Kunlin Wei
Journal:  PLoS Comput Biol       Date:  2016-09-08       Impact factor: 4.475

Review 10.  Gamification for health and wellbeing: A systematic review of the literature.

Authors:  Daniel Johnson; Sebastian Deterding; Kerri-Ann Kuhn; Aleksandra Staneva; Stoyan Stoyanov; Leanne Hides
Journal:  Internet Interv       Date:  2016-11-02
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