Karen Iler Kirk, Ph.D., CCC-SLP* Shahid and Ann Carlson Khan Professor and Head

Department of Speech and Hearing Science University of Illinois at Urbana-Champaign

Multimodal Assessment and Speech Perception Outcomes in Children with Cochlear Implants or

Hearing Aids

Work supported by NIDCD Grants R01 DC 008875 and P50 DC000242

DISCLOSURE: Test materials described in this presentation are licensed to G.N. Otometrics through The University of Iowa

Collaborators

�  The University of Iowa �  Karen Iler Kirk, PhD (PI) �  Lindsay Prusick, AuD �  Virginia Driscoll, MA �  Nathaniel Wisecup, BA �  Lauren Diamond, BA �  Lauren Dowdy, BA �  Ruth Flaherty, BA

�  House Research Institute, Los Angeles �  Laurie Eisenberg, PhD (PI) �  Amy Martinez, MA �  Dianne Hammes Ganguly, MA

�  Children’s Memorial Hospital, Chicago �  Nancy Young, MD (PI) �  Susan Stentz, AuD �  Lisa Weber, AuD �  Iguehi James, MPH

�  Washington State University �  Brian French, PhD (PI) �  Chad Gotch, MS

�  University of Illinois �  Michael Novak, MD �  Jean Thomas, AuD �  Michael Hudgins, BA

Introduction �  Listeners must extract linguistic message from highly

variable acoustic speech signal

�  Variability introduced by:

�  Talker characteristics - gender, age, dialect and speech rate

�  Environment – noise, reverberation

�  Presentation format – A-only vs. Auditory-plus-Visual

�  Linguistic characteristics

�  Word frequency – how often words occur in language

�  Lexical Density – the number of phonemically similar words or lexical

neighbors

Multimodal Lexical Sentence Test (MLST-CTM) �  21 lists of 8 sentences

�  10 talkers �  3 key words per sentence �  Key words in each sentence drawn from the same lexical category

�  Strong Psychometric principles �  Lists are reliable and equivalent within each format: V, A, AV

Purposes �  To examine performance in quiet in children with cochlear

implants or hearing aids

�  To examine performance in noise as a function of � Signal-to-Noise Ratio (SNR) � Group

�  CI only �  CI + HA

�  To evaluate AV enhancement as a function of SNR

CI Users (n = 32)

HA Users (n = 27)

CI+HA Users (n=9)

Mean Age at Test 9.86 years 8.92 years 9.61 years

Mean Age at Onset .18 years 1.07 years 0 years

Mean Age Fit (current sensory aid)

2.93 years 3.18 years 6.67 years

Hearing Loss Classification (4 frequency PTA)

Profound - 20* Unknown - 12

Mild - 9 Moderate – 15

Severe - 2 Profound - 1

CI: Profound HA: Severe -8 Profound -1

Receptive Vocabulary Age

9.32 years 9.73 years 9.63 years

Gender 16 males 16 females

16 males 11 females

7 males 2 females

Assessing Performance in Quiet Participants (N=68)

*Pre-implant thresholds

Methods �  All MLSTTM lists administered twice �  Every participant tested in all 3 presentation formats

�  1/3 Visual Only �  1/3 Auditory Only �  1/3 Auditory + Visual

�  Additional auditory only testing �  Isolated word recognition (PBK) �  2 lists of HINT-C

�  Procedures �  Speech presented at 60 dB SPL in quiet

�  Verbal responses scored as percent correct

�  Receptive Vocabulary assessed using PPVT

Results: Multimodal Sentence Recognition

Auditory-Only Speech Recognition

Performance in Noise: CI Participants (n=20)

CI (n=14)   CI+HA (n=6)  

Mean Age at Test   12.1 yrs   9.8 yrs  

Mean Age at Implantation 3.2 yrs   5.5 yrs  

Mean Length of Device Use   9.9 yrs   4.5 yrs  

Type of CI  

Freedom (n=5) CI24M (n=5) CI24R (n=1)

Countour (n=3)  

Hybrid L24 (n=2) Contour (n=1) Freedom (n=2)

CI512 (n=1)  

Procedures �  Speech administered at 60 dBA SPL

�  Each participant tested in A and AV formats � Quiet � SNRs: -5, 0, +5, +10 � 2 lists per condition (2 formats X 4 SNRS = 8 lists)

�  Verbal responses scored as % key words correct

�  Logistic regression computed to estimate Speech Recognition Threshold

Results

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CI CI + HA A only 2.8 dB -0.6 dB

A + V -8.5 dB -13.1 dB

Audiovisual Gain

Ra = (AV-A)/(100-A)

�  Relative gain in accuracy in AV condition relative to A only

�  Used by Lachs et al. (2001) to examine AV speech perception in children with CIs

Ra by SNR

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Conclusions

�  The MLST-CTM �  Incorporates "real-world” stimulus variability

�  Multiple talkers �  Different presentation formats

�  Is a more sensitive measure of performance than traditional tests

�  The addition of visual cues enhances speech perception �  Largest improvements at poorer signal-to-noise ratios

�  Not all children show similar benefit �  Enhancement is larger for children with acoustic low frequency hearing

�  Future testing to examine factors related to AV enhancement