Impact of Various Frequency Allocation Tables on Pitch Perception in Post-Lingual Cochlear Implant Recipients: A Case Series Study
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Abstract
Background and Aim: Cochlear implants in post-lingually deaf patients often result in reduced hearing naturality compared to their previous acoustic hearing, making adaptation and speech perception challenging. This study aimed to evaluate participants' perceptual ratings using Speech, Spatial Qualities (SSQ) 12 and the Sound Quality rating scale, alongside speech and pitch perception, across four different Frequency Allocation Tables (FAT).
Case Presentation: Four post-lingual cochlear implant users completed subjective ratings using the Speech, Spatial, and Qualities of Hearing Scale (SSQ 12) and the Speech Quality Rating Scale, while objective tests, including speech perception scores in quiet and noise, and psychophysical assessments like pitch perception tasks, were conducted across the four FATs.
Results: Performance using logarithmic FAT was better across all the domains of SSQ 12 and Speech Quality rating scale and in Speech in Noise Ratio (SNR) at both 0 and +10 dB. Pitch perception across four FATs reveals a statistically significant difference noted in the apical electrode score when compared with medial and basal electrodes across all the FATs.
Conclusion: The default FAT provided by the manufacturer may not be suitable for all users due to several factors such as length of the electrode array, shallow insertion of electrodes. Thus, all the FAT options must be utilized and tested for subjective, objective, and psychophysical performance and the best suitable FAT should be set for the specific patient.
2. Gomaa NA, Rubinstein JT, Lowder MW, Tyler RS, Gantz BJ. Residual speech perception and cochlear implant performance in postlingually deafened adults. Ear Hear. 2003;24(6):539-44. [DOI:10.1097/01.AUD.0000100208.26628.2D]
3. Lazard DS, Lee HJ, Truy E, Giraud AL. Bilateral reorganization of posterior temporal cortices in post-lingual deafness and its relation to cochlear implant outcome. Hum Brain Mapp. 2013;34(5):1208-19. [DOI:10.1002/hbm.21504]
4. Jethanamest D, Tan CT, Fitzgerald MB, Svirsky MA. A new software tool to optimize frequency table selection for cochlear implants. Otol Neurotol. 2010;31(8):1242-7. [DOI:10.1097/MAO.0b013e3181f2063e]
5. Chang CJ, Sun CH, Hsu CJ, Chiu T, Yu SH, Wu HP. Cochlear implant mapping strategy to solve difficulty in speech recognition. J Chin Med Assoc. 2022;85(8):874-9. [DOI:10.1097/JCMA.0000000000000748]
6. Xie D, Luo J, Chao X, Li J, Liu X, Fan Z, et al. Relationship Between the Ability to Detect Frequency Changes or Temporal Gaps and Speech Perception Performance in Post-lingual Cochlear Implant Users. Front Neurosci. 2022;16:904724. [DOI:10.3389/fnins.2022.904724]
7. Fuller CD, Galvin JJ 3rd, Maat B, Başkent D, Free RH. Comparison of Two Music Training Approaches on Music and Speech Perception in Cochlear Implant Users. Trends Hear. 2018;22:2331216518765379. [DOI:10.1177/2331216518765379]
8. Pijl S, Schwarz DW. Melody recognition and musical interval perception by deaf subjects stimulated with electrical pulse trains through single cochlear implant electrodes. J Acoust Soc Am. 1995;98(2 Pt 1):886-95. [DOI:10.1121/1.413514]
9. Luo X, Landsberger DM, Padilla M, Srinivasan AG. Encoding pitch contours using current steering. J Acoust Soc Am. 2010;128(3):1215-23. [DOI:10.1121/1.3474237]
10. Limb CJ, Roy AT. Technological, biological, and acoustical constraints to music perception in cochlear implant users. Hear Res. 2014;308:13-26. [DOI:10.1016/j.heares.2013.04.009]
11. Caldwell MT, Jiradejvong P, Limb CJ. Impaired Perception of Sensory Consonance and Dissonance in Cochlear Implant Users. Otol Neurotol. 2016;37(3):229-34. [DOI:10.1097/MAO.0000000000000960]
12. Galvin JJ 3rd, Fu QJ, Nogaki G. Melodic contour identification by cochlear implant listeners. Ear Hear. 2007;28(3):302-19. [DOI:10.1097/01.aud.0000261689.35445.20]
13. van de Heyning P, Arauz SL, Atlas M, Baumgartner WD, Caversaccio M, Chester-Browne R, et al. Electrically evoked compound action potentials are different depending on the site of cochlear stimulation. Cochlear Implants Int. 2016;17(6):251-62. [DOI:10.1080/14670100.2016.1240427]
14. Landsberger DM, Svrakic M, Roland JT Jr, Svirsky M. The Relationship Between Insertion Angles, Default Frequency Allocations, and Spiral Ganglion Place Pitch in Cochlear Implants. Ear Hear. 2015;36(5):e207-13. [DOI:10.1097/AUD.0000000000000163]
15. Zanetti D, Conte G, Di Berardino F, Lo Russo F, Cavicchiolo S, Triulzi F. Assessment of Frequency-Place Mismatch by Flat-Panel CT and Correlation With Cochlear Implant Performance. Otol Neurotol. 2021 Jan;42(1):165-173. [DOI:10.1097/MAO.0000000000002967]
16. Noble W, Jensen NS, Naylor G, Bhullar N, Akeroyd MA. A short form of the Speech, Spatial and Qualities of Hearing scale suitable for clinical use: the SSQ12. Int J Audiol. 2013;52(6):409-12. [DOI:10.3109/14992027.2013.781278]
17. Polat Z, Bulut E, Ataş A. Assessment of the Speech Intelligibility Performance of Post Lingual Cochlear Implant Users at Different Signal-to-Noise Ratios Using the Turkish Matrix Test. Balkan Med J. 2016;33(5):532-8. [DOI:10.5152/balkanmedj.2016.160180]
18. Fu QJ, Shannon RV. Effects of electrode configuration and frequency allocation on vowel recognition with the Nucleus-22 cochlear implant. Ear Hear. 1999;20(4):332-44. [DOI:10.1097/00003446-199908000-00006]
19. Boyer J, Stohl J. MELUDIA - Online music training for cochlear implant users. Cochlear Implants Int. 2022;23(5):257-69. [DOI:10.1080/14670100.2022.2069313]
20. Essens PJ, Povel DJ. Metrical and nonmetrical representations of temporal patterns. Percept Psychophys. 1985;37(1):1-7. [DOI:10.3758/bf03207132]
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| Keywords | ||
| Cochlear implants speech perception pitch perception frequency allocation table hearing loss post-lingual | ||
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