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BRIEF REPORT |
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Year : 2021 | Volume
: 40
| Issue : 1 | Page : 31-38 |
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Auditory steady-state responses to narrow-band chirps in predicting aided behavioral thresholds
CS Vanaja, Ashwini Kunjir
School of Audiology and Speech Language Pathology, Bharati Vidyapeeth (Deemed to be University), Pune, Maharashtra, India
Date of Submission | 08-Nov-2021 |
Date of Acceptance | 12-Jul-2022 |
Date of Web Publication | 06-Sep-2022 |
Correspondence Address: Dr. C S Vanaja School of Audiology and Speech Language Pathology, Bharati Vidyapeeth (Deemed to be University), Pune–Satara Road, Dhankawadi, Pune 411043, Maharashtra India
 Source of Support: None, Conflict of Interest: None
DOI: 10.4103/jose.JOSE_5_21
Purpose: A review of the existing literature shows that auditory steady-state responses (ASSR) to narrow-band (NB) chirps analyzed using q sample averaging is more reliable and accurate than ASSR for modulated tones in predicting behavioral thresholds. Studies in this direction have been carried out to predict hearing sensitivity. However, there is a dearth of studies investigating ASSR for NB chirps in persons using hearing aids. The present study evaluated if ASSR for NB chirps analyzed using q sample averaging could be used to predict aided behavioral thresholds during the hearing aid selection. Specifically, the study investigated the agreement and differences between behavioral thresholds predicted from aided ASSR with aided behavioral thresholds. Materials and Methods: Retrospective analysis of clinical records of 24 ears with hearing loss were carried out. The age of the children ranged from 3 to 5 years. Aided behavioral thresholds and aided ASSR for NB chirps were recorded at 500 Hz, 1000 Hz, 2000 Hz, and 4000 Hz. Results: Wilcoxon signed-rank test revealed no significant difference between aided thresholds predicted through aided ASSR and measured behavioral thresholds for all four frequencies. The Bland–Altman analysis also showed that the results of the two tests are comparable for all four frequencies. Conclusions: Aided ASSR can predict aided behavioral thresholds in children who fail to provide voluntary responses to behavioral tests, but the results need to be crosschecked using other measures. ASSR can thus be added to the protocol used for hearing aid fitting and validation in young children. Keywords: Electrophysiological measure, hearing aid selection, hearing aid validation, hearing aid verification
How to cite this article: Vanaja C S, Kunjir A. Auditory steady-state responses to narrow-band chirps in predicting aided behavioral thresholds. J All India Inst Speech Hear 2021;40:31-8 |
How to cite this URL: Vanaja C S, Kunjir A. Auditory steady-state responses to narrow-band chirps in predicting aided behavioral thresholds. J All India Inst Speech Hear [serial online] 2021 [cited 2023 Mar 27];40:31-8. Available from: http://www.jaiish.com/text.asp?2021/40/1/31/355664 |
The selection of an appropriate hearing device(s) is a crucial step in aural rehabilitation. The emphasis on neonatal hearing screening has underscored the importance of early intervention for infants with hearing loss. The advancement in the field of audiology has made it possible to diagnose hearing loss and initiate aural habilitation early in life. Evidence in the literature indicates that it is possible to fit hearing devices to infants as young as 5 weeks (Yoshinaga-Itano, 2004). However, fitting appropriate hearing devices and verifying the efficacy of the hearing devices in infants and children are challenging tasks for audiologists. One of the major difficulties faced by audiologists in this regard is obtaining voluntary responses for behavioral tests from infants and young children. To overcome this limitation, electrophysiological measures are recommended in the test battery.
Auditory steady-state response (ASSR) is one of the electrophysiological measures used for assessing hearing in difficult-to-test populations. Many investigators have reported that ASSR can be used to predict pure-tone thresholds of infants and children (Aoyagi et al., 2007; Cone-Wesson et al., 2002; Guzzetta et al., 2011; Rance et al., 2005). Attempts were made to use ASSR as an objective measure in the selection and validation of hearing devices for infants/children with hearing loss (Damarla & Manjula, 2007; Picton et al., 1998). The strengths of using ASSR for the hearing aid selection lie in its ability to obtain frequency-specific information from infants and children under natural or sedated sleep. Compared with auditory brainstem response (ABR), ASSR can be recorded in considerably short time (Sininger et al., 2018) and, hence, would make a good choice if one needs to repeat the test with more than one hearing aid. Picton et al. (1998) measured hearing thresholds using ASSR for amplitude-modulated sinusoids in 35 children using hearing aids and reported that ASSR can be used to measure functional gain. Similarly, a positive correlation was reported between insertion gain obtained using real ear measurements and functional gain measured using aided and unaided ASSR (Damarla & Manjula, 2007). Further, the intensity amplitude function of ASSR was used to describe a protocol to establish the dynamic range, gain, compression ratio, and maximum output of hearing aid (Zenker Castro et al., 2006).
It can be construed from these studies that ASSR can be helpful in fitting hearing aids for the difficult-to-test population. A majority of the earlier studies investigating the usefulness of ASSR in the selection or validation of hearing aids have used modulated tones for eliciting ASSR. Though the results of many of these studies indicate that ASSR can be used to predict behavioral pure-tone thresholds, the reliability and accuracy of ASSR to modulated tones in predicting thresholds have been questioned by some of the investigators. Based on an investigation in persons with normal hearing and persons with hearing impairment, Israelsson, Bogo, & Berninger (2015) raised concerns about the reliability of multiple ASSR to tones with a mixed modulation in predicting hearing thresholds. The correlation values between ASSR thresholds to modulated tones and behavioral thresholds reported in a few investigations do not justify the use of ASSR in predicting behavioral thresholds, especially at low frequencies (Attias et al., 2014; Rance et al., 2005; Rodrigues & Lewis, 2010). In addition, the amplitude of ASSR to modulated tones is reported to be highly variable across test sessions in persons with normal hearing as well as those with sensorineural hearing loss (D’Haenens et al., 2008; Wilding et al., 2012). Owing to such discrepant findings, ASSR is not a widely used tool for hearing evaluation or hearing aid selection and validation in the audiology clinics.
The detectability of ASSR is determined by the amplitude of responses and signal-to-noise ratio. As is the case for all the electrophysiological measures, several factors have an effect on the amplitude of ASSR. The two major factors affecting the amplitude of ASSR are the stimuli used for testing and the techniques used for recording. Studies have demonstrated that ASSR can be elicited using broad-band and narrow-band (NB) chirps as stimuli (Elberling et al., 2007; Rodrigues & Lewis, 2014). Amplitude-modulated tones stimulate only a narrow portion of the basilar membrane resulting in low amplitude of ASSR, whereas the use of chirp stimuli improves the amplitude of the response (Rodrigues & Lewis, 2014). The higher amplitude of ASSR observed for NB chirps has been attributed to increased neural synchrony for chirps (Elberling et al., 2007). Research has also shown that reliable ASSR can be obtained using NB chirps in infants (Rodrigues & Lewis, 2014) and children (Venail et al., 2015).
Initially, one sample test was used to evaluate the phase or phase and amplitude of response of the first harmonic to detect ASSR (Rodrigues & Lewis, 2014). There is evidence in the literature to show that the use of q sample test, which considers higher harmonics along with fundamental frequency for analysis, leads to a better detection of the response (Cebulla et al., 2006). Based on these studies, some of the commercially available instruments have included the facility to record ASSR for NB chirps and analyze the response using q sample test. Sininger et al. (2018) referred to the use of NB chirp stimuli along with the analysis of multiple harmonics of the modulation frequency with new approach to critical test values as “next-generation ASSR.” It has been reported that “next-generation ASSR” yields low ASSR thresholds (Rodrigues & Lewis, 2014; Sininger et al., 2018). Lee et al., (2016) reported that NB chirp ASSR thresholds were closer to the behavioral thresholds with a stronger correlation and better reliability when compared with ASSR thresholds for modulated tones.
A majority of the studies on “next-generation ASSR” have only explored its usefulness in assessing hearing sensitivity. There is a dearth of studies on the use of ASSR for NB chirps as stimuli and q sample test for analysis, in the hearing aid selection and/or validation. Hence, the present study was designed to investigate if aided ASSR (ASSR recorded while a child is using a hearing aid) for NB chirps can be used in the hearing aid selection. Specifically, the study investigated the agreement and differences between behavioral thresholds predicted from aided ASSR and aided behavioral thresholds.
Materials and Methods | |  |
A retrospective design was used to investigate the aims and objectives of the study. The study was carried out following the ethical rules of Bharati Vidyapeeth (DU) Medical College, Pune.
Participants
Clinical records of children registered in the cochlear implant clinic of Bharati Vidyapeeth (DU) School of Audiology and Speech Language Pathology from 2018 to 2020 were reviewed. All the parents of children registered at the cochlear implant clinic signed a consent form that the results of clinical evaluations may be used for research purposes without revealing the identity of the children. The standard protocol followed in the cochlear implant clinic for evaluating cochlear implant candidacy in children includes testing with hearing aids using age-appropriate behavioral and physiological tests. Behavioral tests include aided behavioral observation audiometry or visual reinforcement audiometry or play audiometry. Physiological measures include aided ASSR or cortical auditory-evoked potentials. Results of both physiological and behavioral tests are correlated to decide whether the child is a candidate for cochlear implant or not. Clinical records of 24 ears of children in the age range of 3–5 years were chosen for analyses. All the children had bilateral severe or profound hearing loss as revealed by pure-tone audiometry. Immittance evaluation did not indicate any middle ear pathology. Hearing aid evaluation was carried out using aided sound field audiometry and aided ASSR.
Equipment
A calibrated Madsen Itera audiometer with TDH 39 supra-aural headphones housed in MX 41 AR cushions, Radioear B-71 bone vibrator, and matched loudspeaker were used to measure the behavioral pure-tone thresholds and aided sound field thresholds. The immittance evaluation was conducted using the Interacoustics AT235 immittance meter. Aided ASSR was recorded using the Interacoustics Eclipse EP25 Version 4.4 software module with calibrated FBT J5A Processed Active monitor speakers.
Test environment
All the behavioral tests were performed in an acoustically treated room with optimum lighting and temperature. The electrophysiological tests were conducted under natural or sedated sleep in a quiet room with optimum temperature and dim lighting.
Procedure
Initially, a detailed case history was taken from the parents, followed by an otoscopic examination of all the participants. Pure-tone hearing thresholds were estimated in air conduction and bone conduction modalities using play audiometry. The immittance evaluation including a tympanogram for 226 Hz probe tone and acoustic reflex testing for 500 Hz, 1000 Hz, 2000 Hz, and 4000 Hz was carried out. ABR and otoacoustic emissions were recorded to crosscheck the results of play audiometry.
Based on the pure-tone thresholds, a digital hearing aid was programmed for each ear to provide appropriate amplification. Aided behavioral thresholds were obtained through play audiometry in an acoustically treated two-room suite. The child was seated on a chair placed at a distance of 1 m from the loudspeakers. Aided thresholds were obtained with monaural hearing aids, for warble tones presented through sound field speakers, at octave intervals from 500 to 4000 Hz.
Aided ASSR was recorded with monaural hearing aids under natural or sedated sleep. NB chirp stimuli with center frequencies of 500 Hz, 1000 Hz, 2000 Hz, and 4000 Hz were presented through a calibrated loudspeaker. The NB chirps used in EP 25 are obtained by decomposing broad-band CE chirp (Elberling & Don, 2010). The duration of the chirp varies with frequency and is 1.5 ms for 4000 Hz, 2.5 ms for 2000 Hz, 3.5 ms for 1000 Hz, and 4.5 ms for 500 Hz. All four stimuli were presented simultaneously at a unique repetition rate around 90 Hz. Single-channel recording was performed with the noninverting electrode on the upper forehead (Fz), inverting electrodes on the test ear mastoid (M1 or M2), and common electrode on the lower forehead (Fpz).
A detailed description of the algorithm used for the automatic detection of ASSR in EP 25 is described by Sininger et al. (2020). It assesses individual sweeps and analyzes amplitude as well as phase of 12 harmonics of the modulation frequency (repetition rate). Using the stopping criteria described by Stürzebecher et al., (2006), an analysis with a small sample of individual sweeps is initiated. The statistical testing is repeated as and when more samples are collected. The calculated test value is always compared with the critical test value for repeated testing developed by Stürzebecher et al., (2005). If the calculated test value reaches the critical test value, response is considered as present and the test is stopped. If the test value does not reach the critical value, testing is stopped after 6 min.
Noise rejection was set to 40 nV. The testing was initiated at 80 dB HL, and the intensity was reduced in 10 dB steps to obtain ASSR threshold. The lowest intensity at which ASSR was obtained was considered as ASSR threshold. Thresholds for each frequency were evaluated simultaneously.
The mean difference between ASSR thresholds and behavioral thresholds in persons with normal hearing reported by Khan (2020) was deducted from the ASSR thresholds obtained for each participant to predict their behavioral thresholds. This is referred to as “predicted behavioral thresholds,” whereas the thresholds obtained through sound field audiometry are referred to as “measured behavioral thresholds.”
Results | |  |
Measured behavioral thresholds and predicted behavioral thresholds were tabulated for statistical analyses. Thresholds obtained through the two methods were compared using Bland–Altman analysis, a method used for comparing two measurements. The analysis was carried out separately for each frequency using XLSTAT for Excelt. [Table 1] shows the mean and standard deviation of the measured and predicted behavioral thresholds. It was observed that the measured behavioral thresholds and the predicted behavioral thresholds are comparable. [Table 1] also shows the results of paired t test comparing the measured and predicted behavioral thresholds. The results indicated that there was no significant difference between the two thresholds at any of the frequencies. | Table 1: Descriptive and comparative statistics of the measured and predicted behavioral thresholds
Click here to view |
Bland–Altman analysis plots were obtained to assess the level of agreement (LoA) between the measured thresholds and predicted thresholds by estimating the bias present between them. [Table 2] depicts the bias (mean difference), LoA, and Pearson’s correlation values between measured behavioral thresholds and predicted behavioral thresholds for the four frequencies. It can be observed that there was a moderate-to-strong positive correlation between the measured behavioral thresholds and predicted behavioral thresholds at each of the frequencies. The mean bias (difference) was very low for all the frequencies indicating the agreement between the two methods. Further, the bias was larger for 2000 and 4000 Hz when compared with 500 Hz and 1000 Hz. LoA also followed a similar trend. The scatter plots and Bland–Altman plots for the four frequencies are shown in [Figure 1][Figure 2][Figure 3][Figure 4]. From the plots, it can be observed that very few points were outside the 95% LoA, indicating that the predicted thresholds were within 95% LoA for most of the individuals. | Table 2: Bias, level of agreement, and correlation values between the measured and predicted thresholds
Click here to view |  | Figure 1: Bland–Altman graph comparing the predicted and measured threshold for 500 Hz
Click here to view |  | Figure 2: Bland–Altman graph comparing the predicted and measured threshold for 1000 Hz
Click here to view |  | Figure 3: Bland–Altman graph comparing the predicted and measured threshold for 2000 Hz
Click here to view |  | Figure 4: Bland–Altman graph comparing the predicted and measured threshold for 4000 Hz
Click here to view |
Discussion | |  |
In the present study, hearing aid–assisted ASSR for NB chirps was used to predict aided behavioral thresholds in children with hearing loss. Earlier studies have shown that ASSR for NB chirps can be used to predict pure-tone thresholds in persons with normal hearing as well as those with sensorineural hearing loss (Ehrmann-Müller et al., 2021; Khan, 2020; Rodrigues & Lewis, 2010; Sininger et al., 2018). It has been reported that ASSR to NB chirps can be used as a reliable objective method in estimating the behavioral threshold in both normal hearing individuals and those with various degrees of sensorineural hearing loss. The results of the present study demonstrated that the hearing aid–assisted behavioral thresholds can be predicted using hearing aid–assisted ASSR for NB chirps. The findings are in consonance with the earlier reports on ASSR in persons using hearing aids (Damarla & Manjula, 2007; Picton et al., 1998). Despite variations in the stimuli and analysis methods used in the present study, the results are comparable. The correlation values obtained in the present study using NB chirps were similar to those reported in the earlier studies that used modulated tones. Although the test time could not be monitored and analyzed owing to the retrospective study design, clinical observation revealed that ASSR to NB chirps analyzed using q sample averaging yielded reliable responses in lesser time. Thus, ASSR for NB chirps can be included as an objective measure for assessing benefit from hearing aids. These results support the observation of Yonghua and Shuoyao (2019) who reported that ASSR to NB chirps in the sound field can be used to assess hearing aid benefit in children with moderate and very severe hearing loss. However, a comparison of the results of the present study with those of the earlier studies indicates that ASSR obtained for NB chirps analyzed using q sample averaging does not improve accuracy.
A previous research has shown that ABR is not a good test for measuring aided thresholds as the hearing aids cannot effectively process the transient stimuli used for recording ABR (Brown et al., 1999). The duration of the NB chirps used in the present study was longer than the duration of the stimuli used for click evoked ABR. ASSR obtained for these stimuli in children using hearing aids indicates that the stimuli were processed through hearing aids. In view of these, further studies are required to investigate the effectiveness of hearing aids in processing short duration signals.
Though the results of the present study showed a significant association between the thresholds predicted using ASSR and those measured through behavioral testing, the correlation values were not very strong. The correlation values obtained in the present study are similar to correlation values reported earlier for recordings carried out with and without hearing aids (Attias et al., 2014; Rance et al., 2005; Rodrigues & Lewis, 2010). The correlation values and LoA values obtained do not support the use of ASSR as an independent test for estimating benefit from hearing aids. It may thus be reasonable to include ASSR in the test battery to compliment information obtained from other measures.
Children were tested under sedation or natural sleep with stimuli being presented at a repetition rate of around 90 Hz. Earlier research has shown that ASSR can be reliably recorded under sleep for stimuli with a modulation frequency of 80 Hz or greater (Aoyagi et al., 2007). This is definitely a boon while evaluating infants and children for hearing aid fitting. The current study evaluated clinical records of children in the age range of 3–5 years, as behavioral thresholds obtained through aided sound field audiometry were considered as a standard measure for comparison of predicted behavioral thresholds. In our clinic, aided ASSR has been carried out on infants as young as 5 months of age, and behavioral responses obtained on follow-up has shown correlation with the results of ASSR. The data have not been analyzed statistically owing to a limited number of samples. We opine that including aided ASSR recording in the protocol for fitting hearing aid device will enable audiologists in fitting hearing devices at a young age. The use of objective measures will facilitate the selection and verification of hearing aids in children in whom obtaining voluntary responses for behavioral tests may not be feasible.
Conclusions | |  |
The implementation of newborn hearing screening programs has significantly brought down the age of identification of hearing loss, thereby facilitating early intervention. It can be concluded from the present study that aided ASSR can be recorded for NB chirps presented with a modulation frequency of 90 Hz and the same can be used to predict behavioral aided thresholds of children who cannot give voluntary responses for behavioral tests. However, moderate correlation value and large LoA obtained in the present study suggest that the results of ASSR need to be crosschecked with other measures.
Acknowledgements
The authors acknowledge the authorities of the BV(DU) School of Audiology and Speech Language Pathology for permitting to publish this study. The authors thank all the audiologists of BV(DU) SASLP who were part of the aural rehabilitation team of children included in the present study.
Financial support and sponsorship
Nil.
Conflicts of interest
There are no conflicts of interest.
References | |  |
1. | Aoyagi, M, Watanabe, T, Ito, T, & Abe, Y (2007). Reliability and frequency specificity of auditory steady-state response detected by phase spectral analysis. The Journal of the Acoustical Society of America, 122(3): EL58-EL61. |
2. | Attias, J, Karawani, H, Shemesh, R, & Nageris, B (2014). Predicting hearing thresholds in occupational noise-induced hearing loss by auditory steady state responses. Ear and Hearing, 35(3): 330-338. |
3. | Brown, E, Klein, A. J, & Snydee, K. A (1999). Hearing-aid-processed tone pips: Electroacoustic and ABR characteristics. Journal of American Academy of Audiology, 10(4): 190-197. |
4. | Cebulla, M, Stürzebecher, E, & Elberling, C (2006). Objective detection of auditory steady-state responses: Comparison of one-sample and q-sample tests. Journal of American Academy of Audiology, 17(2): 93-103. |
5. | Cone-Wesson, B, Dowell, R. C, Tomlin, D, Rance, G, & Ming, W. J (2002). The auditory steady-state response: Comparisons with the auditory brainstem response. Journal of American Academy of Audiology, 13(4): 173-187; quiz 225-176. |
6. | Damarla, V, & Manjula, P (2007). Application of ASSR in the hearing aid selection process. Australian and New Zealand Journal of Audiology, 29(2): 89-97. |
7. | D’Haenens, W, Vinck, B. M, De Vel, E, Maes, L, Bockstael, A, Keppler, H, … Dhooge, I (2008). Auditory steady-state responses in normal hearing adults: A test-retest reliability study. Int ernational J ournal of Audiol ogy, 47(8): 489-498. |
8. | Ehrmann-Müller, D, Shehata-Dieler, W, Alzoubi, A, Hagen, R, & Cebulla, M (2021). Using ASSR with narrow-band chirps to evaluate hearing in children and adults. European Archives of Oto-Rhino-Laryngology, 278(1): 49-56. |
9. | Elberling, C, & Don, M (2010). A direct approach for the design of chirp stimuli used for the recording of auditory brainstem responses. The Journal of the Acoustical Society of America, 128(5): 2955-2964. |
10. | Elberling, C, Don, M, Cebulla, M, & Stürzebecher, E (2007). Auditory steady-state responses to chirp stimuli based on cochlear traveling wave delay. The Journal of the Acoustical Society of America, 122(5): 2772-2785. |
11. | Guzzetta, F, Conti, G, & Mercuri, E (2011). Auditory processing in infancy: Do early abnormalities predict disorders of language and cognitive development? Developmental Medicine & Child Neurology, 53(12): 1085-1090. |
12. | Israelsson, K. E, Bogo, R, & Berninger, E (2015). Reliability in hearing threshold prediction in normal-hearing and hearing-impaired participants using mixed multiple ASSR. Journal of American Academy of Audiology, 26(3): 299-310. |
13. | Khan, Q (2020). Threshold Estimation Using Auditory Brainstem Response for Tonebursts, Chirps and Auditory Steady State Response: A Comparative Study. An unpublished Master’s dissertation submitted to Bharati Vidyapeeth (DU), Pune. |
14. | Lee, M. Y, Ahn, S. Y, Lee, H. J, Jung, J. Y, Rhee, C. K, & Suh, M. W (2016). Narrow band CE-chirp auditory steady-state response is more reliable than the conventional ASSR in predicting the behavioral hearing threshold. Auris Nasus Larynx, 43(3): 259-268. |
15. | Picton, T, Durieux-Smith, A, Champagne, S, Whittingham, J, Moran, L, Giguère, C, & Beauregard, Y (1998). Objective evaluation of aided thresholds using auditory steady-state responses. Journal of the American Academy of Audiology, 9(5): 315-331. |
16. | Rance, G, Roper, R, Symons, L, Moody, L. J, Poulis, C, Dourlay, M, & Kelly, T (2005). Hearing threshold estimation in infants using auditory steady-state responses. Journal of American Academy of Audiology, 16(5): 291-300. |
17. | Rodrigues, G. R, & Lewis, D. R (2010). Threshold prediction in children with sensorioneural hearing loss using the auditory steady-state responses and tone-evoked auditory brain stem response. International Journal of Pediatric Otorhinolaryngology, 74(5): 540-546. |
18. | Rodrigues, G. R, & Lewis, D. R (2014). Establishing auditory steady-state response thresholds to narrow band CE-chirps(®) in full-term neonates. International Journal of Pediatric Otorhinolaryngology, 78(2): 238-243. |
19. | Sininger, Y. S, Hunter, L. L, Hayes, D, Roush, P. A, & Uhler, K. M (2018). Evaluation of speed and accuracy of next-generation auditory steady state response and auditory brainstem response audiometry in children with normal hearing and hearing loss. Ear and Hearing, 39(6): 1207-1223. |
20. | Sininger, Y. S, Hunter, L. L, Roush, P. A, Windmill, S, Hayes, D, & Uhler, K. M (2020). Protocol for rapid, accurate, electrophysiologic, auditory assessment of infants and toddlers. Journal of American Academy of Audiology, 31(6): 455-468. |
21. | Stürzebecher, E, Cebulla, M, & Elberling, C (2005). Automated auditory response detection: Statistical problems with repeated testing Evaluación repetida en la detección de respuestas auditivas. International Journal of Audiology, 44(2): 110-117. |
22. | Stürzebecher, E, Cebulla, M, Elberling, C, & Berger, T (2006). New efficient stimuli for evoking frequency-specific auditory steady-state responses. Journal of American Academy of Audiology, 17(6): 448-461. |
23. | Venail, F, Artaud, J. P, Blanchet, C, Uziel, A, & Mondain, M (2015). Refining the audiological assessment in children using narrow-band CE-chirp-evoked auditory steady state responses. Int ernational J ournal of Audiol ogy, 54(2): 106-113. |
24. | Wilding, T. S, McKay, C. M, Baker, R. J, & Kluk, K (2012). Auditory steady state responses in normal-hearing and hearing-impaired adults: An analysis of between-session amplitude and latency repeatability, test time, and F ratio detection paradigms. Ear and Hearing, 33(2): 267-278. |
25. | Yoshinaga-Itano, C (2004). Levels of evidence: Universal newborn hearing screening (UNHS) and early hearing detection and intervention systems (EHDI). Journal of Communication Disorders, 37(5): 451-465. |
26. | Yonghua, W, & Shuoyao, X (2019). Feasibility study on the evaluation of the effect of narrow-band CE-chirp ASSR in the hearing field after hearing aid in hearing-impaired children. Advanced Treatments in ENT Disorders, 3: 7-11. |
27. | Zenker Castro, F, Fernández Belda, R, & Barajas de Prat, J. J (2006). [Fitting hearing aids in early childhood based on auditory evoked potentials in steady states]. Acta Otorrinolaringologica Espanola, 57(9): 388-393. |
[Figure 1], [Figure 2], [Figure 3], [Figure 4]
[Table 1], [Table 2]
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