The only time information that was saved for ASSR was the time for the entire evaluation. For ABR, the number of sweeps for each run at threshold (lowest stimulus level at a single frequency) were recorded. The mean number of sweeps required for the ABR run at threshold, and therefore meeting the prescribed FMP value, was 2181 with a SD of 1361.49. The range of number of sweeps required to reach threshold was from 800 sweeps, which is the minimum allowed by the ABR system, to just under 8000.
The amount of averaging needed to achieve ABR thresholds was also analyzed by hearing threshold level. As an estimate of the average hearing level, the threshold obtained by the broad-band CE-Chirp was used. The data are shown in Figure 10 and indicated that the threshold responses required more averaging as the degree of hearing loss increased. This trend was significant with F(19,47) = 1.818, p = 0.049.
The average residual noise at threshold was computed for both ASSR and ABR techniques at each frequency by ear. These are shown in Table 6.
Of the 93 children with valid tests by ABR or ASSR, 47 (51%) were found to have average thresholds of 12 dB eHL or less in both ears by one or both methods without discrepancies between the 2. Of the 41 children originally referred because of newborn hearing fails, 20 (49%) were determined to have normal hearing. Most of the children with normal hearing had 5 or more points passing on the DPOAE and were judged normal on tympanometry. Overall, of the 47 children with normal hearing, 25 (53%) were considered normal on measures of DPOAE and tympanometry in both ears and had average broad-band CE-Chirp thresholds of 20 dB or less. Otoacoustic emissions outcomes were also evaluated by overall hearing level as estimated by average ASSR thresholds. DPOAEs could be absent with any level of hearing while most children with present DPOAEs were found to have average thresholds of 20 dB or under. The maximum average hearing level for a child with 5 DPOAE points present was 36.25 dB. Sixty-two ears demonstrated both 6 points present on DPOAE and normal tympanometry. These were found to have average hearing levels of 14 dB or less.
The average thresholds in the normally-hearing group are 4.01 and 6.32 dB eHL for ASSR and ABR, respectively. The mean difference of 2.31 dB is statistically significant by paired t test (p < 0.001). The relationship between age and threshold in the normally-hearing group showed a slow decline (improvement) in thresholds with age from 0.7 to 53 months. The regression equation for ABR was y = 6.47 − 0.01 × x and for ASSR was y = 4.43 − 0.05x, where x is average threshold and y is age in months.
When evaluating electrophysiologic threshold measures, an excellent way to compare data across studies is to isolate the thresholds produced by normally-hearing subjects in each study. Our normally-hearing children revealed ASSR thresholds (SDs) of 25.0 (6.9), 16.0 (7.3), 7.8 (5.7), and 6.3 (6.8) dB nHL for 500, 1000, 2000, and 4000 Hz, respectively. By ABR, normally-hearing children revealed thresholds (SDs) of 20.19 (4.8), 13.1 (3.8), 10.1 (1.5), and 10 (0) dB nHL for 5000, 1000, 2000, and 4000 Hz, respectively.
Figure 11 shows threshold results for normally-hearing infants and children using ASSR from ours and 13 prior studies that utilized a wide variety of stimulus, recording and detection parameters. Results from the normally-hearing participants in the present study demonstrated lower ASSR thresholds than all other studies except for Rodrigues and Lewis (2014) who used the same “Next Generation” technology. The ABR thresholds produced by normally-hearing participants in this study are in good agreements with a meta-analysis by Stapells (2000) at 500 Hz and are 2 to 3 dB lower at 1000 to 4000 Hz.
Comparison of Thresholds
The first experimental question of this study was “When using NB CE-Chirp stimuli for both, does Second Generation ASSR detection technology (as implemented in the Interacoustics Eclipse) reveal frequency-specific threshold predictions that are equivalent to those found by ABR (using the FMP automated detection method)?” Every effort was made to avoid any bias toward either technique including the randomization of test order.
Table 3 and Figure 5 indicate that the thresholds found by the two techniques were highly correlated with r2 values ranging from 0.769 to 0.963. Regression slopes range from 0.79 to 0.97 indicating that the relationship between the two measures were reasonably consistent across levels. However, regression shifts (Table 3) and threshold difference scores (Table 4) indicated that ASSR thresholds are consistently lower than ABR thresholds. The differences were largest at 500 Hz and progressively lower with frequency. Statistically, the threshold values were found to be different for all comparisons except 4000 Hz when all data are included. However, statistical significance in this regard is not the most relevant factor. The actual question is whether a clinician would feel that one of these tests could substitute for the other reliably. To address this question, the Bland and Altman (1995) method was applied.
The Bland–Altman method recommends that for equivalent techniques, 95% of data points should fall within 2 SDs of the mean difference score on their plots. Evaluation of the Bland–Altman plots in Figure 6 shows that more than 5% of the data points are outside the ±1.96 SD lines for the data at 500, 1000, and 2000 Hz but not for 4000 Hz.
The results from these analyses indicated that ASSR and ABR thresholds as evaluated in this study are equivalent only at 4000 Hz. Both paired t tests and the Bland–Altman analysis indicate that we cannot consider the two techniques to reveal the “equivalent” thresholds for 500, 1000, or 2000 Hz. At these frequencies, the ASSR revealed lower thresholds than the ABR. Lower thresholds in this context would be considered closer to “real or behavioral” thresholds and more sensitive.
The finding from this study that threshold estimations are lower by ASSR than by ABR is opposite to some previous findings in children (Rance et al. 2006; Van Maanen & Stapells 2010). The largest discrepancy between ABR and ASSR for Van Maanen and Stapells (2010) was at 500 Hz with ABR thresholds lower by an average of 10.7 dB. In contrast, this study found ASSR thresholds at 500 Hz to be more sensitive by an average of 9.35 dB. Therefore, the difference between studies in sensitivity of ASSR thresholds re ABR at 500 Hz is 20 dB which is substantial.
The correction factors at 500 Hz used in this study are 10 dB greater for ASSR than for ABR for thresholds of 45 dB or less. These have been recommended by the manufacturer and ASSR corrections are based on published data (Rodrigues et al. 2010) However, correction factors are complicated and dependent on many factors, particularly for ABR where protocols and detection routines are not standardized. Corrections for ABR are based on data from the United Kingdom (Stevens et al. 2013) where the protocols are slightly different. It is possible that correction factors contributed slightly to the discrepancies between ABR and ASSR found in this study.
The 20 dB increase in ASSR sensitivity at 500 Hz must be attributed to a combination of amplitude advantage afforded by the NB CE-Chirp and next-generation improvements in response detection. Five hundred Hertz has always been a difficult frequency for ASSR detection and was the focus of the study by Stürzebecher et al. (2006). This study showed the systematic improvement in detection of the 500 Hz stimulus by (1) changing from standard amplitude modulation stimulus to a 7-cosine series with modulation rate determined by the frequency spacing. The detection improved further when (2) a phase correction was applied to the cosines which imposed the appropriate cochlear delay time and improved even more when (3) a simple frequency offset was applied to the series, eliminating overlap of the cosines with the modulation harmonics used for detection. Later, Stürzebecher and Cebulla (2013) found that the table lookup for determining critical test values showed the greatest benefit in detection at 500 Hz. Certainly, the improved performance of the “Next Generation” ASSR in detection of the 500 Hz threshold can be attributed to the attention paid to this goal.
This study differs from previous comparisons of ABR and ASSR in that it employed an objective criterion, FMP, for response detection of ABR. Visual detection was also considered in the final decisions regarding threshold by ABR but very few discrepancies were noted. Consequently, ABR thresholds from this study should be in close agreement with other studies or slightly lower due to the increased averaging time allowed. As noted, the ABR thresholds achieved in this study are in agreement or very slightly better than those of the meta-analysis of Stapells (2000). This finding would lend credibility to the FMP as it agrees favorably with good “visual detection” used in the studies of the meta-analysis.
The FMP was particularly useful in determining when to stop averaging. However, if there was a discrepancy between the yes-no decision of a response by visual and FMP methods, the first author would decide. For example, the original noise-stopping rule terminated an average when the background noise reached 20 nV. This led to the stopping of several near threshold runs before the FMP criterion was reached, even though a small but clear response was present. In those cases, if a clear response was noted, the threshold was adjusted to the stopped level rather than one step above. A noise-stopping rule of 15 nV is now recommended. This discrepancy only happened near threshold where the amplitude of the response was small causing a slow rise in the FMP curve. In three other cases, electrical interference distorted waveforms and FMP values were artificially inflated and did not agree with visual detection. These cases were excluded from the analysis. After an external isolation transformer was installed, the interference did not reoccur.
Another reason why the FMP protocol should have produced accurate thresholds is that testing continued, when necessary, for longer periods of time than are generally used in ABR studies. The maximum number of sweeps was set to 6000 and this could be extended by the tester if it appeared that a pass by FMP was imminent. Typical protocols continue to 2000 sweeps and some to 3000 or 4000 which may not be adequate to resolve a very small response at threshold (Sininger 1993). This is apparent from the number of sweeps needed to achieve an adequate response at threshold being 2181 on average with a range from 800 to 8000.
The second experimental question was whether there was a significant time advantage for ASSR when compared with ABR. The data indicate that, on average, the full audiogram (4 frequencies per ear) could be estimated in 19.71 min for ASSR and 32.38 min for ABR. This represents a 13.28 min and 41% time decrease for ASSR over ABR. These differences are statistically significant (p < 0.00) but also clinically significant. It is important to note that the largest time savings of ASSR over ABR was found for children under anesthesia where ABR average time was 40.47 min while ASSR was 19.62 which represents a 52% decrease in test time. Given the concerns with and costs of anesthesia, any decrease in test time is important. It is not certain why test time for ASSR did not change from natural sleep to anesthesia conditions. Because the test time for ASSR is under 20 min, it is possible that the natural sleeping child has ample time to be fully asleep and quiet for the entire test, much like under anesthesia.
Van Maanen and Stapells (2009) used ASSR with simultaneous four-frequency stimulation bilaterally to evaluate a group of normally-hearing infants previously tested by ABR. They reported ASSR test times as the time spent making an assessment (all frequencies and ears) at a single stimulus level. The average time per level was 6.3 min with a SD of 3.10. They also state that one to six intensities were recorded per infant. By interpolation, an average of 3.5 intensities at 6.3 min would be 22.05 min for the ASSR assessment in the normally-hearing infants which is slightly longer but in the same range of the 15.31 min (SD = 6.71) found in this study. In another study that utilized the same equipment as the current one, Venail et al. (2015) evaluated children with hearing loss and reported an average test time of 22.90 min, very close to the average 19.71 min found here. Vander Werff (2009) reported test times from adult subjects, both normally hearing and with hearing loss while comparing analysis techniques both with simultaneous binaural simulation. The average test times for 4-frequency thresholds in both ears were 46.1 and 43.6 min for the 2 techniques but test times were faster for normally-hearing subjects. Mueller et al. (2012) reported ASSR test times for adults with and without hearing loss using and an Eclipse system and found an average of 18.6 min overall with normally-hearing subjects being tested somewhat more quickly (16.1) min.
Overall, the test times for this study are well in line with most and faster than some. The Eclipse system has a feature that allows independence of frequency and levels during testing while other systems will not change stimulus level until all frequencies are ready to do so. The latter would increase the testing time.
The automated protocols of ASSR should lead to greater consistency across labs and clinics on any given model of equipment. The short test times reported here were expected as a benefit of the protocol used in this study. Testing started with an “estimate” of overall threshold levels obtained by ABR with a broad-band CE-Chirp. ASSR threshold searches for all frequencies then started with levels at or just above this threshold. The protocol also called for elimination of the 10-dB step in favor of intelligent bracketing using time-to-response as an indicator of sensation level; an ASSR that registers a response in less than a minute is likely well above threshold whereas those that require 5 min or so many be close to threshold. The protocol also called for DPOAEs and multifrequency tympanometry before electrophysiological testing. Testers expected a child with normal tympanometry and present DPOAEs and a 10 or 20 dB broad-band chirp threshold to have excellent hearing and moderate or high level thresholds were avoided during testing.
Regardless of test times being longer for ABR than ASSR, the times reported for ABR are considered excellent by most clinical standards and are clearly lower than many reported in the literature. Janssen et al. (2010) found the mean test time for an ABR protocol nearly equivalent to the one used here, to be 54.6 min compared with our finding of 32.38 min. It should be noted that the test times from this study are prorated to estimate the time needed to complete eight thresholds making the time differences even more dramatic. All 8 thresholds were obtained by ABR in 83% of subjects and 90% of subjects had 6 or more thresholds completed. For ASSR, all 8 thresholds were completed in 87% subjects and 91% had 6 or more thresholds completed.
Data from Janssen et al. (2010) on test times can be assumed to be average sleep times. The average time in natural sleep for infants was 48.4 min. The combined average times for ABR and ASSR in the present study was 52.08 min which helps to explain why both tests could be completed in 1 session for 82 subjects. It should not be necessary in a clinical setting to use both frequency-specific ABR and ASSR, but it is encouraging to know either test is estimated to take well under the expected natural sleep time.
The amplitude advantage of the NB CE-Chirp over traditional tone bursts will produce a larger response SNR that can meet a specified criterion in a shorter amount of time. While Ferm et al. (2013) employed averaging using a fixed number of sweeps (3000), they did find that the resulting FMP for NB CE-Chirp ABRs was more than twice that of the tone pip responses and acknowledged the time savings that this could afford when stopping on an SNR rule as FMP does.
The same protocol features that are mentioned for ASSR also reduced test time for the ABR. In addition, as is traditional with the ASSR, ABR averages were not repeated unless they were highly questionable. Rather than needing to see replication, the testers relied on the statistical FMP along with visual recognition of a response, for verification. Split-half averages could be viewed as well. This feature of the protocol has the potential to cut testing time in half.
Finally, the use of a statistical detection criterion has the distinct advantage of determining the number of sweeps needed to achieve a response, or a nonresponse for the exact conditions (ABR amplitude and background noise) being tested. Compared with traditional fixed sweep protocols, less averaging time is needed for suprathreshold testing and more time will be spent averaging near threshold. This has the added advantage of lowering the threshold of the response which could be lost from insufficient averaging in a fixed sweep protocol.
Test times reported here include only the actual electrophysiologic testing. Preliminary testing including wideband tympanometry, DPOAEs, and Broad-Band CE-Chirp thresholds was performed on most subjects as well. Only the chirp threshold, however, required the child to be asleep. The test time did not include any waveform marking for latency or amplitude which was done after the program timer was off. If a full audiogram can be predicted in less than 20 min, and the average sleep time is 48 min, the additional sleep time may be available for other valuable tests such as real ear to coupler measures or even for parent counseling. Most important is the very realistic expectation that the audiogram prediction can be achieved in one visit thus avoiding the chain reaction discussed in the introduction.
This study confirms what others have found that children with normal hearing can be tested in less time than their counterparts with hearing loss. This is shown in Figure 8 for both techniques. Figure 10 shows how the number of sweeps needed to reach threshold by ABR increases with hearing loss.
Half of the children evaluated including 49% of those referred by NHS were found to have normal hearing in both ears. This has been seen in previous studies (Janssen et al. 2010) and is consistent with clinical reports. The protocol for this study did not include searching to true threshold but was tested at levels below those used to define normal hearing in other places, for example Canada. We tested down to 20 dB nHL at 500 but correction factors would yield threshold predictions of 5 dB eHL for ABR and 0 dB eHL for ASSR at that level. No thresholds were corrected below 0 eHL. Corrected thresholds for 1000 Hz at 10 dB were 0 dB eHL for both techniques and 5 dB eHL for 2000 and 4000 Hz for both techniques. These excellent thresholds were predicted on average in 24.62 min for ABR and 15.31 min by ASSR. While these are not “true” thresholds, they are very close to 0 dB and stopping represented a trade-off regarding test time. Establishing normal responses that are close to threshold is certainly preferable to a “screening” type measure where the threshold is essentially unknown. Children who need follow-up in the future will have a true baseline on which to judge any changes in hearing, mild asymmetries can be revealed and without time restrictions there seems to be no good reason not to test at low levels. This, of course, is a clinical decision but may be viewed more positively if time constraints are reduced.
Having the DPOAE and tympanometry information ahead of time was valuable in terms of planning the full electrophysiologic assessment. Absent DPOAEs at all frequencies was not found to be a good predictor of hearing levels but present ones were. Also, in the decision regarding whether to use test time for bone conduction measures, the wideband tympanometry can be very helpful. Bone conduction was often omitted in the test battery of this study. It was employed for 11 cases and tested with a wideband CE-Chirp by ABR. Nine cases had confirmed sensorineural hearing loss by bone conduction, one was clearly conductive and one was inconclusive. This study had time constraints due to the need to test both technologies in the experimental protocol. In a clinical test battery, where either ABR or ASSR (but not both) is used, there should be adequate time for a complete assessment of bone conduction when thresholds are elevated.
Figure 11 reveals the wide variations in ASSR results from the past. The spread of values for “normal” thresholds predicted by ASSR is as much as 40 dB or more with stimuli calibrated in nHL. These results certainly have contributed to a lack of confidence in the ASSR technique. There appears to be a lowering of the thresholds with time, based on the dates of the studies, which must relate to improvements in technique particularly for response detection. This figure should reassure users of ASSR that a lack of sensitivity seen in some implementations of the technique are not inherent in the ASSR strategy, but simply represent detection technology that was not fully developed.
The results from this study (right and left ears) and Rodrigues and Lewis (2014) are clearly lower than found in other studies, nearly identical and both used the “Next Generation” detection and NB CE-Chirp stimuli with the Eclipse system. The reason for slightly higher thresholds found in this study relative to Rodrigues and Lewis relates to the 10 dB nHL stopping rule for 2000 and 4000 Hz while Rodrigues and Lewis sought true thresholds. The thresholds for 500 and 1000 are nearly identical.
One other study, Michel and Jørgensen (2017) used the same technology as this study for a group of children with hearing loss and normal hearing and yet, their normally-hearing group demonstrated higher thresholds than this study or Rodrigues and Lewis (2014; see Fig. 19). For their normal group of infants <12 weeks of age, they found thresholds of 30, 25, 20, and 15 dB nHL for 500, 1000, 2000, and 4000 Hz, respectively. Older normally-hearing children had slightly higher thresholds in their study. Careful reading of the Michel and Jørgensen (2017) study finds that assessments of the normally-hearing group were stopped before reaching threshold as they were “found to have normal hearing.” This is the only possible explanation for the differences as other methods were consistent with this study.
There are many possible reasons why this study found lower thresholds for normally-hearing children than others and certainly, whether threshold is truly sought, or testing stops at suprathreshold levels was a factor. The acoustic environment of the testing, the type of stimulus used, and the age of subjects can all influence thresholds obtained with ASSR along with many other factors. The NB CE-Chirp undoubtedly contributed to low thresholds. The sensitivity of the detection algorithm and control of maximum allowable noise levels, however, may have had the largest influence. The features of what we call “Next Generation” detection, including the assessment at 12 modulation harmonics, rather than one, and the use of both phase and amplitude information, rather than one or the other as well as the careful calculation of appropriate test criterion all must contribute to the speed, accuracy, and sensitivity of this ASSR system.
The ABR thresholds from normally-hearing infants in this study are in line with previous studies. Our thresholds ranged from 10 to 20.1 dB nHL before corrections. Stapells et al. (1995) found thresholds of 13.2 to 15.9 dB nHL and Sininger et al. (1997) had a range from 6 to 16 dB n HL for normally-hearing infants. The agreement among these studies is good although the latter two included threshold searches to 0 dB while the present study stopped at low, but suprathreshold levels.
The consistency of automated detection as implemented with any given ASSR technology is a factor that should be considered when deciding whether to utilize ABR or ASSR. Clinicians can expect to have the accuracy and test time results seen in this study when utilizing the same technology for testing, given that good testing technique and environment are maintained. However, unless the nontraditional protocol for ABR was adopted, it is not clear that an audiologist could expect the good ABR results that are presented here. In addition to improved accuracy and speed, the use of ASSR will make testing more consistent across clinics and testers.
In conclusion, this study demonstrated that both ABR with automated detection and Next Generation ASSR, each using NB CE-Chirp stimuli, give consistent predictions of audiometric thresholds in a time frame that is reasonable for testing nonsedated infants and toddlers. ASSR as executed in this study will produce lower (better) thresholds in considerably less time and should be considered an excellent choice for electrophysiologic audiometric testing.
The authors acknowledge funding for this study from the Oticon Foundation of Denmark. The authors thank the conscientious audiology staff members who provided feedback on protocols and patient data, including Sue Windmill, AuD, Carrie Wingo, AuD, Kelly Baroch, AuD and Gayle Riemer, MA in Cincinnati, Emily Spitzer, BS, Lauren Okulski, AuD, Shana Jacobs, AuD. Lauren Johnson, AuD, Mallory Baker, AuD, and Sarah Martino, AuD in Chapel Hill and Erica Schicke, AuD and Tamara Scott, AuD in Denver. Study coordinators were invaluable in enrolling subjects and managing information. Amanda Ruiz served as study coordinator in Denver and Morgan Bamberger, MS, was coordinator in Cincinnati. Jane Gralla, University of Colorado, provide invaluable advice on statistical analyses.
Attias J., Karawani H., Shemesh R., et al. Predicting hearing thresholds in occupational noise-induced hearing loss
by auditory steady state responses. Ear Hear, 2014). 35, 330–338.
Bland J. M., Altman D. G. Comparing methods of measurement: Why plotting difference against standard method is misleading. Lancet, 1995). 346, 1085–1087.
Casey K. A., Small S. A. Comparisons of auditory steady state response
and behavioral air conduction and bone conduction thresholds for infants and adults with normal hearing. Ear Hear, 2014). 35, 423–439.
Cebulla M., Elberling C. Auditory brain stem responses evoked by different chirps based on different delay models. J Am Acad Audiol, 2010). 21, 452–460.
Cebulla M., Stürzebecher E. Automated auditory response detection: Further improvement of the statistical test strategy by using progressive test steps of iteration. Int J Audiol, 2015). 54, 568–572.
Cebulla M., Stürzebecher E., Elberling C. Objective detection of auditory steady-state responses: Comparison of one-sample and q-sample tests. J Am Acad Audiol, 2006). 17, 93–103.
Cone-Wesson B., Dowell R. C., Tomlin D., et al. The auditory steady-state response: Comparisons with the auditory brainstem response
. J Am Acad Audiol, 2002a). 13, 173–187.
Cone-Wesson B., Rickards F., Poulis C., et al. The auditory steady-state response: Clinical observations and applications in infants and children
. J Am Acad Audiol, 2002b). 13, 270–282.
Dau T., Wegner O., Mellert V., et al. Auditory brainstem responses with optimized chirp signals compensating basilar-membrane dispersion. J Acoust Soc Am, 2000). 107, 1530–1540.
de Boer E. A cylindrical cochlea model: The bridge between two and three dimensions. Hear Res, 1980). 3, 109–131.
Don M., Elberling C. Evaluating residual background noise in human auditory brain-stem responses. J Acoust Soc Am, 1994). 96(5 Pt 1), 2746–2757.
Don M., Elberling C. Use of quantitative measures of auditory brain-stem response peak amplitude and residual background noise in the decision to stop averaging. J Acoust Soc Am, 1996). 99, 491–499.
Don M., Elberling C., Waring M. Objective detection of averaged auditory brainstem responses. Scand Audiol, 1984). 13, 219–228.
Elberling C., Don M. Quality estimation of averaged auditory brainstem responses. Scand Audiol, 1984). 13, 187–197.
Elberling C., Don M. Auditory brainstem responses to a chirp stimulus designed from derived-band latencies in normal-hearing subjects. J Acoust Soc Am, 2008). 124, 3022–3037.
Elberling C., Don M. A direct approach for the design of chirp stimuli used for the recording of auditory brainstem responses. J Acoust Soc Am, 2010). 128, 2955–2964.
Elberling C., Wahlgreen O. Estimation of auditory brainstem response
, ABR, by means of Bayesian inference. Scand Audiol, 1985). 14, 89–96.
Elberling C., Callo J., Don M. Evaluating auditory brainstem responses to different chirp stimuli at three levels of stimulation. J Acoust Soc Am, 2010). 128, 215–223.
Elberling C., Don M., Cebulla M., et al. Auditory steady-state responses to chirp stimuli based on cochlear traveling wave delay. J Acoust Soc Am, 2007). 122, 2772–2785.
Ferm I., Lightfoot G. Further comparisons of ABR response amplitudes, test time, and estimation of hearing threshold using frequency-specific chirp and tone pip stimuli in newborns: Findings at 0.5 and 2 kHz. Int J Audiol, 2015). 54, 745–750.
Ferm I., Lightfoot G., Stevens J. Comparison of ABR response amplitude, test time, and estimation of hearing threshold using frequency specific chirp and tone pip stimuli in newborns. Int J Audiol, 2013). 52, 419–423.
Firszt J. B., Gaggl W., Runge-Samuelson C. L., et al. Auditory sensitivity in children
using the auditory steady-state response. Arch Otolaryngol Head Neck Surg, 2004). 130, 536–540.
Holte L., Walker E., Oleson J., et al. Factors influencing follow-up to newborn hearing screening for infants who are hard of hearing. Am J Audiol, 2012). 21, 163–174.
Janssen R. M., Usher L., Stapells D. R. The British Columbia’s Children
’s Hospital tone-evoked auditory brainstem response
protocol: How long do infants sleep and how much information can be obtained in one appointment? Ear Hear, 2010). 31, 722–724.
JCIH. (Year 2007 Position Statement: Priniciples and Guidelines for Early Hearing Detection and Intervention Programs. Pediatrics, 2007). 120, 23.
John M. S., Brown D. K., Muir P. J., Picton T. W. Recording auditory steady-state responses in young infants. Ear Hear, 2004). 25, 539–553.
Korczak P., Smart J., Delgado R., et al. Auditory steady-state responses. J Am Acad Audiol, 2012). 23, 146–170.
Kristensen S. G., Elberling C. Auditory brainstem responses to level-specific chirps in normal-hearing adults. J Am Acad Audiol, 2012). 23, 712–721.
Levi E. C., Folsom R. C., Dobie R. A. Coherence analysis of envelope-following responses (EFRs) and frequency-following responses (FFRs) in infants and adults. Hear Res, 1995). 89, 21–27.
Lins O. G., Picton T. W., Boucher B. L., et al. Frequency-specific audiometry using steady-state responses. Ear Hear, 1996). 17, 81–96.
Luts H., Desloovere C., Kumar A., et al. Objective assessment of frequency-specific hearing thresholds in babies. Int J Pediatr Otorhinolaryngol, 2004). 68, 915–926.
McCreery R. W., Kaminski J., Beauchaine K., et al. The impact of degree of hearing loss
on auditory brainstem response
predictions of behavioral thresholds. Ear Hear, 2015). 36, 309–319.
Michel F., Jørgensen K. F. Comparison of threshold estimation in infants with hearing loss
or normal hearing using auditory steady-state response evoked by narrow band CE-chirps and auditory brainstem response
evoked by tone pips. Int J Audiol, 2017). 56, 99–105.
Muhler R., Mentzel K., Verhey J. Fast hearing-threshold estimation using multiple auditory steady-state responses with narrow-band chirps and adaptive stimulus patterns. Sci World J, 2012). 2012, .
Petoe M. A., Bradley A. P., Wilson W. J. On chirp stimuli and neural synchrony in the suprathreshold auditory brainstem response
. J Acoust Soc Am, 2010). 128, 235–246.
Rance G., Rickards F. Prediction of hearing threshold in infants using auditory steady-state evoked potentials. J Am Acad Audiol, 2002). 13, 236–245.
Rance G., Tomlin D., Rickards F. W. Comparison of auditory steady-state responses and tone-burst auditory brainstem responses in normal babies. Ear Hear, 2006). 27, 751–762.
Rance G., Roper R., Symons L., et al. Hearing threshold estimation in infants using auditory steady-state responses. J Am Acad Audiol, 2005). 16, 291–300.
Rickards F. W., Tan L. E., Cohen L. T., et al. Auditory steady-state evoked potential in newborns. Br J Audiol, 1994). 28, 327–337.
Rodrigues G. R., Lewis D. R. Establishing auditory steady-state response thresholds to narrow band CE-chirps(®) in full-term neonates. Int J Pediatr Otorhinolaryngol, 2014). 78, 238–243.
Rodrigues G. R. I., Lewis D. R., Fichino S. N. Steady-state auditory evoked responses in audiological diagnosis in children
: A comparison with brainstem evoked auditory responses. Braz J Otorhinolaryngol, 2010). 76, 96–101.
Rodrigues G. R. I., Ramos N., Lewis D. R. Comparing auditory brainstem responses (ABRs) to toneburst and narrow band CE-chirp in young infants. Int J Pediatr Otorhinolaryngol, 2013). 77, 1555–1560.
Savio G., Cárdenas J., Pérez Abalo M., et al. The low and high frequency auditory steady state responses mature at different rates. Audiol Neurootol, 2001). 6, 279–287.
Sininger Y. S. Auditory brain stem response for objective measures of hearing. Ear Hear, 1993). 14, 23–30.
Sininger Y. S., Abdala C., Cone-Wesson B. Auditory threshold sensitivity of the human neonate as measured by the auditory brainstem response
. Hear Res, 1997). 104, 27–38.
Stapells D. R. Threshold estimation by the tone-evoked auditory brainstem response
: A literature meta-analysis. J Speech Language Pathol Audiol, 2000). 24, 9.
Stapells D. R., Gravel J. S., Martin B. A. Thresholds for auditory brain stem responses to tones in notched noise from infants and young children
with normal hearing or sensorineural hearing loss
. Ear Hear, 1995). 16, 361–371.
Stevens J., Sutton G., Wood S. Guidelines for the early audiological assessment and management of babies referred from the Newborn Hearing Screening Programme Version 3.1. National Health Service, Screening Programmes:Newborn Hearing, 2013). 44.
Stürzebecher E., Cebulla M. Automated auditory response detection: Improvement of the statistical test strategy. Int J Audiol, 2013). 52, 861–864.
Stürzebecher E., Cebulla M., Elberling C. Automated auditory response detection: Statistical problems with repeated testing. Int J Audiol, 2005). 44, 110–117.
Stürzebecher E., Cebulla M., Pschirrer U. Efficient stimuli for recording of the amplitude modulation following response. Audiology, 2001). 40, 63–68.
Stürzebecher E., Cebulla M., Wernecke K. Objective response detection in the frequency domain: Comparison of several q-sample tests. Audiol Neurootol, 1999). 4, 2–11.
Stürzebecher E., Cebulla M., Elberling C., et al. New efficient stimuli for evoking frequency-specific auditory steady-state responses. J Am Acad Audiol, 2006). 17, 448–461.
Swanepoel D., Ebrahim S. Auditory steady-state response and auditory brainstem response
thresholds in children
. Eur Arch Otorhinolaryngol, 2009). 266, 213–219.
Swanepoel d. e. W., Steyn K. Short report: Establishing normal hearing for infants with the auditory steady-state response. S Afr J Commun Disord, 2005). 52, 36–39.
Van Maanen A., Stapells D. R. Normal multiple auditory steady-state response thresholds to air-conducted stimuli in infants. J Am Acad Audiol, 2009). 20, 196–207.
Van Maanen A., Stapells D. R. Multiple-ASSR thresholds in infants and young children
with hearing loss
. J Am Acad Audiol, 2010). 21, 535–545.
Vander Werff K. R. Accuracy and time efficiency of two ASSR analysis methods using clinical test protocols. J Am Acad Audiol, 2009). 20, 433–452.
Venail F., Artaud J. P., Blanchet C., et al. Refining the audiological assessment in children
using narrow-band CE-Chirp-evoked auditory steady state responses. Int J Audiol, 2015). 54, 106–113.
Keywords:Copyright © 2018 Wolters Kluwer Health, Inc. All rights reserved.
Auditory brainstem response; Auditory steady state response; Children; Hearing loss