ARL-TR-7958 ● APR 2017

US Army Research Laboratory

Critical Examination of the Article Impulse 

Noise Injury Prediction Based on the Cochlear 

Energy by Zagadou, Chan, Ho, and Shelly

by G Richard Price, Joel T Kalb, and Charles R Jokel

Approved for public release; distribution is unlimited.
NOTICES

Disclaimers

The findings in this report are not to be construed as an official Department of the 

Army position unless so designated by other authorized documents.

Citation of manufacturer’s or trade names does not constitute an official 

endorsement or approval of the use thereof.

Destroy this report when it is no longer needed. Do not return it to the originator.
ARL-TR-7958 ● APR 2017

US Army Research Laboratory

Critical Examination of the Article Impulse 

Noise Injury Prediction based on the Cochlear 

Energy by Zagadou, Chan, Ho, and Shelly

by G Richard Price and Joel T Kalb

Human Research and Engineering Directorate, ARL

Charles R Jokel

US Army Public Health Center, APG (Provisional)

Approved for public release; distribution is unlimited.
ii

REPORT DOCUMENTATION PAGE Form Approved

OMB No. 0704-0188

Public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the 

data needed, and completing and reviewing the collection information. Send comments regarding this burden estimate or any other aspect of this collection of information, including suggestions for reducing the 

burden, to Department of Defense, Washington Headquarters Services, Directorate for Information Operations and Reports (0704-0188), 1215 Jefferson Davis Highway, Suite 1204, Arlington, VA 22202-4302. 

Respondents should be aware that notwithstanding any other provision of law, no person shall be subject to any penalty for failing to comply with a collection of information if it does not display a currently valid 

OMB control number.

PLEASE DO NOT RETURN YOUR FORM TO THE ABOVE ADDRESS.

1. REPORT DATE (DD-MM-YYYY)

April 2017

2. REPORT TYPE

Technical Report

3. DATES COVERED (From - To)

February 2016–March 2017

4. TITLE AND SUBTITLE

Critical Examination of the Article Impulse Noise Injury Prediction Based on 

the Cochlear Energy by Zagadou, Chan, Ho, and Shelly

5a. CONTRACT NUMBER

5b. GRANT NUMBER

5c. PROGRAM ELEMENT NUMBER

6. AUTHOR(S)

G Richard Price, Joel T Kalb, and Charles R Jokel

5d. PROJECT NUMBER

5e. TASK NUMBER

5f. WORK UNIT NUMBER

7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES)

US Army Research Laboratory

ATTN: RDRL-HRF-C

Aberdeen Proving Ground, MD 21005-5425

8. PERFORMING ORGANIZATION REPORT NUMBER

ARL-TR-7958

9. SPONSORING/MONITORING AGENCY NAME(S) AND ADDRESS(ES) 10. SPONSOR/MONITOR'S ACRONYM(S)

11. SPONSOR/MONITOR'S REPORT NUMBER(S)

12. DISTRIBUTION/AVAILABILITY STATEMENT

Approved for public release; distribution is unlimited.

13. SUPPLEMENTARY NOTES

14. ABSTRACT

In an article claiming to produce an improved damage risk criterion for human exposure to intense impulsive sounds, Zagadou, 

Chan, Ho, and Shelly critiqued the Auditory Hazard Assessment Algorithm for Humans (AHAAH) model used by the US 

Department of Defense (DOD) in assessing noise hazard and also proposed an alternative. Their approach required that they 1) 

improve the fit of AHAAH to the transfer functions, 2) reproduce the stimulating conditions in the Albuquerque Studies (AS), 

record pressure histories at the eardrum position of a manikin, and 3) produce a better predictive algorithm. Unfortunately, they 

succeeded in none of their aims. They did not in fact use the DOD program but rather some unknown variant. The model they 

did create had a demonstrably worse fit to the transfer functions. For a variety of reasons, they did not reproduce the stimulating 

conditions in the AS. The acoustic data they published are rife with serious artifacts and cannot be considered a replication of 

the AS data. Finally, we have shown that the interpretation of the data and the analytical procedures simply ignored relevant

data on the ear’s response to intense sounds. They consistently made assumptions, creating “data” that contained biases in the 

direction of energy explaining everything—a problem of logical circularity.

15. SUBJECT TERMS

hearing damage risk criteria, impulse noise, Auditory Hazard Assessment Algorithm for Humans, AHAAH, Albuquerque 

Studies

16. SECURITY CLASSIFICATION OF:

17. LIMITATION

 OF

 ABSTRACT

UU

18. NUMBER

 OF 

 PAGES

34

19a. NAME OF RESPONSIBLE PERSON

G Richard Price

a. REPORT

Unclassified

b. ABSTRACT

Unclassified

c. THIS PAGE

Unclassified

19b. TELEPHONE NUMBER (Include area code)

410-278-5984

Standard Form 298 (Rev. 8/98)

Prescribed by ANSI Std. Z39.18
Approved for public release; distribution is unlimited.

iii

Contents

List of Figures v

1. Introduction 1

2. The Non-Problem of the “Non-Monotonic” Response 2

3. Problems with the Model’s Variables? 3

3.1 Basic Understanding 4

3.2 Middle Ear Muscle Latency Inaccuracy 4

3.3 Overlooking Insights from Animal Tests 5

4. The Non-Improvement Improvement 6

5. The Stapes Displacement Problem 6

6. Nonuse of the AHAAH Model 6

7. Non-Improvement of AHAAH-PK 8

8. Non-Replication of the AS Pressure Histories 10

8.1 Measurement Issues 10

8.1.1 Microphone Use 10

8.1.2 Apparatus 11

8.1.3 ATF Issues 11

8.1.4 Distorted Pressure Histories 12

9. Philosophical Issues 15

9.1 Experimental Technique 15

9.2 Assumed and Extrapolated Data 16

9.3 The Physiology of Loss 17

9.4 Middle Ear Muscle Activity 18

10. Conclusions 19
Approved for public release; distribution is unlimited.

iv

11. References 21

List of Symbols, Abbreviations, and Acronyms 24

Distribution List 25
Approved for public release; distribution is unlimited.

v

List of Figures

Fig. 1 Stapes velocity transfer functions for what Zagadou et al. claimed to 

be the original AHAAH model (AHAAH ZCHS) and the same

calculation with the actual AHAAH model (AHAAH PK)...................7

Fig. 2 Comparison of stapes velocity transfer functions for Zagadou et al.’s 

AHAAH-New, the original AHAAH (AHAAH PK), the human data 

of Aibara et al. and Kringlebotn and Gundersen ...................................9

Fig. 3 Eardrum pressure for 1 m, Level 1, from the ATF (blue curve) and the 

eardrum pressure calculated using the original AHAAH model (red 

curve) and the AS tragus data ..............................................................14

Fig. 4 Eardrum pressure for 1 m, Level 6, from the manikin (blue curve) and 

the eardrum pressure calculated using the original AHAAH model (red 

curve) and the AS tragus data ..............................................................15
Approved for public release; distribution is unlimited.

vi

INTENTIONALLY LEFT BLANK.
Approved for public release; distribution is unlimited.

1

1. Introduction

The ability to predict the hazard from very intense sounds typical of gunfire remains 

an active interest for many, including the armed forces, civilian sport shooters, law 

enforcement, industry, and society as a whole, who may be exposed to the intense 

noise of an automotive airbag deployment. The Auditory Hazard Assessment 

Algorithm for Humans (AHAAH) model is serving as the basis for such evaluations 

(SAE 2013; MIL-STD-1474E 2015) and is being considered as a basis for an 

American National Standards Institute (ANSI) standard for impulse noise exposure 

(ANSI S3.62 2017), the first of its kind. Consequently, when Zagadou, Chan, Ho, 

and Shelly (2016) proposed both major revisions to the current AHAAH model and 

immediate use of the revised model as a basis for hazard analysis, it was clearly 

appropriate to evaluate their proposals.

In reviewing their effort, we found that we had serious reservations at many places 

both with regard to the experimental work they did with their understanding and 

use of the AHAAH model, their interpretation of the work they report and the 

alternate model they propose. Our remarks here focus on the most critical issues, 

things that are essentially objective and affect the ultimate acceptance or rejection 

of their positions.

Zagadou et al. (2016) introduced their work by expressing concern for what they 

contended was the AHAAH model’s irrational performance in scaling the hazard 

within the Army’s Albuquerque Studies (AS). Namely, they contended that it 

behaved “non-monotonically” (i.e., higher peak pressures under some conditions 

involved lower predicted hazards). In their article, they proposed first to begin with 

an update of the variables in the model representing the ear’s physiology with the 

promise of improving the model’s fit to the appropriate transfer functions. They 

expected that these changes would correct what they argued was the irrational 

scaling for the AS stimuli. Second, they proposed to examine the improved model’s 

fit to the human data on threshold shift (TS) from intense impulses. The major 

portion of this part of their program was to reproduce exposure stimuli from the AS 

and expose an acoustic test fixture (ATF) at the subject locations. The ATF would 

be fitted with the various hearing protection devices (HPDs) used in the AS and 

pressure histories collected at the eardrum location of the ATF. Given their 

expressed intent to reproduce the AS stimuli, along with use of the HPDs from the 

AS, they felt they would be justified in interpreting the TS data from the subjects 

(Ss) in the AS studies using the acoustic data from the eardrum position of their 

ATF. No additional human exposures were conducted, so it was critical that the 

stimulating conditions of the AS be reproduced as closely as possible. Third, our 

comments address the proposals made by Zagadou et al. to adopt a newly created 
Approved for public release; distribution is unlimited.

2

energy-based model of hearing loss. Such proposal has the effect of losing most of 

the validating data that support the existing AHAAH model. The approach they do 

recommend is barely supported by very few pieces of data selected with a highly 

questionable rationale and other premises that are clearly counter to the hearing loss 

data appropriate to this high-intensity regime. 

We address, in turn, the problem of the “non-monotonic response”, the proposed 

improvements to the model, the replication of the acoustic data from the AS, and 

the revised model and its relationship to assessment of hearing loss. 

2. The Non-problem of the “Non-monotonic” Response

Zagadou et al.’s contention that the AHAAH model behaved irrationally was 

baseless and, in fact, the model’s predictions have been noted, found to be internally 

consistent, and, importantly, in line with hearing loss data (Price 2007, 2010). 

Specifically, for the 1- and 3-m exposures in the AS, the model did make the 

unusual prediction that the most-hazardous impulses would be in the middle of the 

intensity range (Level 4) and that the impulses with the higher peak pressures and 

energies would in fact be progressively less hazardous. It was perhaps a surprising 

prediction, but we believe that one of the functions of a model is to challenge 

preconceptions and produce insight into processes. In any event, the ultimate arbiter 

in these cases is data. If there were a problem with the model, a bad prediction 

would be evidence that something needed to be reformulated and tested, and a 

successful outcome would produce an improved model. However, Zagadou et al. 

skipped the evidence phase of this process (the model’s predictions in these cases 

had not been shown to be faulty), and they simply presumed the predictions of 

lower hazard for those particular impulses as evidence of obvious errors within the 

model.

The heart of the problem with Zagadou et al.’s analysis, we believe, is essentially 

its internal logic. They began with the premise that there could be no such thing as 

what they referred to as a “non-monotonic” prediction (i.e., a higher peak pressure 

with essentially the same A-duration must always produce an increase in hazard). 

Then much of their effort was guided by making a new version of the AHAAH 

model that would conform to that premise. We note that conformity with their 

premise was not data-driven—hearing loss data supporting it—or required by 

established scientific principle. The test of a premise, from the theoretician’s 

viewpoint, is whether or not it leads to accurate predictions. As we will see, the 

premise that the peak pressure level is controlling is simplistic and results in 

predictive errors. 
Approved for public release; distribution is unlimited.

3

The paradoxical reduction in hazard with increased peak pressure has not only been 

noted, discussed, and explained in talks and in print over a number of years 

(Price 2007), but it is also consistent with other impulses that produced similar 

outcomes (Nixon and Sommer 1973; Price 2003). For all the waveforms we have 

tested with the AHAAH model, if a waveform increases in sound pressure level

with no change in shape, the predicted hazard growth is indeed monotonic. The 

critical point in the case of the AS is that the waveforms changed shape with AS

Level, which explains the apparent non-monotonicity. At the higher AS Levels, the 

shape of the waveform was such that the low-frequency elements forced the stapes 

into clipping, which meant that fewer damaging oscillations were transmitted to the 

cochlea, and the prediction was that the impulse with the higher peak pressure was 

in fact safer for the ear. The model’s displays clearly demonstrate this phenomenon. 

We have no explanation as to how Zagadou et al. overlooked these publications 

and the logic supporting the contention, given that they cite an article that explained 

the very problem they purported to address (Price 2007).

Significantly, the data provide at least partial support for the prediction of reduced 

effect with increasing AS Level for the 1-m impulses. In the AS dataset, not all 

conditions in the stimulation matrix were in fact run, which means that the model’s 

prediction of decreasing hazard could not be fully tested. However, some of the 

data did apply. As predicted by the model, a lower-level impulse (1 m, Level 5) is 

in fact more hazardous than the next higher level (about 45% of the Ss showed loss 

at Level 5, decreasing to about 35% at Level 6) (Price 2007). More data would have 

been desirable, but these are consistent with the model’s insight. These data and the 

studies cited earlier all are consistent with the premise that higher peak pressure 

levels (even with similar spectra) are not necessarily associated with higher hazard. 

We conclude that the evidence so far is that the problem of non-monotonicity 

Zagadou et al. raised is in fact a non-problem. Yet, it was the underlying assumption 

that drove the proposed changes to the model and a basis for the claims by Zagadou 

et al. that they had improved the model. 

3. Problems with the Model’s Variables?

The first major project Zagadou et al. set out to accomplish was to improve the 

model’s performance by updating the physiological variables so that they better 

matched the human ear’s characteristics and thereby improved the model’s 

performance in calculating various transfer functions. The goal was worthwhile; 

however, valid tests require that the model being tested is understood and accurately 

used. Unfortunately, there is abundant evidence in their article that Zagadou et al. 

have neither understood the original model nor have they actually used it in their 

tests. In the following, we examine the specific questions.
Approved for public release; distribution is unlimited.

4

3.1 Basic Understanding

Consider first the question of their basic understanding of the model. In one 

instance they maintain that “the parameters of the current AHAAH model,

originally developed for the cat, were assigned to the human model by assuming 

that cats and humans have the same ear properties”. Their assertion is simply not

true. As an electroacoustic model of the ear, conformal with the ear’s physiology, 

the values in the original cat model were indeed appropriate to the cat ear. That 

model was developed to produce good fits to the transfer functions available for 

that ear (Kalb and Price 1987; Price and Kalb 1999). Beginning in the late 1980s,

the full software codes were shared with Dr Chan, one of the article’s authors,

through the workings of a North Atlantic Treaty Organization Research Study 

Group. The values of the parameters in the human model have always been 

appropriate to the human ear and produce good fits to the transfer functions for that 

ear. Because of the common physiology of mammalian ears, the cat and human 

models have a similar structure, but the specific values in the computational models 

are appropriate to each species. For some values in the model (about 20%), the 2 

ears were essentially the same (resting strain of the annular ligament, breaking 

strain of the annular ligament, damping/compliance ratio, etc.). In spite of the fact 

that the variables in the model are listed specifically in a coefficients file, Zagadou 

et al. seem to have not noticed that about 80% of the variables differ between the 

species, a point essential to understanding the essence of the model.

In the spirit of full disclosure, we note that we did incorporate the implicit 

assumption that the hair cell in the cat and the hair cell in the human are essentially 

similar structures and would respond to mechanical stress similarly. The hair cells’

microscopic anatomy is highly similar, and we know of no data that suggest that 

they behave differently. The model calculates basilar membrane displacement 

(which is the forcing function for hair cell displacement). Thus, when the transfer 

functions for the transmission of sound from air to the inner ear are right for each 

species, the assumption of similarity of hair cell properties allows the data from 

exposures to the cat ear to be interpreted with only a modest extrapolation to the 

human case. 

3.2 Middle Ear Muscle Latency Inaccuracy

In a second instance, they state that the maximum gain in the middle ear muscle 

response is “reached with a 9 ms delay”. That is simply not the case. It is true that 

there is a latent period of 9 ms before the middle ear muscle response begins (a 

short latency appropriate at the very high intensity of these impulses). However, 

the middle ear muscle response then grows exponentially with a time constant of 
Approved for public release; distribution is unlimited.

5

11.7 ms (both the latency and time constant are variables in the AHAAH model’s 

coefficients file). This time constant was developed based on the experiments of 

Dallos (1964) on the dynamics of the middle ear muscle reflex. Time to a full 

contraction is about 50 ms from the beginning of the contraction. It is difficult to 

see how Zagadou et al. could have missed these values because in addition to being 

in the coefficients file, they are also displayed graphically on every analysis done 

with the AHAAH model. 

3.3 Overlooking Insights from Animal Tests

There is another sense in which Zagadou et al. appear to not have understood the 

scientific strength of the AHAAH modeling approach. The conceptual structure of 

the approach is very important because it enabled real tests of the model with live 

ears and appropriate stimuli critical to its development and validation. In contrast, 

Zagadou et al., in the end, without discussing the intra-cochlear elements of the 

AHAAH model or providing evidence for shortcomings, recommend the use of 

intra-cochlear energy as the metric for hazard. Further, their position was based on 

very few pieces of TS data: 2 rifle fire exposures and the 28 ears that showed a TS

of 15 dB or greater in the AS (Price 2003). Understandably, there are essentially no 

human data in which real damage has been observed in experiments. But the history 

of experimental exposure of human ears is much greater than the studies Zagadou 

et al. cite (Price 2007). 

Fortunately for science, however, in developing the cat model, we were able to 

subject cat ears to real stresses for a variety of impulses that did produce varying 

degrees of loss in more than 200 ears (Price and Wansack 1989; Pierson et al. 1995; 

Price and Kalb 1999; Price 2003). That is the experimental basis that has produced 

the AHAAH model’s loss formula that connects calculated displacements to 

damage. For 12 different exposures to 12 groups of 10 pairs of cat ears, the 

correlation between the calculated value and the mean immediate TS for each group 

was r = 0.94 (Price 2003). Furthermore, the correspondence between the change in 

the auditory sensitivity was matched by hair cell losses (Price 2006). The very high 

correlation between the model’s predictions and actual losses indicated that the 

majority of the variance in the hearing loss data was being explained by the model, 

which in turn argued that it should be created in a human form and tested. The 

modeling approach ultimately recommended by Zagadou et al. simply ignores this 

work. It appears that Zagadou et al. simply missed this powerful method of 

connecting to the cat model and the considerable database associated with it.
Approved for public release; distribution is unlimited.

6

4. The Non-improvement Improvement

The authors also maintain that they have improved the model by getting the 

circumference of the human head correct (their Table 2). This assertion is truly 

baffling. The AHAAH model for the human ear has neither a head circumference 

nor a radius in its variables, so we are at a loss to understand what changes they 

actually made to whatever model they were working with. Within the AHAAH 

model, the acoustic effects of the head are calculated from the variables associated 

with the diffraction field around the head. It is one thing to overlook something in 

an account but quite another to positively assert it, especially when it is contrary to 

fact.

5. The Stapes Displacement Problem

Zagadou et al. claimed to have done a thorough analysis of the variables associated 

with the AHAAH model and improved its fit to the newest human data—a worthy 

exercise. The 7 changes to the middle ear elements they propose are found in their 

Table 2. 

One of the elements they “corrected” was the area of the stapes. Two comments 

apply. In changing from the centimeter-gram-second to the millimeter-kilogramsecond system of dimensions, they wound up with a stapes 100 times too large. We 

believe that the correct physical area of the stapes footplate for the human ear is 

3.2 mm2 (in the old system). The value we actually used in AHAAH was 2.1 mm2

, 

a deliberate choice to reflect what we believe is the effective area for a human stapes 

operating at very high amplitudes. The problem in the case of the human is that the 

annular ligament is not uniform in its width or thickness, with the often-observed 

result that the stapes’ motion is not piston-like but rocking (von Bekesy 1960; Gyo

et al. 1987; Heiland et al. 1999; Hato et al. 2003; Lauxmann et al. 2014). The 

rocking motion is likely to produce a radiation pattern that approaches that of a 

dipole, which is less effective than a simple piston. Therefore, in the interests of 

simplicity, sometimes held to be a scientific virtue, we opted to use a smaller area 

for the stapes’ footplate for calculations at these very high levels. Zagadou et al. 

seemed to have missed the problem of non-piston-like movement of the stapes at 

high pressure levels.

6. Non-use of the AHAAH Model

In the interests of scientific curiosity, we made their suggested changes to our copy 

of the original AHAAH model (AHAAH-PK) and ran it (correcting their area of 

the stapes to 3.2 mm2) hoping to be able to compare their version of the AHAAH 
Approved for public release; distribution is unlimited.

7

model with the original. Unfortunately for science, that was not to be, because we 

discovered that, apparently, they did not actually use the original AHAAH model. 

Their Fig. 13 portrays the calculation of the middle ear pressure gain for what they 

maintain is the original AHAAH model along with their “New AHAAH”. Our 

Fig. 1 reproduces the data from their figure representing their version of the original 

model (labeled AHAAH ZCHS) along with the same calculation using the original 

model (AHAAH PK). The first important observation is that AHAAH ZCHS does 

not come close to matching AHAAH PK (the 2 models should have been identical). 

We conclude that what they referred to as the AHAAH model in their article had 

been changed in some unidentified ways and was not in fact the original model. 

This is a critical problem for the purposes of their work, because comments 

regarding the original AHAAH cannot be taken seriously. We are at a loss to 

explain this problem with Zagadou et al.’s use of the model. It is possible that 

transcription errors could have occurred or other programming errors could have 

entered in, but comparison of the model outputs should have quickly identified such 

problems. The AHAAH model has for many years been freely available for 

download at the US Army Research Laboratory website. A simple comparison of 

the output with that model with their version of it on virtually any waveform could 

have alerted Zagadou et al. that there was a serious problem with their version of 

the AHAAH model. 

Fig. 1 Stapes velocity transfer functions for what Zagadou et al. claimed to be the original 

AHAAH model (AHAAH ZCHS) and the same calculation with the actual AHAAH model 

(AHAAH PK)

AHAAH ZCHS

AHAAH PK
Approved for public release; distribution is unlimited.

8

7. Non-improvement of AHAAH-PK

A critical focus of the Zagadou et al. work, however, was to improve the fit of the 

model to “the latest human data”. If we continue to focus on the middle ear pressure 

gain (their Fig. 13), we discover that they managed to reduce the goodness of the 

fit between the model and the data rather than improve it. In our Fig. 2 we have 

plotted the middle ear gain for the Aibara et al. (2001) data on 12 cadaver ears that 

they were trying to match. For comparison, we also plotted the calculated responses 

of the “new” AHAAH (their improved version of the model), the original AHAAH 

PK, and the work of Kringlebotn and Gundersen (1985) (data from 68 cadaver ears 

and used in the development of the original AHAAH). Visual inspection of the 

curves shows that at frequencies below 1 kHz the AHAAH-New curve sits well 

above the Aibara et al. data as well as the Kringlebotn and Gundersen data and 

shows peak sensitivity at a lower frequency than all the other curves. As a way of 

quantifying the fit, we calculated the correlation coefficients between the curves. 

The correlation between Aibara et al. and AHAAH PK is 0.91, while the correlation 

between Aibara et al. and AHAAH-New is 0.79—clearly not an improvement. If 

we compare the models’ predictions with Kringlebotn and Gundersen, the 

correlation with AHAAH PK is still higher (0.93 vs. 0.86 for AHAAH-New). These 

data support the contention that in spite of their expressed intentions, Zagadou et al. 

did not in fact improve the fit of the model to at least these transfer function data. 

The original model (AHAAH PK) fits the Aibara et al. and the Kringlebotn and 

Gundersen datasets much better than Zagadou et al.’s “improved” version.
Approved for public release; distribution is unlimited.

9

Fig. 2 Comparison of stapes velocity transfer functions for Zagadou et al.’s AHAAH-New, 

the original AHAAH (AHAAH PK), the human data of Aibara et al. (2001), and Kringlebotn 

and Gundersen (1985)

In passing, we note that the data from Aibara et al. might not be the ultimate data 

to match for 2 reasons. First, as we noted earlier, there is general agreement that the 

human annular ligament is not symmetrical, with the result that the motion of the 

stapes is not that of a simple piston but rather includes rocking elements in 2 planes, 

especially at high amplitudes. The test fixture used by Aibara et al. appears to have 

held the head of the stapes so as to limit it to piston-like movement in one plane, 

producing a motion not truly characteristic of the human stapes. Second, the 

measurements of compliance were made using very-low-frequency driving 

(near 1 Hz). Measurements of annular ligament compliance at very low frequencies 

approaching steady state (Gan et al. 2011) and subsequent analysis using 

temperature–frequency superposition (Zhang and Gan 2014), show stiffening of the 

annular ligament with increasing frequency. It seems to us that the performance of 

the ligament needs to be evaluated at realistic auditory frequencies, at least for the 

purpose of predicting conductivity in the normal auditory range.

In the end we conclude that whereas Zagadou et al. set out to improve the fit of the 

AHAAH model to the conduction data, however laudable their intent, they simply 

failed to produce a better fit than the actual original model.

AHAAH-New

KRINGLEBOTN and GUNDERSEN

AIBARA et al. (±1 SD)

AHAAH PK
Approved for public release; distribution is unlimited.

10

8. Non-replication of the AS Pressure Histories

A major area of critical concern with the work of Zagadou et al. was their apparent 

failure to reproduce the waveforms from the AS—a task central to their 

experimental design. Zagadou et al. invested a great deal of effort attempting to 

recreate the impulse-producing apparatus used in the AS. This involved C4 

explosive charges detonated in particular structures that were 1, 3, or 5 m from the 

Ss’ ears. Their experimental design required them to recreate the AS pressure 

histories, measuring them in the free-field and at the eardrum position of an ATF 

fitted with the same type(s) of HPD used in the AS (as well as a helmet and goggles, 

which the Ss also wore). If the ATF were an adequate substitute for the human Ss, 

they argued that the waveforms could legitimately be analyzed using AHAAH’s 

algorithms permitting data to be entered at the eardrum position. And if those 

waveform data matched the AS data, they had proposed to use the TS data from the 

AS to validate and/or adjust the model. This approach did have the effect of not 

requiring the testing of additional human Ss, but it does require scrupulous attention 

to the details of the physical measurement. It is obviously critical that the pressure 

histories match those of the AS if we are to allow them to be meaningful predictors 

of the hearing loss data from the AS. Following an analysis of the limited data 

available in their report, we believe that they failed to reproduce the AS in 

numerous ways, so much so that we conclude that they simply did not in fact 

reproduce the AS stimulating conditions as required. We offer several examples of 

this problem in the following.

8.1 Measurement Issues

8.1.1 Microphone Use

First we address the nonstandard use of pencil gauges in making the free-field 

measures. The pencil gauge is designed to be pointed directly at the impulse source 

so that the incident wave passes the sensor’s surface at grazing incidence. In 

Zagadou et al.’s Figs. 2 and 3, which picture the gauges in use, we note that they 

are pointed horizontally in the direction of the impulse source. In the case of the 5-

m condition, the actual impulse source was considerably elevated above the 

horizontal, which means that the pencil gauges were susceptible to off-axis effects. 

In the original AS, measurements were made with pancake gauges oriented 

vertically, which minimized the off-axis influences.
Approved for public release; distribution is unlimited.

11

8.1.2 Apparatus

Second, we note that in spite of Zagadou et al.’s assertions that the stimulating 

apparatus was faithfully reproduced, the apparatus for the 1- and 3-m conditions 

was significantly different from that used in the AS exposures, which would alter 

the true exposure waveforms (see their Fig 2.). In the original AS apparatus, the Ss 

were seated next to a vertically oriented, mortar-like tube on a raised platform made 

of expanded metal, which was essentially acoustically transparent. The muzzle of 

the “mortar” was about 1.5 m above the platform, which was in turn a little less 

than 2 m above a hard surface. Thus, the ground reflection in the AS data had a path 

length of about 7 m (probably somewhat more, because the effective center of the 

stimulating impulse is above the muzzle by some amount). However, in the setup 

pictured in the Zagadou et al. article, there appears to be a hard, deck-like reflecting 

surface at the level of the platform rather than the expanded metal used in the 

original apparatus. Thus, the ground reflection was closer by about 4 m, which to a 

first approximation would mean that the reflected waveform would appear to be 

about 10–12 ms earlier in the waveform than it did in the AS. In deciding whether 

or not they had reproduced the AS impulses, Zagadou et al. used metrics that 

examined only the initial peak in the waveform. 

The AHAAH model indicates that the ground reflection is a nontrivial issue, even 

though the reflected wave is much less intense than the initial waveform. The 

problem is that at these high pressure levels (170+ dB), peak-clipping by the stapes 

produces a waveform entering the cochlea in which only a small percentage of the 

hazard is calculated as being due to the initial peak of the waveform, and a majority 

of the effect is assignable to the latter part of the waveform (which is still very 

intense) (Price 2012). So the reflected energy may be critical to understanding the 

hazard from a particular stimulating situation. It appears that in this regard, 

Zagadou et al. have not reproduced the stimulating conditions in the AS.

8.1.3 ATF Issues

Third, we observe that the data from the ATF they used were grossly distorted by 

some combination of unspecified factors. Zagadou et al. in effect noted this 

problem in their data, and as a result, they found it necessary to “extrapolate” lowerpressure-level data to achieve the higher-pressure-level data they needed! We 

comment more on this extraordinary procedure later, but there really is no substitute 

for good measurements. Their Fig. 6 displays the transfer functions measured with 

the ATF, and it is clear that their data, especially at the lower frequencies, did not 

come close to matching the normal transfer function for the human ear. We have 

no way of diagnosing the problem(s) for certain, but such problems can arise when 

the ATF design does not sufficiently isolate the “back path” to the microphone. 
Approved for public release; distribution is unlimited.

12

Such isolation is very hard to achieve, especially for the low frequencies. We also 

note that the distorted data they cite were produced by impulses from a shock tube 

operating at much lower pressures (155–160 dBP) than those in the AS dataset 

(178–195 dBP). The data they have shown appear to be full of measurement 

artifacts, which should preclude their use in a test such as this. Furthermore, it is 

reasonable to suppose that the measurement artifacts must have gotten worse as the 

pressures rose to the Levels actually used in the AS. Our experience has shown that 

valid pressure histories are admittedly difficult to make in this pressure region, 

especially under conditions where heat from the exploding sources can itself cause 

the microphone output to distort. Distortions of this sort can even be seen in some 

of the original AS data.

It also occurs to us that the problem of simulating the stimulating conditions in the 

AS was perhaps even impossibly complex. Not only did the Ss wear an HPD, but 

they also wore combat helmets and protective goggles. The goggles and helmet 

were part of the immediate acoustic environment and their interaction with the ATF 

may have produced unexpected effects, given that skin on the scalp and hair are not 

normally part of an ATF. Also, at the very high pressures used in these studies (up 

to 195 dB, or more than 100 kPa), it was possible to get physical displacement of 

objects in the sound field.

8.1.4 Distorted Pressure Histories

The foregoing problem with measurements becomes more apparent when we 

examine the pressure histories Zagadou et al. actually used in their calculation and 

the ones they provide in the article. We read the pressure history data in their Fig. 9, 

which represented pressures at the eardrum position for the 5-m data and the 

defeated muff. Fortunately, samples of the waveforms from the original AS have 

been made available to the research community, and we were able to compare them 

with the Zagadou et al. data. A careful examination reveals a host of serious 

problems:

• The growth of the peak pressure level (PPL) of the impulse does not match 

the AS data. Zagadou et al. show essentially no growth of PPL at the ear 

drum between Level 1 and Level 4 (PPL in the free-field in the AS rose 

8.3 dB between those levels, and the corresponding PPL under the muff at 

the Ss’ tragus rose 7.2 dB over that same interval). The lack of growth in 

the data of Zagadou et al. makes no physical sense and runs counter to their 

claim that they matched the growth of PPL.

• When faced with artifacts in their pressure history data, Zagadou et al. did 

a most extraordinary thing—they “extrapolated data”. Their extrapolation,
Approved for public release; distribution is unlimited.

13

however well-intentioned, was based on linear thinking in a world of 

nonlinear processes, not the least of which was the muffs themselves 

(an issue the authors neither noted nor commented upon). Consider the 

nonlinearity introduced by the muff. If we use the waveforms from the 

original AS, we find that if we compare the A-weighted energy in the 

impulse outside the muff with the A-weighted energy at the tragus, we get 

an estimate of the attenuation provided by the muff (for the record, peak 

pressure measures behave similarly). The effects were nontrivial. In the case 

of the 1-m data, the attenuation of the muff improved 11 dB, while the 

outside energies rose by 18 dB. Under the muff, then, the total rise of 

A-weighted energy was only 7 dB! In contrast, for the intact muff in the AS, 

the attenuation became less by 5.4 dB, which means that the energy rose by 

23 dB under the muff for a nominal 18-dB rise outside it (Price 2007). 

Assumptions concerning the pressure histories, under these circumstances, 

can only be viewed as very risky, especially if the exact shape of the 

pressure history matters. In any event, Zagadou et al. made linear 

assumptions and, not surprisingly, their results reflect their assumptions.

The PPLs for their Levels 5–7 (at the eardrum) rose 5.6, 3.1, and 2.5 dB,

respectively (11.2 dB total). For the same data range, the free-field pressure 

(FFP) data from the AS showed rises of 2.6, 3.3 and 2.0 dB, respectively

(7.9 dB total), and the PPLs at the tragus in the AS rose 1.5, 4.5, and 

1.6 dB, respectively (7.6 dB total), with pressure growth at the tragus 

paralleling the free-field. Arguably, the data from Zagadou et al. showed a 

rise about 3.5 dB higher than the measured responses. Such data can hardly 

be used with confidence.

• Next we note with surprise that the absolute PPLs in the Zagadou et al. data 

(for pressure at the eardrum under a protector) are higher than the 

corresponding FFPs in the AS—by 1.3–8.7 dB! Further, if one looks at the 

PPLs at the tragus for the AS studies, the PPLs of the Zagadou et al. data 

(nominally at the ear drum) were 12–22 dB higher than the AS data at the 

tragus. It is obvious through simple inspection that something is drastically 

wrong with the data at the eardrum of the ATF. Others using the same ATF 

did not find such an aberration in PPLs (Murphy et al. 2015). And when we 

have exercised the AHAAH model to predict pressure histories at the 

eardrum, we find that, not surprisingly, there is little difference predicted 

between pressures at the tragus and at the eardrum. We will cover more of 

this later. 

• Furthermore, the wave shape of the original AS data at the tragus had a slow 

rise and smooth, rounded form, and an extended duration, as one would 
Approved for public release; distribution is unlimited.

14

expect to find in a pressure history measured under a protector. In contrast, 

the Zagadou et al. data look essentially like free-field waveforms with 

significant high-frequency content (unlikely under a muff). When we tried 

using AHAAH to predict pressure histories at the eardrum, given pressures 

at the tragus, the calculated shape changed little. We can conceive of no 

physical way that such a pressure level and shape change could have 

occurred in a proper measurement. 

• The problems of this sort are not confined to the 5-m data. Zagadou et al. 

reported no waveform data for the 3-m condition, but their Fig. 8a contains 

overlaid waveforms for the 1-m condition. We have digitized their 

waveforms from the printed figure, with the obvious limitations on 

accuracy. That need not concern us given that the issues that concern us are 

not subtle. In our Fig. 3, we show their 1-m Level 1 waveform at the 

eardrum with our calculated waveform (using pressures at the tragus from 

the AS) for the same condition. In this case, the lowest pressure level for 

this condition, we find that the agreement between the 2 pressure histories 

is quite good.

Fig. 3 Eardrum pressure for 1 m, Level 1, from the ATF (blue curve) and the eardrum 

pressure calculated using the original AHAAH model (red curve) and the AS tragus data

In our Fig. 4, we compare our calculated 1-m Level 6 waveform with theirs,

and the difference is substantial. The PPL of their waveform is 120 kPa, 

about 25 kPa higher than the free-field pressure and more than 100 kPa 

(18 dB) higher than the calculated pressure. Furthermore, the A-duration of 

Zagadou et al.’s impulse was less than 1 ms—the same as that of the FFP—

while the calculated pressure had a rounded leading edge and an A-duration 

of a little over 2 ms (matching the A-duration at the tragus in the AS). 

Clearly some consequential measurement issues developed as the pressure 

rose. These data contain serious anomalies. 
Approved for public release; distribution is unlimited.

15

Fig. 4 Eardrum pressure for 1 m, Level 6, from the manikin (blue curve) and the eardrum 

pressure calculated using the original AHAAH model (red curve) and the AS tragus data

The foregoing points make the case that Zagadou et al.’s measurement system was 

defective, and that they did not in fact reproduce the AS data. These shortcomings 

invalidate any subsequent analysis using these data in assessing the sensitivity of 

the human ear to damage from intense impulse noise (as Zagadou et al. have done).

Furthermore, it is difficult to conceive how this critical set of issues could have 

escaped their attention and brings into serious question their concluding 

recommendation that the “use of the ATF method to collect eardrum data as model 

input will correctly account for the HPD and orientation effects”. The use of an 

ATF has much potential in the assessment of HPD effects as well as the 

complexities of exposures that do not occur in the free-field. However, there are 

still many technical issues that need to be addressed—especially in the case of very 

intense stimuli—before a standard ATF can be agreed upon. 

9. Philosophical Issues

The logic underlying the design of these experiments seems problematic in that it 

pervaded and confused the scientific effort, leading to what we believe are invalid 

outcomes. One set of issues involves the experimental technique and the other the 

presumptions in their analysis. We cover both in turn.

9.1 Experimental Technique

The study set out to critically examine the AHAAH model and improve its fit to 

the human hearing loss data. That is a worthwhile focus. Their experimental 

approach included reproducing the stimuli used in the AS—possibly a useful effort, 

depending upon the use to which such data might be put. Certainly, there have been 

ATF EARDRUM

AS EARDRUM (AHAAH)
Approved for public release; distribution is unlimited.

16

questions regarding the true variability in the AS style exposures (Price 2010). 

Also, it would be good to have waveforms measured under the nonlinear earplugs 

tested in those studies (not currently available) and to measure the response of 

additional protectors that might be tested as well. This research might have 

produced interesting and useful data. Though they said they made such measures,

they did not report them.

However, Zagadou et al. made the G.R.A.S. ATF an integral part of their 

measurement setup. It would be fair to say that there is no consensus in the technical 

community that the perfect ATF has been developed and that differences between 

ATFs constitute a significant element of variability (Murphy et al. 2015). One of 

the difficulties in using such devices at these high pressures is in the nonlinearity 

of microphones used in them. In an “unprotected” exposure, the PPLs can be very 

high indeed. There are gauges that can meet the requirement for the high peak 

pressure, but they tend to be less sensitive and have a poor signal-to-noise ratio at 

the lower pressures encountered with less-intense stimuli and protected exposures. 

The AHAAH model, furthermore, has made the measurement world more difficult 

by requiring the measurement of very-low-frequency energy (down to about 1 Hz). 

That energy does not itself produce hearing loss, but it does affect the conductive 

path by causing the stapes suspension to clip, which modulates the flow of higherfrequency energy that does cause intra-cochlear damage. A real series of technical 

challenges needs to be worked out before measurements can be made confidently. 

There is also the question regarding the back-path conduction (equivalent to “bone 

conduction”) of the ATF. Controlling the microphone’s exposure to these 

influences is essential to making valid measurements. As we have seen, the data 

that Zagadou et al. report in their Fig. 6 suggest that this was a real problem in their 

experiments. In nonlinear systems one cannot simply assume away the problem of 

a measurement error. In our estimate, this is another fatal flaw in the execution of

the study.

9.2 Assumed and Extrapolated Data

The measurement problem is compounded by the authors’ willingness to assume 

data rather than to strictly adhere to empirical evidence. For example, they 

comment that in interpreting the hearing loss data from the AS, they analyzed them 

“in accordance to the original approved statistical protocol”. That means that they 

assumed that energy is the critical variable for an ear’s susceptibility and proceeded 

to create data consistent with that presumption. In the original AS, if an ear failed 

at a particular energy level in the exposure matrix, for statistical purposes it was 

presumed to fail at all higher levels as well. This meant that more than half of the 

failures in their statistical analysis had been assumed rather than observed. For the 
Approved for public release; distribution is unlimited.

17

purposes of a simple statistical analysis, in the words of Hamlet, “tis a 

consummation devoutly to be wished”. Unfortunately for this approach, the 

presumption of failure at higher levels was in fact not met in the AS data. A detailed 

analysis of the data has shown that there were 28 failures (greater than 15 dB of 

TS). Of those, 25 went on in the protocol to finally fail at higher levels, sometimes 

much higher levels. Only 3 ears met the presumption in the experimental design 

and failed when re-exposed to the same energy (Price 2010). Clearly the 

presumption of failure at all higher levels based on energy at one level is not 

supported by the AS data. The problem has been noted in the literature (Price 2007); 

yet in their analysis, Zagadou et al. embodied the presumption that energy in the 

free-field was the controlling variable (which was clearly not the case). 

Likewise, in our discussion of their creation of data for the 5-m condition 

(their Fig. 9), we have seen that the outcome is clearly inappropriate (e.g., apart 

from the inappropriately high levels, the expected growth of PPL with intensity was 

only present in the data they created). The circularity of their argument makes it 

unsurprising that they were able to find a match between their model and energy. 

Such procedures are anathema to scientific rigor. 

9.3 The Physiology of Loss

There is another critical issue overshadowing Zagadou et al.’s model and the 

analytic approach they recommend, namely the issue of what has been termed a 

“critical level” (CL) for the ear. A lot of data, from multiple species including 

guinea pig, monkey, cat, and man, for various measures including histology, 

electrophysiological potentials, rate of growth of loss, recovery times, and hearing 

thresholds, all agree that there is a level/zone in which the loss mechanisms change 

from metabolic exhaustion to mechanical stress (Price 1981). Simply put, the ear 

goes from being tired out to being torn up. Hence, it is reasonable to expect to find 

that a metric appropriate to the lower level will not apply at the higher level. 

Experience with exposure to factory noises has shown that one could well expect 

ears to recover from a 35- or 40-dB TS every working day for many years with a 

permanent loss gradually growing over a working lifetime. However, experiments

with animal ears have shown that the same level of TS in response to very intense 

sounds, such as gunfire, would produce about 20 dB of permanent TS from one 

exposure.

Consider the rate of loss once the CL has been crossed. Data from the human ear, 

the chinchilla ear, and the cat ear agree that for a given exposure, the loss measured 

immediately after exposure grows very rapidly with increases in level: about 6 or 

7 dB for every decibel increase in PPL of the exposure (Price 1981; Hamernik
Approved for public release; distribution is unlimited.

18

et al. 1987; Price and Wansack 1989). Thus, once the threshold for mechanically 

based loss has been reached for some exposure, a 10- to 15-dB increase in PPL is 

the difference between no loss and total loss with no hair cells left in that part of 

the cochlea—from one exposure. Clearly the processes are different on either side 

of the CL, and those differences can be ignored only at great peril.

Zagadou et al. neither note nor account for the issues associated with a CL. For 

instance, in their model for loss, the function that relates hazard to the level and 

number of impulses is what they refer to “the traditional 10log10(N) rule”, where N 

represents the number of shots. One of the strong observations for a CL is that the 

rate at which loss accumulates goes from linear in log-time (like the “traditional 

rule” Zagadou et al. commend) to a function that is linear in time (for multiple 

measures and different types of ears [see Price 1981]). Price and Kalb (1991) have 

argued that this change is consistent with the mechanism of mechanical fatigue and 

have embodied it in the cochlear portion of the AHAAH model. Zagadou et al. 

essentially reject this element without noting or commenting on it. 

We also believe that their approach would produce only a very bad fit to the hearing 

loss data should they try to plot a full range of them. In their Figs. 16 and 17, they 

plot a logistic regression analysis of the very small set of hearing loss data they 

have developed. We note that what has been plotted is essentially a population 

susceptibility curve portraying the percentage of the population that would reach a 

threshold of damage on the ordinate given an increasing exposure on the abscissa. 

If we read from their plots, the interval between a 5% incidence to a 95% incidence 

is a range of about 65 dB. The data from the human ear relating to a CL (Price 

1981) as well as data from the cat and chinchilla ears (Hamernik et al. 1987) show 

that once you have reached the zone of the CL, the 5%–95% interval in a population 

is much closer to 20 dB than the 65 dB plotted by Zagadou et al. The 20-dB range 

is, in the AHAAH model, held to be indicative of a susceptibility normally 

distributed with a 6-dB standard deviation. As of this writing, that analysis fits the 

data. We do not doubt that ranges like Zagadou et al. plot may exist where the actual 

exposure conditions are not well defined (angle of exposure is not well controlled, 

middle ear muscle activity is not accounted for, etc.), but in the present case where 

the conditions are clearly specified, their assumed range of 65 dB appears to be 

much too large.

9.4 Middle Ear Muscle Activity

Finally, in the area of what we believe are bad assumptions, Zagadou et al. have 

essentially ducked the question of middle ear muscle activity. Like Scarlett O’Hara,

they have chosen to “think about that tomorrow”, and have nonetheless gone 
Approved for public release; distribution is unlimited.

19

forward with a specific, highly questionable viewpoint. It is true that, like many 

other aspects of hearing loss to intense sounds, more data with respect to human 

middle ear muscle effects would be desirable. Yet recent data have shown that 94% 

of the human Ss tested have a middle ear muscle reflex (Flamme 2015) and a 

number of other studies have shown them to be conditionable in animals and man 

(Djupesland 1964, 1965; Brasher et al. 1969; Yonovitz 1976). Beyond that, the 

cognitive capacity of the human adds to the probability of a conditionable response. 

For instance, it has been shown that Ss’ middle ear muscles contracted as they

contemplated handling a toy that was thought to be noisy (Marshall et al. 1975). 

The evidence suggests that it is reasonable to expect the middle ear muscles can 

contract in advance of the auditory stimulus. In fact, it would be difficult to make 

the argument that we should not expect a contraction in advance of the stimulus! 

Interestingly, we note that the original AHAAH model (for the cat ear) was 

developed with data in which experimental designs were arranged to specifically 

avoid middle ear muscle involvement (animals were anesthetized at the time of 

exposure). To obtain a realistic response for a normal population, the muscle effects 

were then added once the pure cochlear loss mechanisms were quantified. 

In any event, the AHAAH model has been validated with the active middle ear 

muscle effects as an option, and the acceptable levels within it reflect the 

appropriate presence (or absence) of the response (Price 2007). Actually, the basic 

question is whether or not a conditioned response can be demonstrated. The 

unconditioned response (as in a string of continuing impulses, or even an exposure 

in the presence of a moderately loud background sound) is not really debated. It 

seems to us rather perverse, in the presence of so much positive information, to 

simply conduct an analysis assuming that there was no muscle response. Due 

scientific diligence would surely have commended that in the presence of doubt, 

both analyses be performed and the differences examined. Zagadou et al., again, 

assumed an outcome and did not qualify or limit the application of their proposal.

10. Conclusions

The work reported in the Zagadou et al. article was nominally aimed at producing 

an improved damage risk criterion for human exposure to intense impulsive sounds. 

We take no pleasure in concluding that the scientific rigor in this work was woefully 

deficient, and as a result this work failed to deal with the problems it set out to 

address. 

Zagadou et al. began with the premise that the “non-monotonic” response of the 

AHAAH model (presently used as a hazard assessment tool) was evidence of a 

serious problem. We have seen that it has long been known that there was no true 
Approved for public release; distribution is unlimited.

20

non-monotonicity and furthermore that the available data did in fact fit the model’s 

prediction.

Zagadou et al., in fact, did their work on an unknown version of the AHAAH model 

that differs in unspecified ways from the official version. Any comments regarding 

problems with or improvements to AHAAH are therefore moot. 

Zagadou et al. claimed to improve the model’s fit to the transfer functions for the 

human ear. We have seen from a transfer function that they published that they did 

not in fact use the original model. Yet it should have been obvious to them that this 

error existed. Furthermore, we showed that the changes they made, for at least the 

data to which we had access, resulted in a poorer fit to one of the critical transfer 

functions for the human ear. Their efforts at model improvement produced a 

demonstrably less good fit to the data. 

Zagadou et al. proposed to reproduce the AS exposure stimuli and measure the 

acoustic response at the eardrum location of an ATF. We have seen that the data 

they have published are rife with serious artifacts and cannot in any sense be 

considered to have been a replication of the AS data.

Finally, we have shown that in the interpretation of the data and the analytical 

procedures they used, Zagadou et al. simply ignored relevant data on the ear’s 

response to intense sounds and consistently made assumptions that favored a bias 

in the direction of energy explaining everything—a problem of logical circularity.
Approved for public release; distribution is unlimited.

21

11. References

Aibara R, Welsh J, Puria S, Goode R. Human middle-ear sound transfer function 

and cochlear input impedance. Hear Res. 2001;152:100–109.

American National Standards Institute (ANSI) S3.62. Impulse noise with respect 

to hearing hazard [accessed 2017 Mar 9]. http://asastandards.org/s3wf62/.

Brasher PF, Coles RRA, Elwood MA, Ferres HM. Middle-ear muscle activity and 

temporary threshold shift. Int Audiol. 1969;8:579–584.

Dallos P. Dynamics of the acoustic reflex; phenomenological aspects. J Acoust Soc 

Am. 1964;36:2175–2183.

Djupesland G. Middle ear muscle reflexes elicited by acoustic and nonacoustic 

stimulation. Acta Oto-Laryngol Suppl. 1964;188:287–292.

Djupesland G. Electromyography of the tympanic muscles in man. Intern Audiol.

1965;4:34–41.

Flamme GA, Deiters KK, Tasko SM, Ahroon WA. Prevalence of acoustic reflexes 

in the United States. J Acoust Soc Am. 2105;138:1831–1832.

Gan RZ, Yang F, Zhang X, Nakmali D. Mechanical properties of the annular 

ligament. Med Eng & Phys. 2011;33:330–339.

Gyo K, Aritomo H, Goode R. Measurement of the ossicular vibration ratio in 

human temporal bones by use of a video measuring system. Acta Otolarngol. 

1987;103:87–95.

Hamernik RP, Patterson JH, Salvi RJ. The effect of impulse intensity and number 

of impulses on hearing and cochlear pathology in the chinchilla. Acoust Soc 

Am. 1987;81:1118–1129.

Hato N, Stenfeldt S, Goode RL. Three-dimensional stapes footplate motion in 

human temporal bones. Audiol Neurotol. 2003;8:140–152.

Heiland KE, Goode RL, Asai M, Huber AM. A human temporal bone study of 

stapes footplate movement. Am J Otol. 1999;20:81–86.

Kalb JT, Price GR. Mathematical model of the ear’s response to weapons impulses. 

Proceedings of the Third Conference on Weapon Launch Noise Blast 

Overpressure. Aberdeen Proving Ground (MD): Army Ballistics Research 

Laboratory (US); 1987. Available as: Aberdeen Proving Ground (MD): Army 

Research Laboratory (US); 2015 Apr. Report No.: ARL-RP-0521.
Approved for public release; distribution is unlimited.

22

Kringlebotn M, Gundersen T. Frequency characteristics of the middle ear. J Acoust 

Soc Am. 1985;77:159–164.

Lauxman M, Eiber A, Haag F, Ihrie S. Nonlinear stiffness characteristics of the 

annular ligament. J Acoust Soc Am. 2014;136:1756–1767.

Marshall L, Brandt JF, Marston LE. Anticipatory middle ear reflex activity from 

noisy toys. J Speech Hear Disord. 1975;40:320–326. 

MIL-STD-1474E. Design criteria standard, noise limits. Washington (DC): 

Department of Defense (US); 2015.

Murphy WJ, Fackler CJ, Shaw P, Khan A, Flamme GA, Meinke DK, Finan DS, 

Lankford JE, Stewart M. Comparison of the performance of three acoustic test 

fixtures using impulse peak insertion loss measurements. Washington (DC): 

Engineering and Physical Hazards Branch (EPHB), Division of Applied 

Research and Technology, National Institute for Occupational Safety and 

Health; 2015. EPHB Report. No.: 350-14a. p. 40.

Nixon CW, Sommer HC. Primary components of simulated airbag noise and their 

relative effects on human hearing. Report on Department of Transportation

Interagency Agreement IA-0-1-2160. Washington (DC): National Highway

Traffic Safety Administration Research Institute, Office of Vehicle Structural 

Research Biomechanics Division; 1973.

Pierson LL, Price GR, Kalb JT, Mundis PA. Comparison of impulse noise effects 

produced by two rifle muzzles. J Acoust Soc Am. 1995;97:3344. 

Price GR. Implications of a critical level in the ear for the assessment of noise 

hazard at high intensities. J Acoust Soc Am. 1981;69:171–177.

Price GR. Impulse noise and the cat cochlea [accessed 2003]. 

http://www.arl.army.mil/www/default.cfm?page=352.

Price GR. Predicting mechanical damage to the Organ of Corti. In: Pharmacological 

Strategies for Prevention and Treatment of Hearing Loss and Tinnitus Hearing 

Research. p. 5–13 [accessed 2006]. doi: http://dx.doi.org/10.1016/j.heares 

.2006.08.005.

Price GR. Validation of the auditory hazard assessment algorithm for the human 

with impulse noise data. J Acoust Soc Am. 2007;122:2786–2802.

Price GR. 2010. Susceptibility to intense impulse noise: evidence from the 

Albuquerque dataset. J Acoust Soc Am. 2010;127:1746. 
Approved for public release; distribution is unlimited.

23

Price GR. Impulse noise hazard: from theoretical understanding to engineering 

solutions. Noise Con Eng J. 2012;60:301–312.

Price GR, Wansack S. Hazard from an intense mid-range impulse. J Acoust Soc 

Am. 1989;86:2185–2191. 

Price GR, Kalb JT. Auditory hazard from airbag noise exposure. J Acoust Soc Am. 

1999;106:2629–2637.

Society of Automotive Engineers (SAE). Procedure and instrumentation for 

measuring acoustic impulses from deployment of automotive inflatable 

devices. Warrendale (PA): SAE International; 2003. Standard No.: J247.

Von Békésy G, Wever EG. Experiments in hearing. New York (NY): McGraw Hill; 

1960.

Yonovitz A. 1976. Classical conditioning of the stapedius muscle. Acta OtoLaryngol. 1976;82:11–15. 

Zagadou B, Chan P, Ho K, Shelley D. Impulse noise injury prediction based on the 

cochlear energy. Hear Res. 2016;342:23–38.

Zhang X, Gan RZ (2014). Dynamic properties of human stapedial annular ligament 

measured with frequency–temperature superposition. J Biomech Eng.

2014;136(8):081004.
Approved for public release; distribution is unlimited.

24

List of Symbols, Abbreviations, and Acronyms

AHAAH Auditory Hazard Assessment Algorithm for Humans

AHAAH ZCHS article AHAAH model

AHAAH PK original AHAAH model

ANSI American National Standards Institute

AS Albuquerque Studies

ATF acoustic test fixture

CL critical level

FFP free-field pressure

HPD hearing protection device

PPL peak pressure level

S subject

TS threshold shift
Approved for public release; distribution is unlimited.

25

1 DEFENSE TECHNICAL

(PDF) INFORMATION CTR

DTIC OCA

2 DIRECTOR

(PDF) US ARMY RESEARCH LAB

RDRL CIO L

IMAL HRA MAIL & RECORDS

MGMT

1 GOVT PRINTG OFC

(PDF) A MALHOTRA

1 ARMY RSCH LAB – HRED

(PDF) RDRL HRB B

T DAVIS

BLDG 5400 RM C242

REDSTONE ARSENAL AL 

35898-7290

7 ARMY RSCH LAB – HRED

(PDF) SFC PAUL RAY SMITH CENTER

RDRL HRO COL H BUHL

RDRL HRA I MARTINEZ

RDRL HRR R SOTTILARE

RDRL HRA C RODRIGUEZ

RDRL HRA B J HART

RDRL HRA A C METEVIER

RDRL HRA D B PETTIT

12423 RESEARCH PARKWAY

ORLANDO FL 32826

1 USA ARMY G1

(PDF) DAPE HSI B KNAPP

300 ARMY PENTAGON 

RM 2C489

WASHINGTON DC 20310-0300

1 USAF 711 HPW

(PDF) 711 HPW/RH K GEISS

2698 G ST BLDG 190 

WRIGHT PATTERSON AFB OH 

45433-7604

1 USN ONR

(PDF) ONR CODE 34 P MASON

875 N RANDOLPH STREET

SUITE 1425 

ARLINGTON VA 22203-1995

1 USN ONR

(PDF) ONR CODE 341 J TANGNEY

875 N RANDOLPH STREET

BLDG 87 

ARLINGTON VA 22203-1986

1 USA HQDA 

(PDF) ARI M SAMS

6000 6TH STREET BLDG 1464 

FT BELVOIR VA 22060

1 USA NSRDEC

(PDF) RDNS D TAMILIO

10 GENERAL GREENE AVE 

NATICK MA 01760-2642

1 OSD OUSD ATL

(PDF) HPT&B B PETRO

4800 MARK CENTER DRIVE

SUITE 17E08

ALEXANDRIA VA 22350

ABERDEEN PROVING GROUND

12 DIR USARL

(PDF) RDRL HR

L ALLENDER

P FRANASZCZUK

RDRL HRB

J LOCKETT

RDRL HRB A

M LAFIANDRA

RDRL HRB C

J GRYNOVICKI

RDRL HRB D

D HEADLEY

RDRL HRF

K OIE

RDRL HRF A

A DECOSTANZA

RDRL HRF B

A EVANS

RDRL HRF C

R PRICE

J GASTON

RDRL HRF D

A MARATHE
Approved for public release; distribution is unlimited.

26

INTENTIONALLY LEFT BLANK.