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Audiology Review: Preparing for the Praxis and Comprehensive Examinations
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92
AUDIOLOGY NUGGET
DSP routinely involves a significant number of trade-offs. In simple terms, the
more complex processing that takes place, the longer the processing time and
the more significant the digital storage requirements. To increase clarity of music
processing through hearing aids, most manufacturers have increased the bit resolution used in their devices (more specifically at the analog-to-digital converter
or ADC). Recall that an increase in one bit increases the dynamic range of a
digital system by 6 dB. Thus, by increasing the bit resolution by a value of 2
(from 16-to 18-bit, for example), these devices allow for an additional 12 dB
of input with less distortion by increasing the input dynamic range from 96 to
108 dB. Given the significant fluctuations in sound level associated with many
forms of music, this increase in dynamic range is intended to enhance music
perception for hearing aid users.
Nyquist Theorem and Aliasing Distortion
Effective sampling of a continuous signal requires at least two samples per cycle. This equates to effective sampling occurring at one half of the sampling frequency, commonly referred to as the Nyquist
frequency. Or put another way, a sampling frequency must be at least twice the highest frequency of
interest in a signal. If an insufficient sampling frequency is used, distortion (i.e., aliasing distortion)
will occur at or near the frequency that is one half the sampling frequency.
n
Aliasing distortion (shown in Figure 3–3) is the introduction of lower-frequency components
to a signal that are not present in the original signal.
n
According to the Nyquist theorem, using a sampling frequency of 44.1 kHz can provide
accurate frequency representation to approximately 22 kHz. Frequencies near or above 22kHz
FIGURE 3–3. Example of aliasing distortion. Source: Adapted from Hearing
Science Fundamentals, Second Edition (pp. 1–370) by Lass, N. J., & Donai,
J. J. Copyright © 2023 Plural Publishing, Inc. All rights reserved.
CHAPTER 3 Acoustics, Psychoacoustics, and Instrumentation
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are of concern due to the possibility of aliasing distortion. This is precisely the reason that
most audio applications use at least a 44.1 kHz sampling frequency (22 kHz is above the
frequency range of human hearing and thus any distortion should be undetectable).
n
There are two ways to reduce the effects of aliasing distortion. One is to low-pass filter the
signal below the Nyquist frequency to eliminate distortion. This type of filter is often referred
to as an anti-aliasing filter. The other solution is to increase the sampling frequency to increase
the frequency at which aliasing distortion occurs.
DSP Stages
n
Refer to Figure 3–4 for a simplified visual representation of common DSP that occurs in HAs.
Initially, a sound input is detected and processed by a microphone, converted into an electrical
signal, and then amplified by a preamplifier. Then the electrical signal (i.e., continuous signal)
is converted into a digital (i.e., discrete) signal, which is performed by the analog-to-digital
converter (ADC).
During this, sampling frequency and amplitude resolution parameters are of paramount
purpose and should be specified to meet the needs of the application.
n
Once the signal is in a digital format, it is processed by the DSP chip, where its frequency
and amplitude characteristics are modified based on patient factors such as type and degree
of hearing loss as well as patient characteristics such as previous HA use and uncomfortable
listening levels (for digital hearing aid processing). Next, the digital signal is processed by the
digital-to-analog converter (DAC), where the digital signal is converted back to an analog
signal. In this last stage, the analog signal is amplified and transmitted to a receiver (i.e.,
speaker) and is then presented to the patient.
n
In CIs, the same procedure is followed, but instead of the creation of an acoustic analog signal
as the final step, the signals are further broken down into frequency components, which are
then assigned to different electrodes within the cochlea. At these electrode locations, electrical
pulses are produced. These impulses then electrically stimulate the auditory nerve.
93
Auditory signals are coded in intensity, frequency, and time. The primary goal of CI
programming is to provide audibility for low-level and conversational-level speech across
the speech frequency range without exceeding the patient’s comfort or creating a spread of
electrical activity outside of CN VIII (Wolfe & Schafer, 2020).
FIGURE 3–4. Digital signal processing (DSP) process. Source: Adapted from Hearing Science Fundamen-
tals, Second Edition (pp. 1–370) by Lass, N. J., & Donai, J. J. Copyright © 2023 Plural Publishing, Inc. All
rights reserved.
Audiology Review: Preparing for the Praxis and Comprehensive Examinations
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94
KNOWLEDGE CHECKPOINT
Multiple options exist for amplifying high-frequency sensorineural hearing
loss. These include traditional bandwidth amplification, extended bandwidth
amplification, and frequency-lowering techniques (see Chapter 9). In general,
traditional bandwidth hearing aids have an upper frequency limit of approximately 6 to 7 kHz. Extended bandwidth systems, conversely, purport an upper
frequency limit of approximately 9 to 10 kHz. As such, the sampling frequency
(according to the Nyquist theorem) must be higher for the extended bandwidth
devices to allow for accurate processing of information in the 9 to 10 kHz frequency range. To accurately process information at or near 10 kHz, a sampling
frequency of at least 20 kHz is required.
Signal Detection Theory (SDT)
Signal detection theory is a conceptual framework used to describe decision-making in conditions of
uncertainty or “noise.” Noise in this instance refers to the uncertainty associated with decision-making
rather than traditional acoustic sources of noise. When performing a discrimination experiment, listeners develop a response bias (sometimes referred to as a response proclivity) that creates a corresponding
response pattern of hits, misses, false alarms, and correct rejections. Think of the response bias as a
relationship between the level of signal and the listener’s willingness to say “yes” or respond that a signal
is present or different.
Response Types
There are four response types: hits (true positives), misses (false negatives), false alarms (false positives),
and correct rejections (true negatives).
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Hits are defined as a correct response when the stimulus is present. This occurs when the
sound is present and the individual responds.
n
Misses occur when a sound of sufficient intensity (i.e., above threshold) is present but no
response to the sound is provided.
n
False alarms occur when the signal is absent, but the individual responds as it if were present.
n
Correct rejections occur when the signal is absent, and no response is provided.
Response Distributions
Figure 3–5 provides a visual of response distributions used to model the responses associated with a
discrimination task. Responses that occur in the left distribution (Noise) represent responses obtained
without a signal present. Responses that occur in the right distribution (Signal + Noise) represent
responses obtained with a signal present (the noise or uncertainty is always present). The x-axis represents the internal response, with responses to lower-level signals occurring to the left and responses to
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FIGURE 3–5. Signal detection theory noise and signal + noise response
distributions. Source: Adapted from Hearing Science Fundamentals,
Second Edition (pp. 1–370) by Lass, N. J., & Donai, J. J. Copyright © 2023
Plural Publishing, Inc. All rights reserved.
high-level signals occurring to the right of the x-axis (e.g., softer sounds to the left and louder sounds
to the right). The criterion response (represented by the vertical black line) refers to the point at which
the individual responds (“yes” responses to the right and “no” responses to the left).
Response Biases
As previously noted, when performing a detection or discrimination task (e.g., hearing test), individuals will typically develop a response bias, which is an internal judgment of how often and at what level
is required for them to respond. These biases can be divided into three types: liberal, conservative,
and neutral. The type of bias directly influences the distribution of hits, misses, false alarms, and
correct rejections.
n
Liberal response bias refers to when listeners are more likely to respond even if they are
uncertain if the signal is present. This results in an increase in hits and a decrease in misses due
to an increase in the number of overall positive responses. This also results in an increase in the
number of false alarms and fewer correct rejections. A visual is provided in Figure 3–6.
Audiology Review: Preparing for the Praxis and Comprehensive Examinations
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96
FIGURE 3–6. Liberal response bias. Source: Adapted from Hearing
Science Fundamentals, Second Edition (pp. 1–370) by Lass, N. J., &
Donai, J. J. Copyright © 2023 Plural Publishing, Inc. All rights reserved.
A drawback to the liberal response bias is the increased number of false positives, which
can create difficulty and unreliable findings during hearing testing if the false alarms are
misinterpreted as hits or correct responses.
n
Conservative response bias refers to when a listener cautiously responds, often waiting to
respond until the signal is above threshold. This results in an increased number of misses and
a decrease in hits due to the conservative approach to responding. This also results in an
increase in correct rejections and fewer false alarms. A visual is provided in Figure 3–7.
A drawback to a conservative response bias is that the responses deemed as “threshold”
are often not representative of a true threshold (e.g., suprathreshold or minimal response
levels).
n
Neutral response bias refers to when a listener responds in a more impartial way, not waiting
until a signal is louder or surely present to respond or responding when the signal is soft and
questionable. This leads to a more even distribution of hits, misses, false alarms, and correct
rejections as shown in Figure 3–5.
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FIGURE 3–7. Conservative response bias. Source: Adapted from Hearing
Science Fundamentals, Second Edition (pp. 1–370) by Lass, N. J., &
Donai, J. J. Copyright © 2023 Plural Publishing, Inc. All rights reserved.
Q & A
Imagine the situation where a clinician has an adult patient, Joe, who has a
developmental disability and is eager to please. The clinician begins testing and
realizes Joe’s eagerness is impairing his ability to obtain valid thresholds due to a
strong tendency to rapidly respond whether the sound was present or not.
Question: What response bias is Joe exhibiting, and what would you expect in
terms of hits, misses, false alarms, and correct rejections?
Answer: In this case, Joe is demonstrating a liberal response bias. A liberal
response bias typically leads to many hits and false alarms but few correct
rejections and misses. The clinician may have a difficult time determining true
threshold and may underestimate the patient’s audiometric thresholds (assume
thresholds are better than they actually are).
Audiology Review: Preparing for the Praxis and Comprehensive Examinations
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98
Now imagine there is a pediatric patient, Juan, who is distracted and not terribly
interested in the game being used for conditioned play audiometry. Juan looks at
the clinician at lower intensities but does not respond in play until about 10dB
higher intensity.
Question:
What response bias is Juan exhibiting, and what would you expect
in terms of hits, misses, false alarms, and correct rejections?
Answer:
Juan is demonstrating a form of conservative response bias. He signals
that he detects the signal by looking at the clinician but does not engage in the
response behavior (play) until a higher intensity is presented (similar to someone
waiting until he or she is absolutely sure the stimulus is present). These responses
should not be recorded as true threshold, but rather minimal response levels.
Juan’s response pattern would show fewer hits, fewer false alarms, but more
misses and more correct rejections.
d-prime (d ʹʹ) and Receiver Operating Characteristic (ROC) Curves
Signal discriminability is dependent upon the relative separation between the noise (N) and signal
+ noise (S+N) distributions. Thus, significant overlap between the two distributions increases task
difficulty and decreases discriminability. A value known as dʹ, also known as the discrimination index,
quantifies the relative ease or difficulty of the discrimination task.
n
dʹ values are shown in Figure 3–8 (left ). As can be seen, lower dʹ values are associated with
substantial overlap in the distributions (increased difficulty with discrimination), whereas
larger dʹ values are associated with less distribution overlap (less difficulty with discrimination).
These values can also be plotted on receiver operating characteristic (ROC) curves.
Discriminability Index
FIGURE 3–8. ROC curves and dʹ values. Source: Adapted from Hearing Science Funda-
mentals, Second Edition (pp. 1–370) by Lass, N. J., & Donai, J. J. Copyright © 2023 Plural
Publishing, Inc. All rights reserved.
\
'
\
'
'
80
60
40
20
0
20
ROC Curve
40 60 80
False Positive (%)
100
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n
As can be seen in Figure 3–8 (right), false-positive (false alarm) values are displayed on the
x-axis and true positives (hits) are displayed on the y-axis. Ideally, a test with a low false-
positive rate and high true-positive rate (dʹ of 3 as shown in the figure) is desirable. In clinical
terms, a test with a high hit rate and low false alarm rate suggests good diagnostic utility.
Conversely, a test with a 50% true-positive (hit) rate and 50% false-positive (false alarm)
rate (dʹ of 0 shown in the figure) lacks utility because the yes/no outcome is essentially left to
chance. Imagine being tested for a significant medical condition and only 50% of the time the
condition is correctly detected when it is indeed present (hit) and 50% of the time it is falsely
detected when it is absent (false alarm).
n
ROC curves are graphical representations of the performance on a discrimination task with
a binary outcome (e.g., yes/no, present/absent, condition/no condition). It can be plotted
visually and as distributions with associated dʹ values. Notice the leftward deviation of the
ROC curves as dʹ increases from 0 to 3 and the resulting separation of the distributions
on the left (dʹ from 1 to 3). As dʹ increases, the discrimination task decreases in difficulty
(signal detectability becomes easier), shown as a reduction in overlap in the two distributions
(S+N and N).
99
Psychophysical Methods
An individual’s psychological state when performing a perceptual task can drastically influence the
physical response. The methods utilized for obtaining these responses are commonly referred to as
psychophysical methods. Psychophysical methods are means of coupling physical properties of a
stimulus to the perception of and response to that stimulus. Many factors affect perception, including
motivation, alertness, and response preference or bias (refer to the Signal Detection Theory section of
this chapter).
Method of Limits
The method of limits entails changing one parameter of a stimulus, intensity in the case of auditory
testing, by the person performing the assessment (i.e., examiner), with the subject masked to indicate in
some way when they detect the stimulus. This technique is commonly used to obtain hearing thresholds
during an audiological evaluation performed in a hearing clinic (e.g., Hughson Westlake procedure).
n
Advantages: Time efficient (observations are concentrated around threshold); no need to
determine a range of potential thresholds to begin testing (i.e., at what level to begin testing)
n
Disadvantages: Thresholds may be recorded without evidence that the person was listening
Method of Adjustment
The method of adjustment involves the subject adjusting some parameter of a stimulus. For example,
the intensity of a stimulus may be adjusted to a point where it is barely audible, or the frequency
adjusted to match the pitch of a reference tone. The changes made by the subject are recorded and
analyzed by the examiner. Thresholds obtained using this method vary depending on exactly where
on the recorded observations the examiner marks threshold. An example of the method of adjustment
being used in behavioral testing is in Békésy audiometry.
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100
n
Advantages: Easy; appealing to the subject
n
Disadvantages: May produce unreliable results
AUDIOLOGY NUGGET
In Békésy audiometry, a listener is given a response button and instructed to
depress it for as long as they hear a signal; the audiometer first ascends in intensity (typically in 2.5 dB steps) until the button is depressed, then decreases in
similar step sizes until the button is released. This procedure is repeated several
times and the results are plotted. Though Békésy audiometry is not commonly
used in most clinics today, it is often used in military or other hearing conservation settings to monitor hearing thresholds. Historically, it has been used
in detecting conductive, cochlear, and retrocochlear hearing loss, as well as in
testing malingering patients.
Method of Constant Stimuli
The method of constant stimuli uses a two-alternative forced-choice (2AFC) procedure. This process
requires a subject to make a choice from two options (same/different or yes/no, for example). Several
stimulus levels or characteristics (e.g., intensity, brightness) above and below a predetermined criterion
are selected for use in the task. The listener is asked to indicate yes/no or same/different during each
period when a stimulus is presented. Results are plotted as the percentage of time each level of stimulus
was detected. Plotting the response data provides the examiner with a psychometric function, which
is a graphical display of how responses vary with changes in a parameter of the stimulus. A clinical
example of this method is matching the pitch or loudness of tinnitus (although it includes aspects of
the method of adjustment as well).
n
Advantages: Easy to conduct; provides complete picture of responses (i.e., number of
responses obtained above and below threshold to determine actual threshold)
n
Disadvantages: Time-consuming; need a good estimation of the threshold before you start;
many trials are wasted
Validity and Reliability
Validity refers to the accuracy or how well the measure assesses what it is intended to measure. Reliability refers to the consistency of a measure or the ability to obtain similar results when repeating the
measure over time. Figure 3–9 provides a visual representation of reliability and validity. The leftmost
visual demonstrates high reliability because all circles are located in a concentrated area but low validity
because they are located away from the center of the target. The central figure conveys low reliability
and low validity because the circles are widespread over the target and outside of the center of the
target. The rightmost figure shows high reliability and high validity due to a concentration of circles
occurring within the center of the target.
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Low reliability and low validityHigh reliability and low validity High reliability and high validity
FIGURE 3–9. Visual representation of reliability and validity.
Measures of Validity
101
n
Internal validity refers to the degree of confidence that the causal (cause-effect) relationship
being tested is trustworthy and not influenced by other factors or variables.
n
External validity refers to the extent to which results from a study can be applied (generalized)
to other situations, groups, or events.
n
Ecological validity refers to if test findings can be applied to real-world situations.
n
Construct validity refers to a test’s content, structure, variable associations, and responses.
n
Content validity refers to if a test measures what it is intended to measure.
n
Face validity refers to if a test appears to measure what it is intended to measure.
n
Predictive validity refers to a test’s ability to predict future behavior or performance.
n
Concurrent validity of a test measures the ability to predict similar outcomes using different
tests at the same time.
KNOWLEDGE CHECKPOINT
Internal validity can be evaluated in electrophysiological measures — some
measures, like the auditory brainstem response (ABR), are unchanged based on
the patient’s state; however, other measures, like the P300 cortical response, are
greatly impacted by the patient’s attentional state. External validity is exemplified
by tests developed within the VA system: The normative values established in
this population may not be applicable to younger patients, female patients, nonnoise-exposed patients, and so on. An ecologically valid measure of speech in
noise would be the QuickSIN; here, real-word stimuli (sentences) are presented
to listeners. This is a more valid way of measuring patients’ primary complaints of difficulty in noisy environments than a traditional word recognition
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