DOI: 10.7272/q6jh3jdb
title: Cochlear Implant Compression Optimization for Music Listening - Maplaw and AGC

description: Variations in loudness are a fundamental component of the music listening
 experience. Cochlear implant (CI) processing, including amplitude
 compression, and a degraded auditory system may further degrade these
 loudness cues and decrease the enjoyment of music listening. This study
 aimed to identify optimal CI sound processor compression settings to
 improve music sound quality for CI users. Fourteen adult MED-EL CI
 recipients participated (Experiment #1: n=17 ears; Experiment #2: n=11
 ears) in the study. A software application using a modified Comparison
 Category Rating (CCR) test method allowed participants to compare and rate
 the sound quality of various CI compression settings while listening to 25
 real-world music clips. The two compression settings studied were: 1)
 Maplaw, which informs audibility and compression of soft level sounds, and
 2) Automatic Gain Control (AGC), which applies compression to loud sounds.
 For each experiment, one compression setting (Maplaw or AGC) was held at
 the default while the other was varied according to the values available
 in the clinical CI programming software. Experiment #1 compared Maplaw
 settings of 500, 1000 (default), and 2000. Experiment #2 compared AGC
 settings of 2.5:1, 3:1 (default), and 3.5:1. In Experiment #1, the group
 preferred a higher Maplaw setting of 2000 over the default Maplaw setting
 of 1000 (p = 0.003) for music listening. There was no significant
 difference in music sound quality between the Maplaw setting of 500 and
 the default setting (p = 0.278). In Experiment #2, a main effect of AGC
 setting was found; however, no significant difference in sound quality
 ratings for pairwise comparisons were found between the experimental
 settings and the default setting (2.5:1 versus 3:1 at p = 0.546; 3.5:1
 versus 3:1 at p = 0.059). CI users reported improvements in music sound
 quality with higher than default Maplaw or AGC settings. Thus,
 participants preferred slightly higher compression for music listening,
 with results having clinical implications for improving music perception
 in CI users.
description: <strong>Subjects</strong><br> Fourteen MED-EL
 cochlear implant (CI) recipients (7 men and 7 women, average age 60.3 ±
 13.5 SD years) participated in the study. Four subjects were bilaterally
 implanted and 10 unilaterally implanted, yielding 18 CI ears tested. In
 Experiment #1, Maplaw manipulations were studied in 17 CI ears and in
 Experiment #2, AGC manipulations were studied in 11 CI ears.
 Thirteen CI recipients were postlingually-deafened and 1 was
 prelingually-deafened; all used oral/aural communication as their primary
 method of communication. The mean length of implant use was 3.4 ± 2.3
 years and the mean duration of severe-to-profound hearing loss prior to
 implantation was 8.4 ± 12.9 years (range: &lt;0.1 to 47.2 yrs). The CI
 users utilized a variety of devices and processing strategies (Table 1).
 Some of the subjects used a different sound processor model in day-to-day
 listening than the model used for this research experiment (i.e., a
 Sonnet), which may have affected results. The Institutional Review Board
 at the University of California, San Francisco (UCSF) approved this study
 and informed consent was obtained from all participants. 
 Nine subjects reported formal music training, beginning at age
 8.4 ± 5.4 years and lasting 9.0 ± 7.3 years. Of those nine subjects, three
 reported being self-taught musicians as did one additional subject who had
 no formal music training, with training beginning at age 32.0 ± 19.2 years
 and lasting for 3.9 ± 2.2 years. Six of the CI subjects reported that they
 do not listen to music in their day-to-day life, while the other 8
 subjects listen to music an average of 6.7 ± 4.3 hours per week (range: 2
 to 15 hrs/wk).  Most study subjects were using clinical
 default settings for Maplaw (500, 1000) and AGC (3:1). For the subjects
 who participated in Experiment #1, three used Maplaw of 500, 12 used
 Maplaw of 1000-1024, and two used Maplaw of 1500. Of the subjects who
 participated in Experiment #2, only one was using an AGC setting (3.5:1)
 in their clinical program different than the default setting
 (3:1). <strong>Musical
 Stimuli</strong><br> A corpus of 25 real-world music clips
 assembled during earlier studies was used (Roy et al., 2012a, 2012b). Each
 clip is 5 seconds long; there are 5 clips from each of 5 common musical
 genres (Classical, Jazz, Country, Rock, and Hip-Hop), and 60% of clips are
 commonly known while the other 40% are considered obscure. See Roy et al.
 (2012a) for additional details regarding the selection of musical clips.
 Music clips were each normalized to 65 dBA. The average acoustic dynamic
 range for the stimuli was 32.7 dB; by genre, Hip-Hop: 39.9 dB, Jazz: 34.9
 dB, Rock: 27.1 dB, Country: 29.0 dB, and Classical: 32.4 dB. For greater
 detail on the intensity level distribution functions of the music clips,
 broken down to 1/3 octave bands and grouped by genre, see Figure 1 from
 Gilbert et al. (2019). Testing took place in a
 calibrated sound booth. The stimuli were presented from a speaker located
 at 0 degrees azimuth with the listener seated 1 meter from the speaker at
 an average RMS level of 65 dBA. <strong>Test
 Conditions</strong><br> All CI recipients used a Sonnet sound
 processor designated for research use only. To increase consistency of
 audibility of musical clips across test subjects, their preferred everyday
 fittings were modified as follows: upper stimulation levels (MCLs) were
 loudness-balanced at 80% of incoming MCLs, and then the new MCLs were
 swept at 100% to ensure comfort. There were no predetermined restrictions
 imposed upon the patients’ electrical dynamic range (the difference
 between MCL and THR). Volume control was fixed at 100%. Microphone
 directionality and wind noise reduction features were disabled. Other
 parameters (except Maplaw, AGC, MCLs and THRs) were not altered for either
 experiment, in order to minimize acclimatization effects to the new
 programs. For the first 7 subjects, the subjects’ threshold levels (THRs)
 were measured on each electrode and set at the highest inaudible level.
 For the remaining 8 subjects, the THRs were set to either 0 or 10% of
 MCLs. Any changes to THRs were made prior to making other experimental
 changes. We then created multiple new programs for the
 CI user with the Maestro software. For Experiment #1, Maplaw was varied
 (i.e., 500, 1000, 2000), while AGC was fixed at the default (compression
 ratio 3:1, sensitivity 75%). For Experiment #2, AGC compression ratio was
 varied (i.e., 2.5:1, 3:1, 3.5:1), sensitivity was fixed at 100%, and
 Maplaw was fixed at the default (1000). In the MED-EL signal processing
 strategies, the sensitivity sets the knee point above which the AGC will
 become active. At the default sensitivity setting of 75%, the knee point
 is at 52.7 dB SPL. By changing the sensitivity to 100%, the AGC knee point
 is changed to 48 dB SPL and so more of the musical stimuli (delivered at
 65 dBA) is presented in the dynamic range where the AGC is
 active. After the new programs were created, the MCLs
 were adjusted up or down globally in small (1%) increments in order to
 obtain equivalent loudness in all programs. This loudness-matching process
 involved playing a pink noise at 65 dBA and switching back and forth
 between the default Maplaw program (Program 1) and each of the other two
 experimental Maplaw programs in turn to ensure that Programs 2 and 3 were
 loudness-matched to Program 1. Once both Programs 2 and 3 had been
 individually adjusted to match Program 1, all three programs were cycled
 through a final time to confirm the pink noise was the same loudness level
 to the listener in each program. This process was then repeated with the
 three AGC programs.  Program 1 was always the program
 with both Maplaw and AGC set to defaults (Maplaw = 1000, AGC = 3:1), while
 Program 2 and Program 3 were experimental programs and the program order
 was not randomized. For Experiment #1, Program 2 used Maplaw of 2000, and
 Program 3 used Maplaw of 500. For Experiment #2, Program 2 used AGC of
 3.5:1 and Program 3 used AGC of 2.5:1. It was important to rebalance the
 loudness within these programs because, without doing so, programs with a
 higher Maplaw or AGC would seem louder to the CI user, and it is known
 from previous research that the loudness of music may significantly
 influence the sound quality perception (Vickers, 2011). For the 10
 subjects who completed both Experiments #1 and #2, 8 subjects began with
 Experiment #1 and 2 subjects began with Experiment #2.
 We began the experiments with the intention of including even
 lower (i.e., more linear) compression settings in the test conditions, but
 the first few subjects tested with these settings were unable to tolerate
 these programs. More specifically, when the Maplaw was decreased to 250 or
 the AGC was decreased to 2:1, the music clips became too soft overall to
 be evaluated fairly. We attempted to correct for this by increasing the
 MCLs globally in order to make the music clips equally loud in all of the
 conditions. Unfortunately, this resulted in the intensity peaks in the
 music clips becoming uncomfortably loud in the programs with the lowest
 compression settings and therefore those test conditions (i.e., Maplaw of
 250, AGC of 2:1) were discontinued.  CI users listened
 with the test ear only. If the non-test ear had any residual hearing, a
 foam earplug was used. In one case, a CI recipient had a Lyric hearing aid
 in the non-test ear that was situated deep in the ear canal and could not
 be removed for testing. The Lyric was therefore turned off and functioned
 as an earplug. All CI users were asked if they could hear the test stimuli
 with the non-test ear while the earplug was in place and the CI on their
 test ear was turned off; all indicated they were not able to hear the
 stimuli with the non-test ear. Participants completed
 the experiment using a Dell Latitude E7470. Subjects were given the option
 of using a touchscreen, mouse, or touchpad. The computer ran the program
 with MATLAB software version R2012b (Mathworks, Natick, MA,
 USA). <strong>Test
 Paradigm</strong><br> The method used for testing closely
 resembles a Comparison Category Rating (CCR) approach, which allows for
 assessment of relative changes in the perceived sound quality of music
 across various listening conditions (ITU, 1996). The present study
 utilized a user-controlled CCR method, which is different from the
 standard CCR, in that the presentation order is not predetermined or
 randomized; the users may play the sound samples in any order and with the
 possibility of unlimited repetitions. Participants were asked to rate the
 relative sound quality of a particular music clip while using three
 different programs on their CI (“Prog 1”, “Prog 2”, and “Prog
 3”). The ratings were on a sliding scale with the
 following categorical labels: “Much better”, “Slightly better”, “Same as
 Prog 1”, “Slightly worse”, and “Much worse” (see Figure 3). The sliding
 scale corresponded to numbers from 0 to 200; scores from 0 to 99
 represented sound quality worse than Program 1, a score of 100 represented
 sound quality equal to Program 1, and scores from 101 to 200 represented
 sound quality better than Program 1. Program 1 was always set to 100, the
 midpoint (“Same as Prog 1”). The subjects were not explicitly required to
 use the whole range of the sliding scale. Although the term typically used
 to describe the results of a CCR-style test is the Comparison Mean Opinion
 Score (CMOS), per ITU standards (1996), we opted to describe CMOS results
 using the term “Sound Quality Ratings.”  There were 25
 trials in each experiment. Subjects were given verbal instructions, along
 with a live demonstration of the software interface functionality on the
 computer, and then were required to complete a practice round supervised
 by the researcher. The subject was responsible for switching between
 programs using the FineTuner remote control. The instructions were: (1)
 Click “Play” to listen to the music clip. You may replay the music clip as
 often as you wish. (2) Move the Program 1 slider to “Same as Prog 1”
 (i.e., the midpoint of the scale). (3) Switch the CI processor to Program
 2 using the remote control. (4) Play the music clip and move the Program 2
 slider to rate the sound quality as it compares to Program 1. (5) Switch
 the CI processor back to Program 1 and listen to the music clip again. (6)
 Repeat steps (3) and (4) for Program 3. (7) Click “Save and proceed” when
 you are satisfied with your ratings of Programs 2 and 3 as compared to
 Program 1. This procedure enabled a subject to express whether the
 experimental program(s) provided better or worse sound quality than the
 clinical default settings, and to what degree.  During
 the practice round, the subjects were required to complete the task for at
 least 3 trials (music clips), but were allowed to do additional trials
 until they reported they were comfortable using the computer, interacting
 with the software interface, and using the FineTuner remote control. To
 ensure the programs were changed correctly, the researcher enabled the
 indicator light on the processor and observed the number of light flashes
 to verify that they corresponded with the intended program change. During
 a practice round, subjects used whichever programs they were going to use
 for the following experiment. Each experiment took an average of 30 to 60
 minutes per ear. The CI recipient was given a break between ears (for the
 bilateral subjects) and between Experiments #1 and #2 (to allow for device
 reprogramming and to rest). <strong>Statistical
 Analyses</strong><br> All statistical analyses were completed
 using the R statistical computing program (R Core Team, 2020). A linear
 mixed effects (LME) approach was applied using the “lme4” package (Bates
 et al., 2015). For specific models and factors, see results below. In
 order to test for significant differences between test conditions within a
 single ear, comparisons were made with pairwise t-tests (paired, 2-tailed)
 and Bonferroni correction was applied.
description: The Readme-Maplaw.csv and Readme-AGC.csv files describe the data
 files Maplaw.xlsx and AGC.xlsx, respectively. The
 MATLAB package to collect the participant data is included.
 The statistical analysis utilized the R statistical program; the
 R script is included.