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Auditory Hazard Assessment Algorithm for Humans

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Combatants in every branch of the United States’ military are at risk for auditory impairments from steady state or impulse noises. While applying double hearing protection helps prevent auditory damage, the user is isolated from the environment and the ability to detect, identify and localize important environmental cues is impaired. With hearing protection on, a soldier is less likely to be aware of his or her movements, alerting the enemy to their presence. Hearing protection devices (HPD) could also require higher volume levels for communication, negating their purpose.[1]

The US Army Research Laboratory’s developed the Auditory Hazard Assessment Algorithm for Humans (AHAAH) to evaluate the potential damage to a user when exposed to high level impulse noise. The model purports to be more than 94% accurate with regards to identifying safe and hazardous exposures based upon the Blast Overpressure Walk-up study conducted by the US Army.[2][3][4] In almost every instance any error resulted in overcalculation of risk. By comparison the MIL-STD-147D was deemed correct in only 38% of cases with the same data.[4] The user inputs their noise exposure, protection level, and whether they were forewarned of the noise, to receive their hazard vulnerability in auditory risk units (ARU). This value can be converted to compound threshold shifts and the allowed number of exposure (ANE). Compound threshold shifts is a value that integrates both temporary and permanent shifts in auditory threshold, the latter being correlated to hair cell function.[4]

The first military standard (MIL-STD) on sound was published in 1984 and underwent revision in 1997 to become MIL-STD-1474D. In 2015, this evolved to become MIL-STD-1474E which, as of 2018, remains to be the guidelines for United States’ military defense weaponry development and usage. In this standard, the United States Department of Defense established guidelines for steady state noise, impulse noise, aural non-detectability, aircraft and aerial systems, and shipboard noise. Unless marked with warning signage, steady state and impulse noises are not to exceed 85 decibels A-weighted (dBA) and, if wearing protection, 140 decibels (dBP) respectively.[1]

The AHAAH’s improvements in accuracy are often attributed to its sensitivity to the flexing of the middle ear muscle (MEM) and annular ligament of the stapes. When someone is forewarned of a sound, the MEM flexes, which is associated with reduced ability of the sound waves to reverberate. When an impulse sound is produced, the stapes’s annular ligament flexes and strongly clips the sound’s oscillation peak.[2]

As the MIL-STD-1474 has evolved, technology and methods have improved the AHAAH model’s accuracy. AHAAH has been proven to be more accurate in cases of double protection but not always in unwarned impulse noise instances relative to the competitive metric LAeq8hr.[5] Some suggestions for further development focus on creating a more user-friendly software, the placement of the microphone in data collection, the absence of the MEM reflex in populations, and the reevaluation of free-field conditions in calculations. Agencies such as NATO, the American Institute of Biological Sciences, and the National Institute for Occupational Safety and Health agreed that these suggestions be attended to before the metric is implemented. This shared conclusion was made prior to the development of MIL-STD-1474E.[5]

References

  1. ^ a b Amrein, Bruce. "NOISE LIMITS FOR WARFIGHTING Recently Revised Standard Addresses Noise from Military Operations". thesynergist. Retrieved 3 July 2018.
  2. ^ a b Chan, P.C.; Ho, K.H.; Kan, K.K.; Stuhmiller, J.H. (2001). "Evaluation of impulse noise criteria using human volunteer data". J. Acoust. Soc. Am. 110: 1967–1975.
  3. ^ Price, G.R. (2007). "Validation of the auditory hazard assessment algorithm for the human with impulse noise data". J. Acoust. Soc. Am. 122: 2786–2802.
  4. ^ a b c DePaolis, Annalisa; Bikson, Marome; Nelson, Jeremy; de Ru, J Alexander; Packer, Mark; Cardoso, Luis (Feb 2, 2017). "Analytical and numerical modeling of the hearing system: Advances towards the assessment of hearing damage". Hearing Research. 349: 111–118. doi:10.1016/j.heares.2017.01.015. PMID 28161584. Retrieved 3 July 2018.
  5. ^ a b Nakashima, Ann (November 2015). "A comparison of metrics for impulse noise exposure" (PDF). Defence Research and Development Canada. Retrieved 3 July 2018.