The Analysis of Presbycusis Type and Lesion Location Based on Audiogram Description, Speech Audiometry, and Otoaccoustic Emission

Background: This study aims to determine the type of presbycusis and the location of the lesion based on audiogram images, speech audiometry and Otoacoustic Emission. Method: This study was an observational study of 36 presbycusis patients (72 ear samples). Pure tone audiometry, speech audiometry and Otoacoustic Emission were examined to determine the most types of presbycusis and the location of the lesion. A cross-sectional descriptive research method was conducted to analyze the dynamics of the correlation between risk factors and effects by using approaching, observing or collecting data at once (point time approach). Each research subject was observed only once, and measurements were performed towards the character status or subject variables during the examination. Result: The results showed that presbycusis was primarily obtained in the 60-69 years age group (69.4%). And the most types of presbycusis based on the audiogram were metabolic presbycusis (36.1%). The average hearing range based on the audiogram was at a frequency of 26-40 dB or the degree of mild deafness. Most types of deafness were Sensorineural Hearing Loss (SNHL). In speech audiometry, most NPT and NDT were mild and normal deafness as much as 44.4% in NPT and 56.9% in NDT. Based on the OAE, 72 samples showed the results of the referrals. In addition, regarding the results of the audiogram, speech audiometry and OAE, the location of the lesions of all samples were in the cochlea (100%). Conclusion: The most common type of presbycusis based on audiogram images is metabolic presbycusis with a mild hearing loss.

Frequency-lowering processing to improve speech-in-noise intelligibility in patients with age-related hearing loss

OBJECTIVE

Modern hearing aids use various signal-processing strategies to improve speech intelligibility. In this manuscript, we studied the linear frequency transposition (LFT), a frequency-lowering algorithm, in patients with age-related hearing loss. Frequency-lowering algorithms transpose high-frequency sounds to a lower-frequency band. The study aimed to assess whether LFT could be used as a tool to improve speech intelligibility in patients with a better high-frequency preservation.

METHODS

The study population consisted of 77 patients (age average 74.8 ± 12.4) wearing hearing aids with an open or tulip coupling system with age-related hearing loss. The unaided air conduction pure tone average (PTA) at 500, 1000, 2000 Hz was 43.5 ± 14.3 dB; the unaided word recognition score (WRS) average was 53.7 ± 12.5%. We compared WRS in all patients with the hearing aid turned on, in "quiet" and using a "pink" and "babble" masking noise. Three hearing aid settings were tested in each acoustic conditions: no transposition (NT), high transposition (HT), and low transposition (LT). "High" and "low" refer to the "start frequency"; all sounds above the start frequency are transposed in a lower-frequency band. When the start frequency was suggested by the fitting software, we called the condition "high transposition"; when the start frequency was set at the lowest possible value provided by the fitting software, we called the condition "low transposition". The quality of the voice was also assessed asking the patient to give a score from 1 to 10, where 10 was the maximum listening comfort [quality of voice score (QVS)].

RESULTS

Collected data were compared for each condition (NT, HT, LT, in quiet, pink noise and babble noise) and no statistically significant differences were found in WRS and QVS (quiet WRS p = 0.07, pink noise WRS p = 0.18, babble noise WRS p = 0.11, QVS p = 0.91). We selected 33 patients with a better WRS in babble noise using transposition (high and low). In this group, the age was significantly lower than patients who did not use transposition (p = 0.01).

CONCLUSION

Linear frequency transposition is not useful to improve speech-in-noise intelligibility in patients with age-related hearing loss. Despite that no statistically significant differences were found, younger people could get advantages from the LFT when babble noise disturbs the listening of speech. The use of FL algorithm as a way to improve speech intelligibility in noisy environments should be always considered.