METHODS: Twenty-nine healthy Malaysian subjects (14 males and 15 females) aged 19 to 30 years participated in this study. After measuring the head circumference, speech-ABR was recorded by using synthesized syllable /da/ from the right ear of each participant. Speech-ABR peaks amplitudes, peaks latencies, and composite onset measures were computed and analyzed.
RESULTS: Significant gender disparities were noted in the transient component but not in the sustained component of speech-ABR. Statistically higher V/A amplitudes and less steeper V/A slopes were found in females. These gender differences were partially affected after controlling for the head size.
CONCLUSIONS: Head size is not the main contributing factor for gender disparities in speech-ABR outcomes. Gender-specific normative data can be useful when recording speech-ABR for clinical purposes.
METHODS: Speech-and-noise signals were presented to, and recorded from, six hearing aids mounted on a head and torso simulator. Test stimuli were nonsense words mixed with pink, cafeteria, or speech-modulated noise at 0 dB SNR. Fricatives /s, z/ were extracted from the recordings for analysis.
RESULTS: Analysis of the noise confirmed that MBNR in all hearing aids was activated for the recordings. More than 1.0 dB of acoustic change occurred to /s, z/ when MBNR was turned on in four out of the six hearing aids in the pink and cafeteria noise conditions. The acoustics of /s, z/ by female talkers were affected more than male talkers. Significant relationships between amount of noise reduction and acoustic change of /s, z/ were found. Amount of noise reduction accounts for 42.8% and 16.8% of the variability in acoustic change for /s/ and /z/ respectively.
CONCLUSION: Some clinically-available implementations of MBNR have measurable effects on the acoustics of fricatives. Possible implications for speech perception are discussed.
METHODS: The prospective clinical study was conducted at Selayang Hospital (SH) and Hospital Canselor Tuanku Muhriz (HCTM) within one year. A total of 38 children ranging from 3 to 18 years old underwent hearing evaluation using ABR tests and MSSR under sedation. The duration of both tests were then compared.
RESULTS: The estimated hearing threshold of frequency specific chirp MSSR showed good correlation with ABR especially in higher frequencies such as 2000 Hz and 4000Hz with the value of cronbach alpha of 0.890, 0.933, 0.970 and 0.969 on 500Hz, 1000Hz, 2000Hz and 4000Hz. The sensitivity of MSSR is 0.786, 0.75, 0.957 and 0.889 and specificity is 0.85, 0.882, 0.979 and 0.966 over 500Hz, 1000Hz, 2000Hz and 4000Hz. The duration of MSSR tests were shorter than ABR tests in normal hearing children with an average of 35.3 minutes for MSSR tests and 46.4 minutes for ABR tests. This can also be seen in children with hearing loss where the average duration for MSSR tests is 40.0 minutes and 52.0 minutes for ABR tests.
CONCLUSION: MSSR showed good correlation and reliability in comparison with ABR especially on higher frequencies. Hence, MSSR is a good clinical test to diagnose children with hearing loss.
MATERIALS AND METHODS: The EEG signal was used as a brain response signal, which was evoked by two auditory stimuli (Tones and Consonant Vowels stimulus). The study was carried out on Malaysians (Malay and Chinese) with normal hearing and with hearing loss. A ranking process for the subjects' EEG data and the nonlinear features was used to obtain the maximum classification accuracy.
RESULTS: The study formulated the classification of Normal Hearing Ethnicity Index and Sensorineural Hearing Loss Ethnicity Index. These indices classified the human ethnicity according to brain auditory responses by using numerical values of response signal features. Three classification algorithms were used to verify the human ethnicity. Support Vector Machine (SVM) classified the human ethnicity with an accuracy of 90% in the cases of normal hearing and sensorineural hearing loss (SNHL); the SVM classified with an accuracy of 84%.
CONCLUSION: The classification indices categorized or separated the human ethnicity in both hearing cases of normal hearing and SNHL with high accuracy. The SVM classifier provided a good accuracy in the classification of the auditory brain responses. The proposed indices might constitute valuable tools for the classification of the brain responses according to the human ethnicity.