Fast Automated Auditory Brainstem Response (AABR) using new non linear Maximum Length Sequence (MLS) reconstruction and automated signal detection (Ujian respon auditori batang otak automatik yang cepat menggunakan Non Linear Maximum Length Sequence (MLS) Reconstruction dan Automated Signal Detection)

Fast Automated Auditory Brainstem Response (AABR) using new non linear Maximum Length Sequence (MLS) reconstruction and automated signal detection (Ujian respon auditori batang otak automatik yang cepat menggunakan Non Linear Maximum Length Sequence (MLS) Reconstruction dan Automated Signal Detection)

The automated auditory brainstem response (AABR) is one of the important tools in Universal Newborn Hearing Screening (UNHS) because of its high sensitivity and specificity. However AABR recording time is unacceptably long and imposes significant cost to the UNHS program. determined that the non-det...

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Main Authors: Dzulkarnain, Ahmad Aidil Arafat, Wilson, Wayne, Bradley, Andrew, Petoe, Matthew, Smith, Andrew, Jamaluddin, Saiful Adli, Rahmat, Sarah, Moon, Jackie, Hanapiah, Nurhazwani
Format: Article
Language:English
Published: Penerbit Universiti Kebangsaan Malaysia 2010
Subjects:
R Medicine (General)
Online Access:http://irep.iium.edu.my/26073/
http://irep.iium.edu.my/26073/
http://irep.iium.edu.my/26073/1/Acoustic_Perception_Features_in_Normal.pdf
id iium-26073
recordtype eprints
spelling iium-260732013-07-16T02:32:06Z http://irep.iium.edu.my/26073/ Fast Automated Auditory Brainstem Response (AABR) using new non linear Maximum Length Sequence (MLS) reconstruction and automated signal detection (Ujian respon auditori batang otak automatik yang cepat menggunakan Non Linear Maximum Length Sequence (MLS) Reconstruction dan Automated Signal Detection) Dzulkarnain, Ahmad Aidil Arafat Wilson, Wayne Bradley, Andrew Petoe, Matthew Smith, Andrew Jamaluddin, Saiful Adli Rahmat, Sarah Moon, Jackie Hanapiah, Nurhazwani R Medicine (General) The automated auditory brainstem response (AABR) is one of the important tools in Universal Newborn Hearing Screening (UNHS) because of its high sensitivity and specificity. However AABR recording time is unacceptably long and imposes significant cost to the UNHS program. determined that the non-deterministic response of the MLS will contribute to a poor SNR across the different MLS stimulus rates. This is because the MLS ABR response to each stimulus varies with the varying inter-stimulus intervals, and any improvement in SNR depends on the response to each stimulus being the same. In other words, the MLS is linear but the auditory system is non-linear. One possible method to overcome the mismatch between the linear MLS and the non-linear auditory system is to modify the to account for the non-linearities of the auditory system (Bradley & Wilson, 2008). This modified could compensate for the variability in the ABR amplitudes and latencies caused by variability in the inter stimulus intervals. Therefore, this study aims to reduce the time required to complete an AABR assessment for UNHS. 492 AABR waveforms from 126 neonates who underwent UNHS were included in the final data analysis. Those AABRs were acquired at 35 dBnHL and at six different stimulus repetition rates (33, 90, 125, 250 and 418 clicks per seconds). The recording was made using standard clicks (at 33 and 90 cps) and Maximum Length Sequence (MLS) with linear and new non linear MLS reconstruction (at 90, 125, 250 and 418 cps). The time to AABR detection for all stimulus repetition rates were determined using variance ratio analysis (Fsp at 99% confidence level). The result showed that all MLS median detection time was significantly different than the standard click at 33 cps (Mann Whitney U test, p< 0.001), linear and non linear MLS at 418 cps median test time was significantly different than the standard click at its maximum rate 90 cps (Mann Whitney U test, p< 0.001) and MLS linear and MLS non linear reconstruction median test time was statistically different (Friedman test, p< 0.003). The best median time to detection was 3.59 s provided by the MLS non linear reconstruction stimulus at 418 cps. This study concludes that the combination MLS non linear reconstruction and Fsp holds significant promise to reduce UNHS test time. Penerbit Universiti Kebangsaan Malaysia 2010 Article PeerReviewed application/pdf en http://irep.iium.edu.my/26073/1/Acoustic_Perception_Features_in_Normal.pdf Dzulkarnain, Ahmad Aidil Arafat and Wilson, Wayne and Bradley, Andrew and Petoe, Matthew and Smith, Andrew and Jamaluddin, Saiful Adli and Rahmat, Sarah and Moon, Jackie and Hanapiah, Nurhazwani (2010) Fast Automated Auditory Brainstem Response (AABR) using new non linear Maximum Length Sequence (MLS) reconstruction and automated signal detection (Ujian respon auditori batang otak automatik yang cepat menggunakan Non Linear Maximum Length Sequence (MLS) Reconstruction dan Automated Signal Detection). Jurnal Sains Kesihatan Malaysia, supp. . p. 73. ISSN 1675-8161 http://www.ukm.my/jskm/melayu/index.html
repository_type Digital Repository
institution_category Local University
institution International Islamic University Malaysia
building IIUM Repository
collection Online Access
language English
topic R Medicine (General)
spellingShingle R Medicine (General)
Dzulkarnain, Ahmad Aidil Arafat
Wilson, Wayne
Bradley, Andrew
Petoe, Matthew
Smith, Andrew
Jamaluddin, Saiful Adli
Rahmat, Sarah
Moon, Jackie
Hanapiah, Nurhazwani
Fast Automated Auditory Brainstem Response (AABR) using new non linear Maximum Length Sequence (MLS) reconstruction and automated signal detection (Ujian respon auditori batang otak automatik yang cepat menggunakan Non Linear Maximum Length Sequence (MLS) Reconstruction dan Automated Signal Detection)
description The automated auditory brainstem response (AABR) is one of the important tools in Universal Newborn Hearing Screening (UNHS) because of its high sensitivity and specificity. However AABR recording time is unacceptably long and imposes significant cost to the UNHS program. determined that the non-deterministic response of the MLS will contribute to a poor SNR across the different MLS stimulus rates. This is because the MLS ABR response to each stimulus varies with the varying inter-stimulus intervals, and any improvement in SNR depends on the response to each stimulus being the same. In other words, the MLS is linear but the auditory system is non-linear. One possible method to overcome the mismatch between the linear MLS and the non-linear auditory system is to modify the to account for the non-linearities of the auditory system (Bradley & Wilson, 2008). This modified could compensate for the variability in the ABR amplitudes and latencies caused by variability in the inter stimulus intervals. Therefore, this study aims to reduce the time required to complete an AABR assessment for UNHS. 492 AABR waveforms from 126 neonates who underwent UNHS were included in the final data analysis. Those AABRs were acquired at 35 dBnHL and at six different stimulus repetition rates (33, 90, 125, 250 and 418 clicks per seconds). The recording was made using standard clicks (at 33 and 90 cps) and Maximum Length Sequence (MLS) with linear and new non linear MLS reconstruction (at 90, 125, 250 and 418 cps). The time to AABR detection for all stimulus repetition rates were determined using variance ratio analysis (Fsp at 99% confidence level). The result showed that all MLS median detection time was significantly different than the standard click at 33 cps (Mann Whitney U test, p< 0.001), linear and non linear MLS at 418 cps median test time was significantly different than the standard click at its maximum rate 90 cps (Mann Whitney U test, p< 0.001) and MLS linear and MLS non linear reconstruction median test time was statistically different (Friedman test, p< 0.003). The best median time to detection was 3.59 s provided by the MLS non linear reconstruction stimulus at 418 cps. This study concludes that the combination MLS non linear reconstruction and Fsp holds significant promise to reduce UNHS test time.
format Article
author Dzulkarnain, Ahmad Aidil Arafat
Wilson, Wayne
Bradley, Andrew
Petoe, Matthew
Smith, Andrew
Jamaluddin, Saiful Adli
Rahmat, Sarah
Moon, Jackie
Hanapiah, Nurhazwani
author_facet Dzulkarnain, Ahmad Aidil Arafat
Wilson, Wayne
Bradley, Andrew
Petoe, Matthew
Smith, Andrew
Jamaluddin, Saiful Adli
Rahmat, Sarah
Moon, Jackie
Hanapiah, Nurhazwani
author_sort Dzulkarnain, Ahmad Aidil Arafat
title Fast Automated Auditory Brainstem Response (AABR) using new non linear Maximum Length Sequence (MLS) reconstruction and automated signal detection (Ujian respon auditori batang otak automatik yang cepat menggunakan Non Linear Maximum Length Sequence (MLS) Reconstruction dan Automated Signal Detection)
title_short Fast Automated Auditory Brainstem Response (AABR) using new non linear Maximum Length Sequence (MLS) reconstruction and automated signal detection (Ujian respon auditori batang otak automatik yang cepat menggunakan Non Linear Maximum Length Sequence (MLS) Reconstruction dan Automated Signal Detection)
title_full Fast Automated Auditory Brainstem Response (AABR) using new non linear Maximum Length Sequence (MLS) reconstruction and automated signal detection (Ujian respon auditori batang otak automatik yang cepat menggunakan Non Linear Maximum Length Sequence (MLS) Reconstruction dan Automated Signal Detection)
title_fullStr Fast Automated Auditory Brainstem Response (AABR) using new non linear Maximum Length Sequence (MLS) reconstruction and automated signal detection (Ujian respon auditori batang otak automatik yang cepat menggunakan Non Linear Maximum Length Sequence (MLS) Reconstruction dan Automated Signal Detection)
title_full_unstemmed Fast Automated Auditory Brainstem Response (AABR) using new non linear Maximum Length Sequence (MLS) reconstruction and automated signal detection (Ujian respon auditori batang otak automatik yang cepat menggunakan Non Linear Maximum Length Sequence (MLS) Reconstruction dan Automated Signal Detection)
title_sort fast automated auditory brainstem response (aabr) using new non linear maximum length sequence (mls) reconstruction and automated signal detection (ujian respon auditori batang otak automatik yang cepat menggunakan non linear maximum length sequence (mls) reconstruction dan automated signal detection)
publisher Penerbit Universiti Kebangsaan Malaysia
publishDate 2010
url http://irep.iium.edu.my/26073/
http://irep.iium.edu.my/26073/
http://irep.iium.edu.my/26073/1/Acoustic_Perception_Features_in_Normal.pdf
first_indexed 2023-09-18T20:38:52Z
last_indexed 2023-09-18T20:38:52Z
_version_ 1777409230619279360

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