Real-time threshold determination of auditory brainstem responses by cross-correlation analysis

Haoyu Wang; Bei Li; Yan Lu; Kun Han; Haibin Sheng; Jialei Zhou; Yumeng Qi; Xueling Wang; Zhiwu Huang; Lei Song; Yunfeng Hua

iScience (Nov 2021)

Real-time threshold determination of auditory brainstem responses by cross-correlation analysis

Haoyu Wang,
Bei Li,
Yan Lu,
Kun Han,
Haibin Sheng,
Jialei Zhou,
Yumeng Qi,
Xueling Wang,
Zhiwu Huang,
Lei Song,
Yunfeng Hua

Affiliations

Haoyu Wang: Department of Otolaryngology-Head and Neck Surgery, Shanghai Ninth People's Hospital, Shanghai, China; Ear Institute, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Shanghai Key Laboratory of Translational Medicine on Ear and Nose Diseases, Shanghai, China; Shanghai Institute of Precision Medicine, Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
Bei Li: Department of Otolaryngology-Head and Neck Surgery, Shanghai Ninth People's Hospital, Shanghai, China
Yan Lu: Shanghai Institute of Precision Medicine, Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
Kun Han: Department of Otolaryngology-Head and Neck Surgery, Shanghai Ninth People's Hospital, Shanghai, China
Haibin Sheng: Department of Otolaryngology-Head and Neck Surgery, Shanghai Ninth People's Hospital, Shanghai, China; Ear Institute, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Shanghai Key Laboratory of Translational Medicine on Ear and Nose Diseases, Shanghai, China
Jialei Zhou: Department of Otorhinolaryngology-Head & Neck Surgery, Shanghai Children's Hospital, Shanghai Jiao Tong University, Shanghai, China
Yumeng Qi: Shanghai Institute of Precision Medicine, Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
Xueling Wang: Department of Otolaryngology-Head and Neck Surgery, Shanghai Ninth People's Hospital, Shanghai, China; Ear Institute, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Shanghai Key Laboratory of Translational Medicine on Ear and Nose Diseases, Shanghai, China
Zhiwu Huang: Department of Otolaryngology-Head and Neck Surgery, Shanghai Ninth People's Hospital, Shanghai, China; Ear Institute, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Shanghai Key Laboratory of Translational Medicine on Ear and Nose Diseases, Shanghai, China
Lei Song: Department of Otolaryngology-Head and Neck Surgery, Shanghai Ninth People's Hospital, Shanghai, China; Ear Institute, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Shanghai Key Laboratory of Translational Medicine on Ear and Nose Diseases, Shanghai, China; Corresponding author
Yunfeng Hua: Department of Otolaryngology-Head and Neck Surgery, Shanghai Ninth People's Hospital, Shanghai, China; Ear Institute, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Shanghai Key Laboratory of Translational Medicine on Ear and Nose Diseases, Shanghai, China; Shanghai Institute of Precision Medicine, Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Corresponding author

Journal volume & issue: Vol. 24, no. 11
p. 103285

Abstract

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Summary: Auditory brainstem response (ABR) serves as an objective indication of auditory perception at a given sound level and is nowadays widely used in hearing function assessment. Despite efforts for automation over decades, ABR threshold determination by machine algorithms remains unreliable and thereby one still relies on visual identification by trained personnel. Here, we described a procedure for automatic threshold determination that can be used in both animal and human ABR tests. The method terminates level averaging of ABR recordings upon detection of time-locked waveform through cross-correlation analysis. The threshold level was then indicated by a dramatic increase in the sweep numbers required to produce “qualified” level averaging. A good match was obtained between the algorithm outcome and the human readouts. Moreover, the method varies the level averaging based on the cross-correlation, thereby adapting to the signal-to-noise ratio of sweep recordings. These features empower a robust and fully automated ABR test.

Published in iScience

ISSN: 2589-0042 (Online)
Publisher: Elsevier
Country of publisher: United States
LCC subjects: Science
Website: http://www.cell.com/iscience/home

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