Adaptive noise cancellation in a multimicrophone system for distortion product otoacoustic emission acquisition

• Published in: IEEE transactions on biomedical engineering Vol. 47; no. 9; pp. 1154 - 1164
• Main Authors: Delgado, R.E., Ozdamar, O., Rahman, S., Lopez, C.N.
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.09.2000; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Acoustic emissions; Acoustic noise; Acquisitions & mergers; Algorithms; Attenuation; Biological and medical sciences; Biomedical Engineering; Cells; Computer Simulation; Ear; Ears & hearing; Ent. Stomatology; Female; Frequency; Hair; Hearing Tests - instrumentation; Hearing Tests - statistics & numerical data; Humans; Infant; Investigative techniques, diagnostic techniques (general aspects); Male; Medical sciences; Microphones; Noise; Noise abatement; Noise cancellation; Noise levels; Noise reduction; Noise standards; Otoacoustic Emissions, Spontaneous; Pathology. Cytology. Biochemistry. Spectrometry. Miscellaneous investigative techniques; Probes; Signal distortion; Signal Processing, Computer-Assisted; Signal to noise ratio; System testing; Human; Hearing; Microphone; Acoustic stimulus; Otoacoustic emission; Noise reduction; Adaptive system; Distortion; Technique; Signal analysis; Outer hair cell; Signal to noise ratio
• ISSN: 0018-9294; 1558-2531
• DOI: 10.1109/10.867919

This study focuses on adaptive noise cancellation (ANC) techniques for the acquisition of distortion product otoacoustic emissions (DPOAEs). Otoacoustic emissions (OAEs) are very low level sounds produced by the outer hair cells of normal cochleas, spontaneously or in response to sound stimulation as a byproduct of a frequency and threshold sensitivity increasing mechanism. Current OAE recording systems rely on test probe noise attenuation and synchronous ensemble averaging for increasing signal-to-noise ratios (SNRs). The efficiency of an ANC algorithm for noise suppression was investigated using three microphones: one placed in the test ear, one in the nontest ear for internal noise reference; one near the subject's head for external noise reference. The system proposed was tested with simulations, off-line averaging and real-time implementation of the ANC algorithm. Simulation results showed that the technique had a potential noise reduction capability of 24 dB for complex multifrequency noise signals. Off-line results mere positive, with a mean SNR improvement of 4.9 dB. Real-time results indicated that the use of an ANC algorithm in combination with standard averaging methods can reduce noise levels by as much as 10 dB beyond that obtained with standard noise reduction methods and probe attenuation alone.