Evoked Auditory Responses in Normals across Stimulus Level

This database is described in:

Silva, I., Epstein, M. Estimating loudness growth from tone-burst evoked responses. J. Acoust. Soc. Am. 127(6):3629-3642; 2010 (June). [doi: 10.1121/1.3397457]

Please cite this publication when referencing this material, and also include the standard citation for PhysioNet:

Goldberger AL, Amaral LAN, Glass L, Hausdorff JM, Ivanov PCh, Mark RG, Mietus JE, Moody GB, Peng C-K, Stanley HE. PhysioBank, PhysioToolkit, and PhysioNet: Components of a New Research Resource for Complex Physiologic Signals. Circulation 101(23):e215-e220 [Circulation Electronic Pages; http://circ.ahajournals.org/cgi/content/full/101/23/e215]; 2000 (June 13).

This database, created and contributed by Michael J. Epstein and Ikaro Silva, was generated as part of a study examining evoked potentials and loudness growth. The database consists of two sets of physiological signals: auditory brainstem response (ABR) and otoacoustic emissions (OAE) and two sets of psychoacoustical estimates of loudness as a function of peak sound pressure level (peSPL). The ABRs were recorded simultaneously with the OAEs in a sound-attenuating, electrically shielded booth. Listeners had three electrodes affixed: the non-inverting electrode was positioned on the forehead, the inverting electrode was positioned on the ipsilateral mastoid (behind the ear), and the ground electrode positioned on the contralateral mastoid. (These locations were scrubbed with alcohol prior to the electrode placement.) The electrode signal was then sent to a GRASS QP511 Quad AC Amplifier, where it was band-pass filtered from 30-3000 Hz, amplified by a factor of 50000, sent to a 32-bit Lynx Two Soundcard (outside the booth), and sampled at 48 kHz. The effective resolution of the recording was 24-bits. Stimuli were presented at a presentation rate of about 24 Hz (2002 samples/trial).

In addition to the raw data, for each level, two zero-mean weighted averages of ABR and OAE recordings were made. The first average consisted of a weighted mean (Elberling and Wahlgreen, 1985) of all the trials in the first half, and the second average consisted of a weighted mean of all the trials in the second half. For each frequency, the stimulus was presented in ascending order from the listener’s threshold to 100 dB peSPL in steps of 5 dB. Threshold was determined from the maximum threshold of the CMM or ME procedure. For the average ABR recordings, an artifact rejection threshold of 50 uV was applied.

Data files

For each subject Nx, you will find the following files:

Averaged Data

Nx_evoked_avelevel_Ffreq_Rrep.dat
(binary) signal file containing the ABR and OAE signals
Nx_evoked_avelevel_Ffreq_Rrep.hea
(text) header file, with comments indicating the sex, ear presented, and age of the subject, number of trials used in the average, estimated residual noise level, and estimated weighted signal-to-noise ratio (wnsfmp)
Nx_LoudnessData_Ffreq.txt
(text) the zero-mean loudness measurements (in log units) obtained via psychoacoustical procedures (magnitude estimation and cross-modality matching) at each of the measured levels.

Raw Data

Nx_evoked_rawlevel_Ffreq_Rrep.dat
(binary) signal file containing the ABR and OAE signals
Nx_evoked_rawlevel_Ffreq_Rrep.hea
(text) header file, with comments indicating stimulus level, stimulus frequency, ear presented, trial length (samples) and condition.
Nx_evoked_rawlevel_Ffreq_Rrep.trg
(binary) annotation file, in which the T annotation indicates the onset of the trial (with respect to stimulus onset).

where:

x = listener ID number (1-8)
level = peSPL of the stimulus (starting from the listener's threshold and increasing in steps of 5 dB until 100 dB peSPL)
freq = stimulus frequency in KHz
rep = number indicating if it's either the first or second independent average

In fewer than 20% of the cases, one of the channels was severely corrupted by electrical artifacts and has been removed from the files (the record names in these cases end with _x). The header file indicates which signal remains in each case (if the only signal has units of 'V', then that signal is the OAE; if it has units of 'nV', then that signal is the ABR).

Software

A sample program (average.c) shows how to use the annotation file to get a standard (non-weighted) averaging from the data file (note that this code does not apply artifact rejection and is included only as an example to show how to process the raw data).

A MATLAB function (mat2wfdb.m) was used while preparing these files to convert the .mat data files in which the data were originally stored to a supported WFDB data format.

Note that this data set contains 24-bit samples (in fact, these are the first recordings in PhysioBank with a resolution exceeding 16 bits). Software linked with version 10.5.0 of the WFDB library, or any later version, can be used to read these records, but earlier versions (released before 16 March 2010) will be unable to do so. The most recent version of the WFDB Software Package contains the WFDB library and many applications that can be used to read these recordings.

Relevant Publications

In addition to the article cited at the top of this page, these publications provide additional background and describe related work:

Silva, I. Estimation of Post-Average SNR from Evoked Responses Under Non-Stationary Noise. IEEE TBME, 56(8):2123-2130; 2009. [doi: 10.1109/TBME.2009.2021400] [Abstract]
Epstein, M. and Silva, I. Analysis of parameters for the estimation of loudness from tone-burst otoacoustic emissions. J. Acoust. Soc. Am. 125(6):3855-3864; 2009.[doi: 10.1121/1.3106531]
Da Silva, Ikaro Garcia Araujo. Objective Estimation of Loudness Growth Using Tone Burst Evoked Auditory Responses. Electrical Engineering Dissertations, Northeastern University, 2009. Paper 23. http://hdl.handle.net/2047/d20000027

Acknowledgments

This database was contributed to PhysioBank by Ikaro Silva, who collected the data at Northeastern University in collaboration with Prof. Michael Epstein. They wish to thank Dr. Jeremy Marozeau for contributing to the initial development of the software for the recording of the evoked responses, Dr. Ying-Yee Kong for assistance with calibration of apparatus, Nora Rosenfeld, Shoshannah Kantor, and Gwen Deevy for assistance with data collection, This work was supported by the Capita Foundation and NIH (Grant No. NIDCD 1R03DC009071).

Additional information

Contact: ikarosilva at ieee dot org or m.epstein at neu dot edu

Questions and Comments

If you would like help understanding, using, or downloading content, please see our Frequently Asked Questions.

If you have any comments, feedback, or particular questions regarding this page, please send them to the webmaster.

Comments and issues can also be raised on PhysioNet's GitHub page.

Updated Wednesday, 12 August 2015 at 17:16 EDT

PhysioNet is supported by the National Institute of General Medical Sciences (NIGMS) and the National Institute of Biomedical Imaging and Bioengineering (NIBIB) under NIH grant number 2R01GM104987-09.