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919 results for “Hearing”
OHHR – The Oldenburg Hearing Health Record [Dataset]
<p><strong>Description of the dataset</strong></p> <p>The Oldenburg Hearing Health Record (OHHR) provides a publicly accessible dataset that can be used to advance hearing health research. It includes a constellation of data collected from 581 participants (aged 18–86 years<em>; </em>255 female; <em>Mean age = 67.31 years; SD = 11.93</em>) between 2013 and 2015 at the Hörzentrum Oldenburg in collaboration with the Cluster of Excellence "Hearing4all". The data was anonymized in accordance with the General Data Protection Regulation (GDPR; Regulation (EU) 2016/679). Each participant was assigned a unique identifier to maintain anonymity while enabling multivariate individualized analyses. </p> <p>All the different data types are listed below:<br><br><strong>Subjective Measures</strong></p> <ul> <li>Home Questionnaire</li> <li>SF-12 Health Survey</li> <li>Technology Readiness Questionnaire</li> <li>Anamnesis</li> </ul> <p><strong>Audiological Tests</strong></p> <ul> <li>Pure Tone Audiometry</li> <li>Adaptive Categorical Loudness Scaling</li> <li>Digit Triplet Test (Speech Reception Threshold in Noise: Screening)</li> <li>Göttingen Sentence Test (Speech Reception Threshold in Noise)</li> </ul> <p><strong>Cognitive Measures</strong></p> <ul> <li>DemTect</li> <li>WortSchatz</li> </ul> <p><strong>Demographic Information</strong></p> <ul> <li>Socio-economic data</li> <li>Scheuch-Winkler Index (calculated)</li> </ul> <p><strong>Supporting Documentation</strong></p> <p><strong>MethodsDescription.rtf/.pdf:</strong> Provides detailed explanations of data type and collection procedures.<br><strong>data.zip/metadata</strong><strong>: </strong>Includes schema and description files for all data tables.</p> <p>A supporting paper was published on Scientific Data:</p> <div> <div> <p>Jafri, S., Berg, D., Buhl, M. <em>et al.</em> The Oldenburg Hearing Health Record (OHHR). <em>Sci Data</em> <strong>12</strong>, 1546 (2025). https://doi.org/10.1038/s41597-025-05884-y</p> </div> </div>
The Hearpiece database of individual transfer functions of an openly available in-the-ear earpiece for hearing device research
<p>We present a database of acoustic transfer functions of the Hearpiece, an openly available multi-microphone multi-driver in-the-ear earpiece for hearing device research. The database includes HRTFs for 87 incidence directions as well as responses of the drivers, all measured at the four microphones of the Hearpiece as well as the eardrum in the occluded and open ear. The transfer functions were measured in both ears of 25 human subjects and a KEMAR with anthropometric ears for five reinsertions of the device. We describe the measurements of the database and analyse derived acoustic parameters of the device. All regarded transfer functions are subject to differences between subjects as well as variations due to reinsertion into the same ear. Also, the results show that KEMAR measurements represent a median human ear well for all assessed transfer functions. The database is a rich basis for development, evaluation and robustness analysis of multiple hearing device algorithms and applications.</p>
Data and materials from: "Towards Auditory Profile-based Hearing-aid Fitting: Fitting Rationale and Pilot Evaluation"
<p>This repository contains materials and data used and described in:</p> <p><strong>Sanchez-Lopez, R., Fereczkowski, M., Santurette, S., Dau, T., Neher, T. (2021). Towards Auditory Profile-based Hearing-aid Fitting: Fitting Rationale and Pilot Evaluation. <em>Audiol. Res.</em> 11, no. 1: 10-21. <a href="https://doi.org/10.3390/audiolres11010002 ">https://doi.org/10.3390/audiolres11010002 </a></strong></p> <p> </p> <p><strong>Abstract</strong></p> <p><strong>Background</strong> - The clinical characterization of hearing deficits for hearing-aid fitting purposes is typically based on the pure-tone audiogram only. In a previous study, a group of hearing-impaired listeners completed a comprehensive test battery designed to tap into different dimensions of hearing abilities. A data-driven analysis of the data yielded four clinically relevant patient subpopulations or “auditory profiles”. The purpose of the current study was to propose and pilot-test profile-based hearing-aid settings to explore their potential for providing more targeted hearing-aid treatment.<br> <strong>Methods </strong>- Four candidate hearing-aid settings were developed and evaluated by a subset of the participants tested previously. The evaluation consisted of multi-comparison preference ratings carried out in realistic sound scenarios.<br> <strong>Results </strong>- Listeners belonging to the different auditory profiles showed different patterns of preference for the tested hearing-aid settings that were largely consistent with the expectations.<br> <strong>Conclusion</strong> - The results of this pilot evaluation support further investigations into stratified, profile-based hearing-aid fitting with wearable hearing aids.</p> <p>Please cite this article when using the data</p> <p> </p> <p><strong>Description of the files:</strong></p> <ul> <li><strong>APBHAF_Audiofiles.zip: </strong>Audio files used in the SenseLabOnline environment. Each folder corresponds to one participant.</li> <li><strong>APBHAF_MUSHA.xlsx: </strong>Raw Data of the MUSHA experiment.</li> <li><strong>APBHAF_MUSHA_Analysis.R: </strong>R code for the data analysis.</li> <li><strong>MUS_SoundScenes.mat</strong>: Mat file with a structure 1x9 MUS with the raw acoustic signals before processing with the hearing-aid simulator. <ul> <li>CurrentMixture: matrix consisting of the simulated acoustic signal recorded by the 4 microphones of the hearing-aid satellites: 1) front-left, 2) back-left, 3) front-right, 4) back-right.</li> <li>CurrentAnchor: matrix consisting of the simulated acoustic signal recorded by the 4 microphones of the hearing-aid satellites: 1) front-left, 2) back-left, 3) front-right, 4) back-right. The Anchor is -6 dB SNR.</li> <li>SampleLabel: Either "Kantine", "Traffic" or "Quiet"</li> <li>ConditionLabel: Either "Cond1", "Cond2" or "Cond3"</li> <li>fsmix: sampling frequency. For all signals must be 32000Hz</li> </ul> </li> <li><strong>MUSHA_Instruction: </strong>Instructions used for explaining the task and the environment.</li> </ul> <p>* The participant IDs in each of the files has been assigned randomly to ensure the anonymization of the data. The pseudo-anonymized data might be shared under request by direct correspondence with the authors.</p>
Human auditory ecology : Extending hearing research to the perception of natural soundscapes by humans in rapidly-changing environments
<p>The audiomaterial corresponding to boreal, tropical and temperate forests, desert, savannah, sub-alpine meadow, and the construction site in New York is copyrighted (license from Wild Sanctuary) and cannot be used without explicit agreement of Bernie Krause. Additional audiomaterial (urban park and street traffic in Paris, France; fast street traffic in Marseille, France; English and French speech material) may only be used with the explicit agreement of the following authors: Jérôme Sueur and Sylvain Haupert (Museum National d'Histoire Naturelle in Paris, France); Sabine Meunier (LMA/CNRS in Marseille, France); Franck Ramus (CNRS in Paris, France) (see Figure legends).</p>
Original Recording of Freiburg Words for Testing Hearing with Speech
<p>The files contain recordings of the monosyllabic words, polysyllabic numbers, and CCITT noise (ITU, 1993) of the Freiburg Speech Test (Hahlbrock, 1953). The words are given in DIN 45621-1:1995. The 400 monosyllables are organized in 20 test lists à 20 nouns. They are stored in "Einsilbige Wörter.zip". The name of each wav-file includes the number of the test list (L01, L02, …) and the position of the word within the test list (W01, W02, …). The 100 polysyllables are organized in 10 test lists à 10 numbers. They are stored in "Mehrsilbige Wörter (Zahlen).zip" with similar nomenclature. DIN 45626-1:1995 describes the recordings. Speech signals were recorded in 1969 in the studios of Norddeutscher Rundfunk, Hamburg, Germany, with the speaker Claus Wunderlich (Brinkmann, 1974). The recordings were processed by Physikalisch-Technische Bundesanstalt, Braunschweig, Germany, and Polygram International, Hannover, Germany. Later, the recordings were digitalized by Siemens AG and distributed on compact disc by "Siemens Audiologische Technik GmbH" (legal successor WS Audiology A/S) with the title "Wörter für Gehörprüfung mit Sprache" ("Words for hearing tests with speech") under item no. 7970155. The words were cut out as accurately as possible, i.e., with as little background before and after each word as possible (see Winkler and Holube, 2016a). The CCITT noise was originally included for calibration purposes, but is often used as noise masker when the monosyllables are presented in background noise.</p>
Hearing Anything Anywhere - the DIFFRIR dataset
<h2>Overview</h2> <p>This is the DIFFRIR dataset, released as part of "Hearing Anything Anywhere" (CVPR, 2024).</p> <p>It contains a dataset of monoaural and binaural Room Impulse Responses (RIRs) and music recordings in four different rooms:</p> <ol> <li>A <strong>Classroom</strong></li> <li>An acoustically <strong>Dampened Room</strong></li> <li>A <strong>Hallway</strong></li> <li><strong>A Complex Room</strong> (shaped like a pentagonal prism with several irregular surfaces of varying materials and pillars)</li> </ol> <p>In each room, we measure RIRs using both monoaural and binaural microphones at several hundred precisely-measured locations. We record different music recordings from these locations as well.</p> <p>We also record several <strong>configurations </strong>in the Dampened Room, the Hallway, and the Complex Room, where we rotate or translate the location of the speaker used to measure the RIR, or insert one or more whiteboard panels at different locations in the room. Each of these configurations also contains measurements of monoaural and binaural RIRs and music.</p> <h2>Organization</h2> <p>There are 14 .zip files in this dataset, containing data from the 14 room configurations across the four rooms. Zip files with the suffix "base" contain data from the base configuration, and <code>hallwayPanel1.zip</code>, <code>hallwayPanel2.zip</code>, and <code>hallwayPanel3.zip</code> contain data from each of the three panel configurations in the hallway.</p> <h2>Files</h2> <p>All data is stored as <code><strong>.npy</strong></code> files. All audio data is stored as numpy float64 arrays with a sampling rate of <strong>48,000 Hz.</strong></p> <p>All audio files are <strong>aligned</strong> such that the time the recording starts is equal to the time that the speaker begins playing the music or hypothetical impulse.</p> <p> </p> <p>In the descriptions below, we specify the contents and shape of each file. <code>N_mono</code> is the number of monoaural data points, and <code>N_binaural</code> is the number of binaural data points recorded in the room configuration.</p> <p>In each .zip file, we have <strong>5 </strong>files for each monoaural data point:</p> <ol> <li><code><strong>RIRs.npy</strong></code> - (N_mono_data, 671,884) - monoaural room impulse responses measured for the room's configuration.</li> <li><code><strong>music.npy</strong></code> - (N_mono_data, N_songs, 623,884) - monoaural music recordings, measured at the same locations as <strong><code>RIRs.npy</code></strong>. N_songs is either 1 or 5.</li> <li><code><strong>xyzs.npy</strong></code> - (N_mono_data, 3) - the xyz microphone locations in meters at which <code>RIRs.npy</code> and <code>music.npy</code> were recorded.</li> <li><code><strong>music_dls.npy</strong></code> - (N_mono_data, N_songs, 624000) - music source files for each of the monoaural music data points. The source is measured by recording a loopback signal, and is aligned such that convolving a source from <code><strong>music_dls.npy</strong></code> with the corresponding RIR in <code>RIRs.npy</code> estimates the corresponding music recording in <strong><code>music.npy</code>.</strong></li> <li><code><strong>mic_numbers.npy</strong></code> - (N_mono,) - an array of integers identifying the microphone of each recording in <code>RIRs.npy</code> and <code>music.npy</code>.</li> </ol> <p>Each .zip file also contains <strong>4 </strong>files for each binaural data point:</p> <ol> <li><code><strong>bin_RIRs.npy</strong></code> - (N_binaural_data, 2, 671,884) - binaural room impulse responses measured for the room's configuration.</li> <li><code><strong>bin_music.npy</strong></code> - (N_binaural_data, N_songs, 2, 623,884) - binaural music recordings, measured at the same locations as <strong><code>bin_xyzs.npy</code></strong>. N_songs is 5.</li> <li><strong><code>bin_xyzs.npy</code> </strong>- (N_binaural_data, 3) - the xyz locations in meters at which each row in <code>bin_RIRs.npy</code> and <code>bin_music.npy</code> was recorded. The location is the <strong>center</strong> of the binaural microphone. To get the location of the left microphone, add 5.5 cm to the x location, and to get the location of the right microphone, subtract 5.5 cm from the x location (the binaural microphone was facing in the -y direction in all rooms/configurations).</li> <li><code><strong>bin_music_dls.npy</strong></code> - (N_binaural_data, N_songs, 624000) - music sources for each binaural data point, measured via direct line loopback.</li> </ol> <h2>Room Geometry, Speaker Location</h2> <p>The <strong>geometric measurements</strong> of the surfaces in the room are provided in the <code>rooms/</code> folder on the <a href="https://github.com/maswang32/hearinganythinganywhere/blob/main/README.md">github</a>, including speaker locations and the locations of all surfaces.</p> <h2>Microphone Calibrations</h2> <p>All monoaural microphone recordings were perfomed using EMM6 measurement microphones. They have already been adjusted to account for differences in microphone sensitivity according to the microphone's sensitivity at 1000 Hz.</p> <p>If you would like to perform more fine-grained microphone frequency calibration, the EMM6 calibration files for each dataset are included in <code><strong>mic_calibrations.zip</strong></code>. This folder contains four subfolders corresponding to each room. In each subfolder, we included the microphone calibration files .txt files, whose titles are {mic_id}_{mic_serial_number}.txt. {mic_id} corresponds to the microphone ID number provided in <code><strong>mic_numbers.npy</strong></code> for each monoaural data point. For more information on microphone calibration files, refer to <a href="https://www.daytonaudio.com/product/911/emm-6-electret-measurement-microphone">this</a> website.</p>
GWAS on self-reported hearing difficulty in the UK Biobank
<p>The dataset contains results of two genome-wide association studies for age-related hearing impairment (ARHI)-related traits as described in the following publication</p> <p><a href="https://www.sciencedirect.com/science/article/pii/S0002929719303477#!"><em>Wells HRR, Freidin MB, Zainul Abidin FN, Payton A, Dawes P, Munro KJ, Morton CC, Moore DR, Dawson SJ, Williams FMK. GWAS Identifies 44 Independent Associated Genomic Loci for Self-Reported Adult Hearing Difficulty in UK Biobank. Am J Hum Genet. 2019 Oct 3;105(4):788-802. doi: 10.1016/j.ajhg.2019.09.008. Epub 2019 Sep 26.</em></a> </p> <p>Please cite the article if using this dataset.</p> <p>Two files provide summary statistics for discovery analysis of <em><strong>Hearing difficulty (HD) </strong></em>and <em><strong>Hearing aid use (HAID)</strong></em> phenotypes for individuals of European descent from <a href="https://www.ukbiobank.ac.uk/">UK Biobank</a>.</p> <p><strong>Acknowledgements</strong></p> <p>The research was carried out using the UK Biobank Resource under application number 11516. H.R.R.W. is funded by a PhD Studentship Grant, S44, from Action on Hearing Loss. The study was also supported by funding from NIHR UCLH BRC Deafness and Hearing Problems Theme, a grant from MED_EL, and the NIHR Manchester Biomedical Research Centre. The English Longitudinal Study of Aging is jointly run by University College London, Institute for Fiscal Studies, University of Manchester, and National Centre for Social Research. Genetic analyses have been carried out by UCL Genomics and funded by the Economic and Social Research Council and the National Institute on Aging. Data governance was provided by the METADAC data access committee, funded by ESRC, Wellcome, and MRC (2015-2018: Grant Number MR/N01104X/1 2018-2020: Grant Number ES/S008349/1). TwinsUK is funded by the Wellcome Trust, Medical Research Council, European Union, the National Institute for Health Research (NIHR)-funded BioResource, Clinical Research Facility, and Biomedical Research Centre based at Guy’s and St Thomas’ NHS Foundation Trust in partnership with King’s College London. We would like to thank all the participants of UK Biobank, English Longitudinal Study of Aging, and TwinsUK.</p> <p><strong>Column headers:</strong></p> <p>SNP, SNP rsID</p> <p>CHR, chromosome</p> <p>BP, genomic position (GRCh37 build) </p> <p>ALLELE1, effect allele (coded as "1")</p> <p>ALLELE0, reference allele (coded as "0") </p> <p>A1FREQ, effect allele frequency</p> <p>INFO, imputation quality</p> <p>BETA, effect size of effect allele</p> <p>SE: standard error of effect size</p> <p>P, P-value of association (without GC correction)</p>
Recreational Reading as a Leisure Activity: Perspectives from Georgian and Finnish Hearing and deaf students
<p><em>Using a mixed methods approach, this study investigates Finnish and Georgian deaf students' attitudes towards leisure reading and the relationship between their reading intentions and actual reading. </em><em>The primary interest of the study is to identify the external factors that affect reading behaviour directly or indirectly. </em></p> <p><em>An Integrative Model of Planned Behaviour is used as a theoretical framework, where intention is considered the main determinant for the behaviour. </em></p> <p><em>The study is cross-cultural, bringing the experiences of two distinct countries together. <br><br></em></p> <p><em>Reading attitude is investigated quantitatively, using a 5-point Likert Scale survey. 29 statements are broken down into three variables: enjoyment ( statements 4-13), difficulty ( statements 14-22) and social reinforcement (statements 23-29). </em></p> <p>Follow-up focus group interviews investigated the perceived external factors that affect reading behaviour negatively. interview questions were also grouped under three categories: 1) General feelings about reading (experiential attitude or affect), 2) Influences from individuals, close networks or society (perceived norms) and situational or environmental restrictions affect behaviour performance (skills, knowledge, resources, other factors). </p> <p>The interview protocol, questions survey and row data are attached as files.</p> <p>Interview transcripts are saved in Finnish and Georgian languages and can be shared only upon a reasonable request. </p>
Virtual audiovisual scenes for hearing device fine-tuning
<p>The virtual audiovisual scenes in this upload were developed to be used during hearing device fine-tuning. By letting patients try out the settings of their hearing devices in a number of different daily-life situations, they can experience what it sounds like in different situations. The audiologist can then ask specific questions and make further adjustments to the settings. This may result in a better fit. The development of the virtual audiovisual scenes is documented in a paper presented at Forum Acusticum (Hendrikse, Dingemanse, Grimm, Hohmann, & Goedegebure, 2023). The development and evaluation of the fine-tuning procedure using these virtual audiovisual scenes will be the focus of future work, and the publication will be added to the related identifiers. This document provides a description of the virtual audiovisual scenes, software & hardware requirements, installation and usage instructions, and information about the licensing.</p> <p>For further information, contact Maartje Hendrikse (<a href="mailto:m.hendrikse@erasmusmc.nl">research.audiologie@erasmusmc.nl</a>).</p>
Genome-wide association statistics of Hearing Problems
<p>Genome-wide Association Statistics of Hearing Problems</p> <p>Citation: De Angelis F, Zeleznik OA, Wendt FR, Pathak GA, Tylee DS, De Lillo A, Koller D, Cabrera-Mendoza B, Clifford RE, Maihofer AX, Nievergelt CM, Curhan GC, Curhan SG, Polimanti R. Sex differences in the polygenic architecture of hearing problems in adults. Genome Med. https://doi.org/10.1186/s13073-023-01186-3</p> <p>COLUMN HEADERS<br> chromosome: chromosome<br> base_pair_location: position<br> effect_allele: effect allele (corresponds to the effect size’s sign; may not be the alternate allele)<br> other_allele: non-effect allele<br> beta: effect measured as beta, sign corresponds to the effect of the effect allele<br> standard_error: standard error of the effect<br> effect_allele_frequency: effect allele frequency in UK Biobank participants of European descent<br> p_value: p value of the association statistic<br> variant_id: variant identifier<br> rs_id: rsID of the variant<br> n: sample size per variant</p> <p> </p>
The Genetic Background of Hearing Loss in Patients with EVA and Cochlear Malformation
<p>This dataset comprises likely pathogenic variants identified through next-generation sequencing (NGS) using a multigene panel (237 genes associated with hearing loss), as well as clinical exome sequencing (TruSightOne Sequencing Panel). Raw data obtained during variant validation using Sanger sequencing method are also included. Furthermore, audiometric data are attached, from which the average air-conduction thresholds for ears with EVA malformation were determined.</p> <p> </p> <p><strong>Abstract manuscripts: </strong></p> <p>The most frequently observed congenital inner ear malformation is enlarged vestibular aqueduct (EVA). It is often accompanied with incomplete partition type 2 (IP2) of the cochlea and a dilated vestibule, which together constitute Mondini malformation. Pathogenic SLC26A4 variants are considered the major cause of inner ear malformation but the genetics still needs clarification. The aim of this study was to identify the cause of EVA in patients with hearing loss (HL). Genomic DNA was isolated from HL patients with radiologically confirmed bilateral EVA (n = 23) and analyzed by next generation sequencing using a custom HL gene panel encompassing 237 HL-related genes or a clinical exome. The presence and segregation of selected variants and the CEVA haplotype (in the 5′ region of SLC26A4) was verified by Sanger sequencing. Minigene assay was used to evaluate the impact of novel synonymous variant on splicing. Genetic testing identified the cause of EVA in 17/23 individuals (74%). Two pathogenic variants in the SLC26A4 gene were identified as the cause of EVA in 8 of them (35%), and a CEVA haplotype was regarded as the cause of EVA in 6 of 7 patients (86%) who carried only one SLC26A4 genetic variant. In two individuals with a phenotype matching branchio-oto-renal (BOR) spectrum disorder, cochlear hypoplasia resulted from EYA1 pathogenic variants. In one patient, a novel variant in CHD7 was detected. Our study shows that SLC26A4, together with the CEVA haplotype, accounts for more than half of EVA cases. Syndromic forms of HL should also be considered in patients with EVA. We conclude that to better understand inner ear development and the pathogenesis of its malformations, there is a need to look for pathogenic variants in noncoding regions of known HL genes or to link them with novel candidate HL genes.</p>
Raw data for Figures 2-4 for journal article: "Experimental Evaluation of the Adhear, a Novel Transcutaneous Bone Conduction Hearing Aid""
<p>This is a data set containing the raw data for figures 2-4 from the journal article:</p> <p>"Experimental Evaluation of the Adhear, a Novel Transcutaneous Bone Conduction Hearing Aid"</p> <p>Original article DOI: 10.1055/a-1308-3888</p> <p>Original article link: https://pubmed.ncbi.nlm.nih.gov/33260222/</p> <p> </p> <p>The data is contained within MATLAB figure (.fig) files, all saved with MATLAB version R2020a.</p> <p> </p>
Figure 1 in Relationships of cochlear coiling shape and hearing frequencies in cetaceans, and the occurrence of infrasonic hearing in Miocene Mysticeti
Figure 1. Cochlear anatomy and visualization of methods. (a) Three-dimensional rendering of the cochlea (shown as right) of Balaenoptera acutorostrata in apical view. (b) Same, virtually transected along the modiolus (mod) showing the primary and secondary bony laminae (bl1 and bl2, respectively). (c) Radii ratio method as applied in this study: circles superimposed onto basal and apical turns of a 2-D projection of the path tracing the basilar membrane within the cochlea. Dots represent three points on each circle for calculation of the respective radius. (d) Landmark-based geometric morphometrics: 3-D resampled path with landmarks 1 to 40.
Figure 3 in Relationships of cochlear coiling shape and hearing frequencies in cetaceans, and the occurrence of infrasonic hearing in Miocene Mysticeti
Figure 3. (a–g) Linear regressions for significant correlations of PC1 and PC2 with individual variables tested in this study.
Figure 2 in Relationships of cochlear coiling shape and hearing frequencies in cetaceans, and the occurrence of infrasonic hearing in Miocene Mysticeti
Figure 2. PCA plot of shape variation of cochlear coiling. Lines represent 95 % confidence ellipses for Mysticeti (red) and Odontoceti (blue). Shape change along the axes is shown as black landmark configurations against the average shape (in gray) in apical view and in profile. Known lowest hearing limits in Hz are given for extant cetaceans (see Table 2). Number in parentheses refers to a fetus. * denotes extinct mysticetes with presumed very low frequency hearing (50 Hz and below). ** denotes extinct mysticetes with presumed infrasonic hearing (below 20 Hz). Gray numbers represent identification numbers (ID) listed in Table 2. The specimens plotting outside of the ellipse are Megapteropsis robusta (ID12) and Eschrichtiidae indet. (ID6).
Hearing Aid Noisy Speech Dataset
<p>Speech dataset, based on the Google Speech Commands Dataset, containing (simulated) noisy own voice as if it were captured by a hearing aid with 2 (front and rear) behind-the-ear microphones and 1 in-ear-canal microphone.</p>
Treatise on Hearing: The Temporal Auditory Imaging Theory Inspired by Optics and Communication (Supplementary Audio Demo Files)
<p>Audio files that supplement "Treatise on Hearing: The Temporal Auditory Imaging Theory Inspired by Optics and Communication". Please refer to the manuscript (preprint) for additional details.</p>
Meta-GWAS for age-related hearing impairement
<p>The dataset comprises summary statistics from the meta-GWAS of 17 studies on age-related hearing impairement. The dataset accompanies the following paper:</p> <p><strong>Genome-wide association meta-analysis identifies 48 risk variants and highlights the role of the stria vascularis in age-related hearing impairment</strong></p> <p>Please cite the paper if using this dataset.</p> <p>Phenotype of ARHI was established using ICD diagnoses and self-reported hearing loss. The study comprised 148,152 cases and 575,472 controls or European ancestry. Adult male and female participants were included from the following 17 population-based cohort studies: Age, Genes/Environment Susceptibility - Reykjavik (AGES), the Danish Twin Registry (DTR), the Estonian Genome Center at the University of Tartu (EGCUT), FinnGen, Framingham Heart Study (FHS), Health Aging and Body Composition (HABC), Italian Network of Genetic Isolates - Friuli Venezia Giulia (INGI-FVG), the Rotterdam Study (RS, cohorts 1 - 3), the Salus in Apulia study (SA; formerly known as Great Age study), Screening Across the Lifespan Twin (SALT and SALTY - young), Screening Twin Adults: Genes and Environment (STAGE), TwinsUK, UK Biobank (UKBB), and the Women’s Genome Health Study (WGHS). </p> <p>UK Biobank data have been used under project #11516.</p> <p>Individual GWASs have been QC'd and harmonyzed using EasyQC followed by fixed-effects IVW meta-analysis using METAL. The dataset includes the results of meta-analysis for n = 8,244,938 SNV with MAF >0.001 and present in at least 9 cohorts.<br> <br> <strong>Dataset columns:</strong></p> <p>SNP, rsID</p> <p>CHR, chromosome</p> <p>BP, genomic position (hg19)</p> <p>Allele1, effect allele</p> <p>Allele2, other allele</p> <p>Freq1, mean frequency of Allele1</p> <p>FreqSE, standard error of Freq1</p> <p>MinFreq, minimal frequency of Allele1 in the study cohorts</p> <p>MaxFreq, maximal frequency of Allele1 in the study cohorts</p> <p>Effect, effect size from the meta-analysis for Allele1</p> <p>StdErr, standard error of Effect</p> <p>P.value, corresponding p-value for meta-analysis</p> <p>Direction, direction of effects in individual studies</p> <p>HetISq, I<sup>2</sup> statistic for heterogeneity between studies</p> <p>HetChiSq, chi<sup>2</sup> statistic for heterogeneity between studies</p> <p>HetDf, degrees of freedom for the chi<sup>2</sup> statistic</p> <p>HetPval, p-value for heterogeneity between studies</p> <p>N, summary sample size</p> <p><strong>Dataset columns description:</strong></p> <p> </p> <p> </p> <p> </p> <p> </p> <p>Seventeen studies included:</p> <p> </p> <p> </p>
ABR raw data and results from automated hearing threshold detection
<p><strong>This repository contains: </strong></p> <ol> <li><strong>data.tar.gz</strong>: raw data from Auditory Brainstem Response (ABR) measurements performed at over 4,000 mice at the German Mouse Clinic. It also contains suitably pre-processed ABR raw data of over 8,000 mice from another public data repository (10.5061/DRYAD.CV803RV) of the Wellcome Sanger Institute. All data is intended to be used by and compatible with code published on GitHub (https://github.com/ExperimentalGenetics/ABR_thresholder). <br> </li> <li><strong>results.tar.gz</strong>: results and visualisations - comparison of two new, independent automatic hearing threshold finding methods and comparison with the manual gold standard method.</li> </ol>
Fig. 10 in Can You Hear Me Now? A Comparative Survey Of Pinniped Auditory Apparatus Morphology
Fig. 10. CT Scans and Reconstructions of the Inner Ear: A — Canis familiaris; B — Eumetopias jubatus with directional labels as follows: Ant — anterior; Dor — dorsal; Med — medial; Pos — posterior. Anatomical labels are: aa — anterior ampulla; ac — anterior semicircular canal; co — cochlea; fc — fenestrae cochleae; fv — fenestrae vestibuli; la — lateral ampulla; lc — lateral semicircular canal; pa — posterior ampulla; pc — posterior semicircular canal (modified from Ekdale, 2013).
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