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Dataset results
195 results for “hearing aids”
Longitudinal Outcomes of Hearing Aids
ClinicalTrials.gov study NCT04030299. IPD Sharing: YES. Countries: 1. Publications: 6.
Impact of Hearing Aid Service-delivery Model and Technology on Patient Outcomes
ClinicalTrials.gov study NCT03579563. IPD Sharing: YES. Countries: 1. Publications: 9.
Wide-Bandwidth Open Canal Hearing Aid For Better Multitalker Speech Understanding
ClinicalTrials.gov study NCT00582946. IPD Sharing: NO. Countries: 1. Publications: 1.
Validation of Novel BTE and SP Hearing Aid Models
ClinicalTrials.gov study NCT04882787. IPD Sharing: NO. Countries: 1. Publications: 2.
Variability In Hearing Aid Outcomes In Older Adults
ClinicalTrials.gov study NCT02448706. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Hearing Aid and Individuals With Cognitive Disorders
ClinicalTrials.gov study NCT04049643. IPD Sharing: YES. Countries: 1. Publications: 8.
Supplementing Hearing Aids With Computerized Auditory Training
ClinicalTrials.gov study NCT00727337. IPD Sharing: Not stated. Countries: 1. Publications: 2.
Investigating Hearing Aid Frequency Response Curves 2
ClinicalTrials.gov study NCT05828017. IPD Sharing: NO. Countries: 1. Publications: 7.
Lab Evaluation of Novel Hearing Aid Coupling Method
ClinicalTrials.gov study NCT05377359. IPD Sharing: NO. Countries: 1. Publications: 7.
The Use of Medical Grade Honey in the Prevention of Bone Anchored Hearing Aid Associated Skin Breakdown
ClinicalTrials.gov study NCT03929224. IPD Sharing: Not stated. Countries: 1. Publications: 6.
Clinical Validation of the Lexie Lumen Hearing Aid
ClinicalTrials.gov study NCT05337748. IPD Sharing: NO. Countries: 1. Publications: 3.
Data from: Hearing-aid adoption in Northern and Southern Germany
Open the record for dataset details and reuse information.
Acoustic feedback tendency in hearing aids for different types and couplings in relation to insertion gain
<p>To make signals audible again for hearing impaired people, hearing aids pick up the sounds with a microphone amplify them and play them back in the ear canal. Parts of the amplified output signal return to the microphone by an acoustic pathway. Depending on the selected amplification, this can result in 'critical feedback', which limits the maximum possible amplification of hearing aids. <br>The Insertion-Gain-Related Feedback Path (IFP) was introduced to characterize the acoustic feedback path. It describes the frequency-dependent gain that a hearing aid can provide until a critical feedback condition becomes possible. In addition to the feedback signal, the IFP also takes the Real Ear Unaided Gain (REUG), the Microphone Location Effect (MLE) and the hearing aid transmission to the eardrum into account. Technical measurements were used in this work, including the use of hearing aid dummies and probe microphones. This was used to determine the IFPs in 28 test subjects' ears. This data is freely available.</p>
Raw Data from - Speech Auditory Brainstem Responses in Adult Hearing Aid Users: Effects of Aiding and Background Noise, and Prediction of Behavioral Measures
<p><em><strong>Folder and Data Description for dataset of:</strong></em></p> <p><strong>Speech Auditory Brainstem Responses in Adult Hearing Aid Users: Effects of Aiding and Background Noise, and Prediction of Behavioral Measures</strong></p> <p>Ghada BinKhamis, Antonio Elia Forte, Tobias Reichenbach, Martin O’Driscoll, and Karolina Kluk</p> <p><strong>Please site the paper when using this dataset</strong> (DOI: 10.1177/2331216519848297)</p> <p> </p> <p><strong>Shared dataset is as follows:</strong></p> <ul> <li><strong>Behavioral data is in the excel spread sheet entitled:</strong> “BinKhamis_et_al_behavioral_data .xlsx”<br> </li> <li><strong>Speech-ABRs (raw EEG (speech-ABR) data) are contained within the five 'zip' folders.</strong></li> </ul> <p><strong>Description of the “Speech-ABRs” folders, subfolders, and raw EEG files:</strong></p> <p><strong>“Speech-ABRs” Folder Information:</strong></p> <ul> <li><strong>Each Speech_ABR folder</strong> contains subfolders from a subset of participants (e.g. Speech_ABR_1_20.zip contains data from participant number 1 to participant number 20)</li> <li><strong>Subfolders:</strong> <ul> <li>Each subfolder starts with the participant code: e.g. HA1, HA2, HA3, HA4, HA5, …, HA98</li> <li>Next is the background condition: noise or quiet</li> <li>Next is whether recordings were: aided or unaided</li> </ul> </li> <li><strong>Example subfolder names:</strong> <ul> <li><strong><em>HA1 noise aided:</em></strong> participant number 1, aided speech-ABRs in background noise</li> <li><strong><em>HA4 noise unaided:</em></strong> participant number 4, unaided speech-ABRs in background noise</li> <li><strong><em>HA55 quiet aided:</em></strong> participant number 55, aided speech-ABRs in quiet</li> <li><strong><em>HA97 quiet unaided</em></strong>: participant number 97, unaided speech-ABRs in quiet</li> </ul> </li> <li>Each participant has 4 subfolders for the four recording conditions (aided quiet, aided noise, unaided quiet, unaided noise) <ul> <li><strong>Each subfolder contains four ‘.mat’ files, ‘.mat’ file names:</strong> <ul> <li>Each ‘.mat’ file starts with the participant code: e.g. HA1, HA2, HA3, HA4, HA5, …, HA98</li> <li>Next is the stimulus: 40 da</li> <li>Next is ‘unaided’ only if recordings were without HA</li> <li>Next is ‘noise’ only if the background condition was noise</li> <li>Next is the stimulus polarity: <ul> <li>‘Pos’ for positive/standard</li> <li>‘Neg’ for negative (reversed polarity stimulus)</li> </ul> </li> <li>And finally the test ear and recording number for that polarity <ul> <li>R1 is the first recording from the right ear, R2 is the second recording from the right ear</li> <li>L1 is the first recording from the left ear, L2 is the second recording from the left ear</li> </ul> </li> <li><strong>Example ‘.mat’ file name:</strong> <ul> <li><strong><em>HA1 40 da Neg Noise R1.mat: </em></strong>participant number 1, aided speech-ABR in response to the 40 ms [da], reversed stimulus polarity, in background noise, right ear recording number 1.</li> <li><strong><em>HA4 40 da unaided Pos Noise L2.mat:</em></strong> participant number 1, unaided speech-ABR in response to the 40 ms [da], standard stimulus polarity, left ear recording number 2.</li> <li><strong><em>HA7 40 da Neg R2.mat:</em></strong> participant number 7, aided speech-ABR in response to the 40 ms [da], reversed stimulus polarity, right ear recording number 2.</li> <li><strong><em>HA10 40 da unaided Pos Noise L1.mat:</em></strong> participant number 10, unaided speech-ABR in response to the 40 ms [da], standard stimulus polarity, in background noise, left ear recording number 1.</li> </ul> </li> </ul> </li> </ul> </li> </ul> <p><strong>File Information:</strong></p> <p><strong>Description of ‘.mat’ files that can be accessed and processed using MATLAB (MathWorks):</strong></p> <p>Each ‘.mat’ file is a structure that contains the following fields:</p> <ul> <li>The first nine fields are informational, for example:</li> <li><strong><em>xunits</em></strong>: ‘s’ indicates that the recording time window is in seconds, conversion to milliseconds would be required to plot the data in milliseconds</li> <li><strong><em>start: </em></strong>‘0’ indicates that both stimulus and recording start at 0 seconds</li> <li><strong><em>points:</em></strong> <strong>2200</strong> is the number of sample points</li> <li><strong><em>chans:</em></strong> 2 is the number of channels <ul> <li><em>Right ear:</em> channel 2, <em>Left ear:</em> channel 1</li> </ul> </li> <li><strong><em>frames:</em></strong> 2500 is the number of epochs</li> <li>The last filed <strong>‘values’</strong> is what contains the raw EEG data (2200x2x2500) <ul> <li><strong>2200 </strong>is the number of samples</li> <li><strong>2 </strong>is the number of channels (channel one is recorded from the left ear lobe (A1) and channel two is from the right ear lobe (A2))</li> <li><strong>2500 </strong>is the number of epochs <ul> <li>Stimulus starts at 0 seconds per epoch, pre-stimulus baseline may be extracted from the end of each epoch (i.e. before the next stimulus).</li> <li>Data are in Volts; conversion to <strong>μVolts </strong>(multiply by 1000) is required.</li> </ul> </li> </ul> </li> </ul> <p><strong>Date of data collection: </strong>October 2017 to July 2018</p>
Assessing Pharmacy Technician Educational Training for the Provision of Over-the-Counter Hearing Aids in Rural Alabama and Mississippi Pharmacies
ClinicalTrials.gov study NCT06864273. IPD Sharing: YES. Countries: 1. Publications: 1.
Evaluation of Efficacy and Patient Acceptance of Sound Amplifier Téo First, in Mild and Moderate Presbycusis Patient 60 Years of Age and Older, With no Previous Hearing Aid
ClinicalTrials.gov study NCT01815788. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Real-World Benefit From Directional Hearing Aids
ClinicalTrials.gov study NCT00438334. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Telephone vs. Voice Over IP Speech Comprehension in Hearing Aided Subjects.
ClinicalTrials.gov study NCT03005912. IPD Sharing: NO. Countries: 1. Publications: 19.
Clinical Trial on Alzheimer Disease, Presbycusis and Hearing Aids
ClinicalTrials.gov study NCT00488007. IPD Sharing: Not stated. Countries: 1. Publications: 2.
Listening Benefits From a Hearing-aid App, a Personal Sound Amplification Product, and a Hearing Aid in Hearing-impaired Listeners
ClinicalTrials.gov study NCT05644106. IPD Sharing: Not stated. Countries: 1. Publications: 1.
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.