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130 results for “acoustic monitoring”
Source code and data files for the acoustic sensor-based wearable fetal movement monitor
<p>This repository contains data files and source code for the acoustic sensor-based wearable fetal movement monitor.</p>
Rainbow Acoustic Monitoring (RAM) in Patients Weighing up to 10kg Comparison Study
ClinicalTrials.gov study NCT03482505. IPD Sharing: NO. Countries: 1. Publications: 0.
Data from: Passive acoustic monitoring effectively detects Northern Spotted Owls and Barred Owls over a range of forest conditions
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Daily totals of odontocete acoustic presence at western North Atlantic acoustic monitoring sites
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DCASE 2024 Challenge Task 10 Development Dataset: Acoustic-based Traffic Monitoring
<h3><strong>Directory structure:</strong></h3> <p><strong>engine-sounds.zip</strong><br>|----- car [<em>car engine sounds</em>]<br>|----- cv [<em>commercial vehicles engine sounds</em>]</p> <p><strong>locX.zip</strong><br>|----- meta.json [<em>contains meta information of traffic condition and sensor setup corresponding to the location</em>]<br>|----- train [<em>train flac files inside</em>]<br>|----- train.csv<br>|----- val [<em>val flac files inside</em>]<br>|----- val.csv</p> <p><strong>simulation.zip</strong><br>|----- locX<br> |----- car<br> | |_____ left [<em>flac files and label csv inside</em>]<br> | |_____ right [<em>flac files and label csv inside</em>]<br> |----- cv<br> |_____ left [<em>flac files and label csv inside</em>]<br> |_____ right [<em>flac files and label csv inside</em>]</p> <p><strong>NOTE:</strong> We split zip files for large size folders (i.e., loc1, loc3, loc6). Please make sure to download <em><strong>all splits</strong></em> before unzipping the data! For example, run </p> <p><code>zip -s 0 loc1.zip --out unsplit-loc1.zip</code></p> <p><code>unzip unsplit-loc1.zip</code></p> <p>in your terminal once you have downloaded <code>loc1.z01</code>, <code>loc1.z02</code>, <code>loc1.z03</code> and <code>loc1.zip</code>.</p> <p> </p> <h3><strong>Contact:</strong></h3> <p>If there is any question, please contact:</p> <ul> <li>Luca Bondi: <a href="mailto:luca.bondi@us.bosch.com">luca </a><a href="mailto:luca.bondi@us.bosch.com">(dot)</a><a href="mailto:luca.bondi@us.bosch.com"> bondi@us (dot) bosch (dot) com</a></li> <li>Shabnam Ghaffarzadegan: <a href="mailto:shabnam.ghaffarzadegan@us.bosch.com">shabnam </a><a href="mailto:luca.bondi@us.bosch.com">(dot)</a><a href="mailto:shabnam.ghaffarzadegan@us.bosch.com"> ghaffarzadegan@us </a><a href="mailto:luca.bondi@us.bosch.com">(dot)</a><a href="mailto:shabnam.ghaffarzadegan@us.bosch.com"> bosch </a><a href="mailto:luca.bondi@us.bosch.com">(dot)</a><a href="mailto:shabnam.ghaffarzadegan@us.bosch.com"> com</a></li> <li>Wei-Cheng (Winston) Lin: <a href="mailto:winston.lin@us.bosch.com">wei-cheng </a><a href="mailto:luca.bondi@us.bosch.com">(dot)</a><a href="mailto:winston.lin@us.bosch.com"> lin@us </a><a href="mailto:luca.bondi@us.bosch.com">(dot)</a><a href="mailto:winston.lin@us.bosch.com"> bosch </a><a href="mailto:luca.bondi@us.bosch.com">(dot)</a><a href="mailto:winston.lin@us.bosch.com"> com</a></li> </ul> <p> </p> <h3><strong>Acknowledgement:</strong></h3> <p><em>This work has partially received funding from the European Union's Horizon 2020 research and innovation programme under the Marie </em><em>Skłodowska</em><em>-Curie grant agreement No. 956962 and from the European Research Council under the European Union's Horizon 2020 research and innovation program / ERC Consolidator Grant: SONORA (no. 773268). This work reflects only the authors' views and the Union is not liable for any use that may be made of the contained information.</em></p> <p> </p>
DCASE 2024 Challenge Task 10 Evaluation Dataset: Acoustic-based Traffic Monitoring
<h3><strong>Directory structure:</strong></h3> <p><strong>locX.zip</strong><br>|----- test [<em>test flac files inside</em>]</p> <p> </p> <p><strong>NOTE:</strong> We split zip files for large size folders (i.e., loc1, loc3, loc6). Please make sure to download <em><strong>all splits</strong></em> before unzipping the data! For example, run </p> <p><code>zip -s 0 loc6.zip --out unsplit-loc6.zip</code></p> <p><code>unzip unsplit-loc6.zip</code></p> <p>in your terminal once you have downloaded <code>loc6.z01</code>, <code>loc6.z02</code> and <code>loc6.zip</code>.</p> <p> </p> <h3><strong>Contact:</strong></h3> <p>If there is any question, please contact:</p> <ul> <li>Luca Bondi: <a href="mailto:luca.bondi@us.bosch.com">luca </a><a href="mailto:luca.bondi@us.bosch.com">(dot)</a><a href="mailto:luca.bondi@us.bosch.com"> bondi@us (dot) bosch (dot) com</a></li> <li>Shabnam Ghaffarzadegan: <a href="mailto:shabnam.ghaffarzadegan@us.bosch.com">shabnam </a><a href="mailto:luca.bondi@us.bosch.com">(dot)</a><a href="mailto:shabnam.ghaffarzadegan@us.bosch.com"> ghaffarzadegan@us </a><a href="mailto:luca.bondi@us.bosch.com">(dot)</a><a href="mailto:shabnam.ghaffarzadegan@us.bosch.com"> bosch </a><a href="mailto:luca.bondi@us.bosch.com">(dot)</a><a href="mailto:shabnam.ghaffarzadegan@us.bosch.com"> com</a></li> <li>Wei-Cheng (Winston) Lin: <a href="mailto:winston.lin@us.bosch.com">wei-cheng </a><a href="mailto:luca.bondi@us.bosch.com">(dot)</a><a href="mailto:winston.lin@us.bosch.com"> lin@us </a><a href="mailto:luca.bondi@us.bosch.com">(dot)</a><a href="mailto:winston.lin@us.bosch.com"> bosch </a><a href="mailto:luca.bondi@us.bosch.com">(dot)</a><a href="mailto:winston.lin@us.bosch.com"> com</a></li> </ul> <p> </p> <h3><strong>Acknowledgement:</strong></h3> <p><em>This work has partially received funding from the European Union's Horizon 2020 research and innovation programme under the Marie </em><em>Skłodowska</em><em>-Curie grant agreement No. 956962 and from the European Research Council under the European Union's Horizon 2020 research and innovation program / ERC Consolidator Grant: SONORA (no. 773268). This work reflects only the authors' views and the Union is not liable for any use that may be made of the contained information.</em></p>
Experimental-data-driven deep learning strategy for Structural Health Monitoring of a plate in acoustic fields
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Gunshot sound files and spectrogram images from passive acoustic monitoring data in Vietnam.
<h3><strong>Introduction</strong></h3> <p>This dataset was created to support benchmarking of automated gunshot detection models using 'torch for R'. The data includes recordings collected from Chu Mom Ray National Park in Vietnam combined with an open dataset of gunshots from Belize (Katsis et al. 2022). The dataset is organized into several folders containing .jpg images and their corresponding .wav audio clips. </p> <h3>Data Summary</h3> <p>The dataset is divided into three main categories based on the region and use case:</p> <ol> <li>imagesvietnamunbalanced: Contains spectrogram images and audio data collected from Chu Mom Ray National Park in Vietnam. These data are used for training and evaluating automated gunshot detection models.</li> <li>imagesvietnam_belize: Includes spectrogram images and audio data from both Vietnam and Belize. The data in this folder is used for benchmarking model performance across different geographical regions.</li> <li>testdatacombined: Separate test data to evaluate performance with a large number of noise clips, representing real-world automated detection scenarios.</li> </ol> <p>Each .jpg image in these directories is associated with a .wav file representing a corresponding audio clip. The .wav files were recorded using passive acoustic monitoring and clips were isolated using manual annotations in Raven Pro Software.</p> <p>If used please cite: </p> <p>Vu, T. T., Phan, D. V., Le, T. S., & Clink, D. J. (2024). Investigating hunting in a protected area in Southeast Asia using passive acoustic monitoring with mobile smartphones and deep learning. <em>Ecological Indicators. </em></p> <p>Vu, T. T., Phan, D. V., Le, T. S., & Clink, D. J. (2024). Gunshot sound files and images from passive acoustic monitoring data in Vietnam. [Data set]. Zenodo. <a href="https://doi.org/10.5281/zenodo.13893977" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.13893977</a></p> <p>Katsis, Lydia; Hill, Andrew; Piña-Covarrubias, Evelyn; Prince, Peter; Rogers, Alex; Doncaster, C. Patrick; Snaddon, Jake (2022), “Tropical forest gunshot classification training audio dataset”, <em>Mendeley Data</em>, V3, doi: 10.17632/x48cwz364j.3</p>
Figura 1 in Device for monitoring population density of insects from acoustic signals emitted
Figura 1 – Guido instalado em Muzambinho/MG
Feasibility of Remote Evaluation and Monitoring of Acoustic Pathophysiological Signals With External Sensor Technology in Covid-19
ClinicalTrials.gov study NCT04695821. IPD Sharing: NO. Countries: 1. Publications: 0.
Use of Rainbow Acoustic Monitoring in Pediatric Patients - A Clinical Engineering Data Collection Protocol
ClinicalTrials.gov study NCT03128827. IPD Sharing: NO. Countries: 1. Publications: 0.
An Evaluation of Non-invasive Acoustic Approach to Detect and Monitor Cerebral Vasospasm
ClinicalTrials.gov study NCT02704637. IPD Sharing: NO. Countries: 1. Publications: 0.
Double Push Acoustic Radiation Force (DP ARF) Ultrasound for Monitoring Degeneration in Duchenne Muscular Dystrophy
ClinicalTrials.gov study NCT01506518. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Detection of CardioRespiratory Events Using Acoustic Monitoring in Preterm Infants on CPAP
ClinicalTrials.gov study NCT05196646. IPD Sharing: NO. Countries: 1. Publications: 0.
Mobile Acoustic Startle Reflex-monitoring System (MARS)
ClinicalTrials.gov study NCT04113850. IPD Sharing: YES. Countries: 1. Publications: 0.
Auditory Nerve Monitoring Using Intra-cochlear Stimulation in Subjects With Acoustic Neuroma
ClinicalTrials.gov study NCT02948790. IPD Sharing: NO. Countries: 1. Publications: 0.
Feasibility of Remote Evaluation and Monitoring of Acoustic Pathophysiological Signals With External Sensor Technology
ClinicalTrials.gov study NCT04693091. IPD Sharing: NO. Countries: 1. Publications: 0.
UFPTI 2403-PR12: Real-Time Volumetric Ionizing Radiation Acoustic Imaging for In-vivo Proton Treatment Monitoring in Pencil-Beam Scanning
ClinicalTrials.gov study NCT06465966. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Performance Equivalence of Rainbow Acoustic Monitoring (RAM) Small Sensor and RAM Revision D Sensor
ClinicalTrials.gov study NCT03122405. IPD Sharing: Not stated. Countries: 1. Publications: 0.
An Innovative Non-invasive Acoustic Approach to Detect and Monitor Cerebral Vasospasm
ClinicalTrials.gov study NCT02093182. IPD Sharing: Not stated. Countries: 1. Publications: 0.
ScienceDex guides
Understand access before you commit
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.