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155 results for “accelerometers”
Insights into short and long-term crop-foraging strategies in a chacma baboon (Papio ursinus) from GPS and accelerometer data
<p>Crop-foraging by animals is a leading cause of human-wildlife 'conflict' globally, affecting farmers and resulting in the death of many animals in retaliation, including primates. Despite significant research into crop-foraging by primates, relatively little is understood about the behaviour and movements of primates in and around crop fields, largely due to the limitations of traditional observational methods. Crop-foraging by primates in large scale agriculture has also received little attention. We used GPS and accelerometer bio-loggers, along with environmental data, to gain an understanding of the spatial and temporal patterns of activity for a female in a crop-foraging baboon group in and around commercial farms in South Africa over one year. Crop fields were avoided for most of the year, suggesting that fields are perceived as a high-risk habitat. When field visits did occur, this was generally when plant primary productivity was low, suggesting that crops were a 'fallback food'. All recorded field visits were at or before 15:00. Activity was significantly higher in crop fields than in the landscape in general, evidence that crop-foraging is an energetically costly strategy and that fields are perceived as a risky habitat. In contrast, activity was significantly lower within 100m of the field edge than in the rest of the landscape, suggesting that baboons wait near the field edge to assess risks before crop-foraging. Together this understanding of the spatiotemporal dynamics of crop-foraging can help to inform crop protection strategies and reduce conflict between humans and baboons in South Africa.</p>
accelerations from the accelerometer, orbit determination and CoM offset
<p>accelerations from the accelerometer, orbit determination and CoM offset</p>
Data from: Quantum Membrane Accelerometer Microchip
<p>Source data for figures.</p>
Pacific black ducks tri-axial accelerometer data with behaviour labels
<p>The tri-axial accelerometer datasets from Pacific black ducks (<em>Anas superciliosa</em>) was measured at 25 Hz. Fifty tri-axial measurements, totalling 2 seconds, were used to form a behaviour segment. Each dataset includes 9343 segments each forming a row in the dataset. Each row contains 151 columns. The first 150 columns are ACC measurements from three orthogonal axes, arranged as x, y, z, x, y, z, ...,x, y, z. The final column is of type character containing the corresponding behaviour. The two datasets contains 16 and 8 behaviour type labels, respectively. </p>
Data of "Stabilizing classical accelerometers and gyroscopes with a quantum inertial sensor"
Open the record for dataset details and reuse information.
24-hour movement behaviors regarding different accelerometer metrics and cardiometabolic variables of Belgian adults
<p>Datase of 213 adults with 24-hour movement behaviors features and cardiometabolic health variables</p> <p>Sociodemographic information</p> <ul> <li>age</li> <li>sex </li> <li>educational level</li> <li>smoking status</li> <li>pathology (having T2DM or not)</li> </ul> <p>Cardiometabolic variables </p> <ul> <li>BMI</li> <li>Waist circumference</li> <li>waist to hip ratio</li> <li>Fat percentage</li> <li>glucose</li> <li>HbA1c</li> <li>HDL-cholesterol</li> <li>LDL-cholesterol</li> <li>Total cholesterol</li> <li>Triglycerides</li> <li>Systolic Blood pressure</li> <li>Diastolic blood pressure</li> </ul> <p>24-hour movement behaviors (Actigraph GT3X+):</p> <ul> <li>Cut-point dependent time usse estimates for sleep, sedentary behavior, light phyiscal activity, moderate to vigorous physical activity</li> <li>Cut-point independent average acceleration</li> <li>Cut-point independent intensity gradient</li> <li>These cut-off points are available for ENMO, MAD, CMP VA (neish) and CMP VM metric (sasaki) as mentioned in the paper</li> </ul> <p>For more information please contact willems.iris@ugent.be</p>
GENEActiv accelerometer files collected during the project entitled "Cultures et comportements alimentaires de la jeunesse dans les pays francophones du Pacifique au XXIème siècle: exemple de la Nouvelle-Calédonie" [Eng: "Eating cultures and behaviors of young people in French-speaking Pacific countries in the 21st century: the example of New Caledonia"] (non-anonymized version - second part)
<p><a title="GENEActiv" href="https://activinsights.com/technology/geneactiv/" target="_blank" rel="noopener">GENEActiv</a> accelerometer .bin files recorded during the project entitled "<strong>Cultures et comportements alimentaires de la jeunesse dans les pays francophones du Pacifique au XXIème siècle: exemple de la Nouvelle-Calédonie</strong>" [en: "<strong>Eating cultures and behaviors of young people in French-speaking Pacific countries in the 21st century: the example of New Caledonia</strong>"]. Devices are 60-Hz triaxial accelerometers.</p> <p>Participant characteristics: 10 to 16 years old students and some parents.</p> <p>Number of participants: 231 (206 adolescents + 25 adults).</p> <p>Year of the study: 2018 - 2019.</p> <p>Place of the study: New Caledonia.</p> <p>The accelerometer raw .bin files are available in <strong>restricted datasets</strong>:</p> <ul> <li><a title="Restricted dataset - first part" href="https://doi.org/10.5281/zenodo.11594645" target="_blank" rel="noopener">non-anonymized version - first part</a></li> <li><a title="non-anonymized version - second part" href="https://doi.org/10.5281/zenodo.12638965" target="_blank" rel="noopener">non-anonymized version - second part</a></li> <li><a title="Restricted dataset - third part" href="https://doi.org/10.5281/zenodo.12661429" target="_blank" rel="noopener">non-anonymized version - third part</a></li> </ul> <p>The accelerometer .csv files with a 1 second epoch and extracted from raw .bin files are available in open datasets:</p> <ul> <li><a title="Open dataset - first part" href="https://doi.org/10.5281/zenodo.12615468" target="_blank" rel="noopener">anonymized version - first part</a></li> <li><a title="Open dataset - second part" href="https://doi.org/10.5281/zenodo.12638746" target="_blank" rel="noopener">anonymized version - second part</a></li> <li><a title="Open dataset - third part" href="10.5281/zenodo.12682660" target="_blank" rel="noopener">anonymized version - third part</a></li> </ul> <p>Other participant characteristics (age, place of living, cultural community and socio-economic status) are available in a <a title="Information associated with GENEActiv accelerometer files collected during the project entitled "Cultures et comportements alimentaires de la jeunesse dans les pays francophones du Pacifique au XXIème siècle: exemple de la Nouvelle-Calédonie" [en: "Eating cultures and behaviors of young people in French-speaking Pacific countries in the 21st century: the example of New Caledonia"] (non-anonymized information version)" href="https://doi.org/10.5281/zenodo.12195186" target="_blank" rel="noopener">restricted non-anonymized dataset</a>.</p> <p>When using this dataset, please cite the following reference:<br><a title="Wattelez et al. 2025" href="https://doi.org/10.1016/j.dib.2024.111228" target="_blank" rel="noopener">G. Wattelez, S. Frayon, O. Galy, Assessing physical activity/behavior of adolescents living in the Pacific with accelerometer data: 231 GENEActiv records in New Caledonia, Data in Brief 58 (2025) 111228, doi: 10.1016/j.dib.2024.111228</a></p>
GENEActiv accelerometer files collected during the project entitled "Cultures et comportements alimentaires de la jeunesse dans les pays francophones du Pacifique au XXIème siècle: exemple de la Nouvelle-Calédonie" [Eng: "Eating cultures and behaviors of young people in French-speaking Pacific countries in the 21st century: the example of New Caledonia"] (non-anonymized version - third part)
<p><a title="GENEActiv" href="https://activinsights.com/technology/geneactiv/" target="_blank" rel="noopener">GENEActiv</a> accelerometer .bin files recorded during the project entitled "<strong>Cultures et comportements alimentaires de la jeunesse dans les pays francophones du Pacifique au XXIème siècle: exemple de la Nouvelle-Calédonie</strong>" [en: "<strong>Eating cultures and behaviors of young people in French-speaking Pacific countries in the 21st century: the example of New Caledonia</strong>"]. Devices are 60-Hz triaxial accelerometers.</p> <p>Participant characteristics: 10 to 16 years old students and some parents.</p> <p>Number of participants: 231 (206 adolescents + 25 adults).</p> <p>Year of the study: 2018 - 2019.</p> <p>Place of the study: New Caledonia.</p> <p>The accelerometer raw .bin files are available in <strong>restricted datasets</strong>:</p> <ul> <li><a title="Restricted dataset - first part" href="https://doi.org/10.5281/zenodo.11594645" target="_blank" rel="noopener">non-anonymized version - first part</a></li> <li><a title="non-anonymized version - second part" href="https://doi.org/10.5281/zenodo.12638965" target="_blank" rel="noopener">non-anonymized version - second part</a></li> <li><a title="Restricted dataset - third part" href="https://doi.org/10.5281/zenodo.12661429" target="_blank" rel="noopener">non-anonymized version - third part</a></li> </ul> <p>The accelerometer .csv files with a 1 second epoch and extracted from raw .bin files are available in open datasets:</p> <ul> <li><a title="Open dataset - first part" href="https://doi.org/10.5281/zenodo.12615468" target="_blank" rel="noopener">anonymized version - first part</a></li> <li><a title="Open dataset - second part" href="https://doi.org/10.5281/zenodo.12638746" target="_blank" rel="noopener">anonymized version - second part</a></li> <li><a title="Open dataset - third part" href="https://doi.org/10.5281/zenodo.12682660" target="_blank" rel="noopener">anonymized version - third part</a></li> </ul> <p>Other participant characteristics (age, place of living, cultural community and socio-economic status) are available in a <a title="Information associated with GENEActiv accelerometer files collected during the project entitled "Cultures et comportements alimentaires de la jeunesse dans les pays francophones du Pacifique au XXIème siècle: exemple de la Nouvelle-Calédonie" [en: "Eating cultures and behaviors of young people in French-speaking Pacific countries in the 21st century: the example of New Caledonia"] (non-anonymized information version)" href="https://doi.org/10.5281/zenodo.12195186" target="_blank" rel="noopener">restricted non-anonymized dataset</a>.</p> <p>When using this dataset, please cite the following reference:<br><a title="Wattelez et al. 2025" href="https://doi.org/10.1016/j.dib.2024.111228" target="_blank" rel="noopener">G. Wattelez, S. Frayon, O. Galy, Assessing physical activity/behavior of adolescents living in the Pacific with accelerometer data: 231 GENEActiv records in New Caledonia, Data in Brief 58 (2025) 111228, doi: 10.1016/j.dib.2024.111228</a></p>
GENEActiv accelerometer files collected during the project entitled "Cultures et comportements alimentaires de la jeunesse dans les pays francophones du Pacifique au XXIème siècle: exemple de la Nouvelle-Calédonie" [Eng: "Eating cultures and behaviors of young people in French-speaking Pacific countries in the 21st century: the example of New Caledonia"] (non-anonymized version - first part)
<p><a title="GENEActiv" href="https://activinsights.com/technology/geneactiv/" target="_blank" rel="noopener">GENEActiv</a> accelerometer .bin files recorded during the project entitled "<strong>Cultures et comportements alimentaires de la jeunesse dans les pays francophones du Pacifique au XXIème siècle: exemple de la Nouvelle-Calédonie</strong>" [en: "<strong>Eating cultures and behaviors of young people in French-speaking Pacific countries in the 21st century: the example of New Caledonia</strong>"]. Devices are 60-Hz triaxial accelerometers.</p> <p>Participant characteristics: 10 to 16 years old students and some parents.</p> <p>Number of participants: 231 (206 adolescents + 25 adults).</p> <p>Year of the study: 2018 - 2019.</p> <p>Place of the study: New Caledonia.</p> <p>The accelerometer raw .bin files are available in <strong>restricted datasets</strong>:</p> <ul> <li><a title="Restricted dataset - first part" href="https://doi.org/10.5281/zenodo.11594645" target="_blank" rel="noopener">non-anonymized version - first part</a></li> <li><a title="non-anonymized version - second part" href="https://doi.org/10.5281/zenodo.12638965" target="_blank" rel="noopener">non-anonymized version - second part</a></li> <li><a title="Restricted dataset - third part" href="https://doi.org/10.5281/zenodo.12661429" target="_blank" rel="noopener">non-anonymized version - third part</a></li> </ul> <p>The accelerometer .csv files with a 1 second epoch and extracted from raw .bin files are available in open datasets:</p> <ul> <li><a title="Open dataset - first part" href="https://doi.org/10.5281/zenodo.12615468" target="_blank" rel="noopener">anonymized version - first part</a></li> <li><a title="Open dataset - second part" href="https://doi.org/10.5281/zenodo.12638746">anonymized version - second part</a></li> <li><a title="anonymized version - third part" href="https://doi.org/10.5281/zenodo.12682660">anonymized version - third part</a></li> </ul> <p>Other participant characteristics (age, place of living, cultural community and socio-economic status) are available in a <a title="Information associated with GENEActiv accelerometer files collected during the project entitled "Cultures et comportements alimentaires de la jeunesse dans les pays francophones du Pacifique au XXIème siècle: exemple de la Nouvelle-Calédonie" [en: "Eating cultures and behaviors of young people in French-speaking Pacific countries in the 21st century: the example of New Caledonia"] (non-anonymized information version)" href="https://doi.org/10.5281/zenodo.12195186" target="_blank" rel="noopener">restricted non-anonymized dataset</a>.</p> <p>When using this dataset, please cite the following reference:<br><a title="Wattelez et al. 2025" href="https://doi.org/10.1016/j.dib.2024.111228" target="_blank" rel="noopener">G. Wattelez, S. Frayon, O. Galy, Assessing physical activity/behavior of adolescents living in the Pacific with accelerometer data: 231 GENEActiv records in New Caledonia, Data in Brief 58 (2025) 111228, doi: 10.1016/j.dib.2024.111228</a></p>
Data from: A comparison of techniques for classifying behaviour from accelerometers for two species of seabird
The behavior of many wild animals remains a mystery, as it is difficult to quantify behaviour of species that cannot be easily followed throughout their daily or seasonal movements. Accelerometers can solve some of these mysteries, as they collect activity data at a high temporal resolution (< 1 sec), can be relatively small (< 1 g) so they minimally disrupt behavior, and are increasingly capable of recording data for long periods. Nonetheless, there is a need for increased validation of methods to classify animal behaviour from accelerometers to promote widespread adoption of this technology in ecology. We assessed the accuracy of six different behavioral assignment methods for two species of seabird, thick-billed murres (Uria lomvia) and black-legged kittiwakes (Rissa tridactyla). We identified three behaviors using tri-axial accelerometers: standing, swimming and flying, after classifying diving using a pressure sensor for murres. We evaluated six classification methods relative to independent classifications from concurrent GPS tracking data. We used four variables for classification: depth, wing beat frequency, pitch and dynamic acceleration. Average accuracy for all methods was greater than 98% for murres, and 89% and 93% for kittiwakes during incubation and chick rearing, respectively. Variable selection showed that classification accuracy did not improve with more than two (kittiwakes) or three (murres) variables. We conclude that simple methods of behavioral classification can be as accurate for classifying basic behaviors as more complex approaches, and that identifying suitable accelerometer metrics is more important than using a particular classification method when the objective is to develop a daily activity or energy budget. Highly accurate daily activity budgets can be generated from accelerometer data using a multiple methods and a small number of accelerometer metrics; therefore, identifying a suitable behavioral classification method should not be a barrier to using accelerometers in studies of seabird behavior and ecology.
Get Going: Accelerometer-Based Intervention to Promote Physical Activity in Frail Older Adults
ClinicalTrials.gov study NCT02635477. IPD Sharing: Not stated. Countries: 2. Publications: 20.
The Effects of Accelerometer Triggered Functional Electrical Stimulation on Post-Stroke Hemiplegic Shoulder Subluxation
ClinicalTrials.gov study NCT02346851. IPD Sharing: Not stated. Countries: 1. Publications: 7.
Closing the Gap Between Self-reported and Accelerometer-based Physical Activity
ClinicalTrials.gov study NCT03539237. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Clinical Validation of a Novel, Accelerometer Based, Continuous Respiratory Rate Sensor
ClinicalTrials.gov study NCT06911541. IPD Sharing: UNDECIDED. Countries: 1. Publications: 1.
Validation of Kinocardiography, a New Technology Measuring Cardiac Mechanical Activity Via Accelerometers and Gyroscopes
ClinicalTrials.gov study NCT04772807. IPD Sharing: UNDECIDED. Countries: 1. Publications: 4.
Measuring the Concurrent Validity of the Upper Limb Use Ratio With Accelerometers in an Ecological Situation After Stroke.
ClinicalTrials.gov study NCT06509542. IPD Sharing: NO. Countries: 1. Publications: 17.
Monitoring of Cardiac Function With 3-axis Accelerometers
ClinicalTrials.gov study NCT01926067. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Validity of a Belt Mounted Accelerometer to Assess Walking Measures in Patients With Chronic Stroke
ClinicalTrials.gov study NCT04288960. IPD Sharing: NO. Countries: 1. Publications: 1.
Assess Whether Knowledge by the Younger of the Function of the Accelerometer Determines Its Amount of Physical Activity
ClinicalTrials.gov study NCT02844101. IPD Sharing: NO. Countries: 1. Publications: 2.
Evaluation of Accelerometer-Based Neuromuscular Monitoring Reliability to Exclude Postoperative Residual Paralysis
ClinicalTrials.gov study NCT01503840. IPD Sharing: Not stated. Countries: 1. Publications: 1.
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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.