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ShareScore release 0.9.0
Dataset results
19 results for “Movement Detection”
Datasets with and without deliberate head movements for detection and imputation of dropout in diffusion MRI
Open the record for dataset details and reuse information.
A Wi-Fi Channel State Information (CSI) and Received Signal Strength (RSS) data-set for human presence and movement detection
<p>This data-set consists of antenna-wise received signal strength (RSS) and channel state information (CSI) data. Both types of data have been captured using the <a href="https://dhalperi.github.io/linux-80211n-csitool/">Intel CSI Tools</a>. The RSS data have been used in our paper "Detecting Human Movement from Ambient Wi-Fi Signal Strength".</p> <p>This release extends the README with a data dictionary for the annotations. We hope to add more information about the data acquisition process (e.g., data acquisition protocols).</p>
gazeNet: End-to-end eye-movement event detection with deep neural networks
<p>This repository contains synthetic eye-movement dataset used to train deep learning based eye-movement event detection algorithm described in Zemblys, R., Niehorster, D.C. & Holmqvist, K. (2018). gazeNet: End-to-end eye-movement event detection with deep neural networks. Behavior research methods, pp 1–25. <a href="https://doi.org/10.3758/s13428-018-1133-5">https://doi.org/10.3758/s13428-018-1133-5</a></p> <p>Code used to train a model can be found on github <a href="https://github.com/r-zemblys/gazeNet">here</a>. Code to generate synthetic eye-movement data can be downloaded from <a href="https://github.com/r-zemblys/gazeGenNet">here</a>.</p>
Machine learning methods detect arm movement impairments in a patient with parieto-occipital lesion using only early kinematic information.
<p>This depository contains the data and codes of the paper: </p> <p>Bosco, A., Bertini C., Filippini M., Foglino C., Fattori P (2022). Machine learning methods detect arm movement impairments in a patient with parieto-occipital lesion using only early kinematic information. <em>Journal of Vision</em>, in press. </p> <p>Data are provided in mat-file, codes is provided in m-files (Matlab).</p>
Spatial variation in population-density, movement and detectability of snow leopards in a multiple use landscape in Spiti Valley, Trans-Himalaya
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Autism Detection Based on Eye Movement Sequences on the Web: A Scanpath Trend Analysis Approach
<p>We propose a novel approach to detect autism based on the eye-movement paths of users on the Web. This approach based on Scanpath Trend Analysis (STA) proposed by Eraslan et al. (2016, 2017). This dataset is created to provide supplementary data for our paper entitled "Autism Detection Based on Eye Movement Sequences on the Web: A Scanpath Trend Analysis Approach" presented at <a href="http://www.w4a.info/2020/">the 17th International Web for All Conference (W4A'20)</a>. This dataset includes all the individual paths used for the evaluation of our proposed approach. The dataset also includes the Python code to re-run the evaluation.</p> <p><strong>References:</strong></p> <ul> <li>Sukru Eraslan, Yeliz Yesilada, and Simon Harper. 2016. Scanpath Trend Analysis on Web Pages: Clustering Eye Tracking Scanpaths. ACM Transactions on the Web, (SCI-E), 10, 4, Article 20.</li> <li>Sukru Eraslan, Yeliz Yesilada, and Simon Harper. 2017. Engineering web-based interactive systems: trend analysis in eye tracking scanpaths with a tolerance. In Proceedings of the ACM SIGCHI Symposium on Engineering Interactive Computing Systems (EICS '17). ACM, New York, NY, USA, 3-8.</li> </ul>
A novel method for detecting extra-home range movements (EHRMs) by animals and recommendations for future EHRM studies
<p>Infrequent, long-distance animal movements outside of typical home range areas provide useful insights into resource acquisition, gene flow, and disease transmission within the fields of conservation and wildlife management, yet understanding of these movements is still limited across taxa. To detect these extra-home range movements (EHRMs) in spatial relocation datasets, most previous studies compare relocation points against fixed spatial and temporal bounds, typified by seasonal home ranges (referred to here as the "Fixed-Period" method). However, utilizing home ranges modelled over fixed time periods to detect EHRMs within those periods likely results in many EHRMs going undocumented, particularly when an animal's space use changes within that period of time. To address this, we propose a novel, "Moving-Window" method of detecting EHRMs through an iterative process, comparing each day's relocation data to the preceding period of space use only. We compared the number and characteristics of EHRM detections by both the Moving-Window and Fixed-Period methods using GPS relocations from 33 white-tailed deer (Odocoileus virginianus) in Alabama, USA. The Moving-Window method detected 1.5 times as many EHRMs as the Fixed-Period method and identified 120 unique movements that were undetected by the Fixed-Period method, including some movements that extended nearly 5 km outside of home range boundaries. Additionally, we utilized our EHRM dataset to highlight and evaluate potential sources of variation in EHRM summary statistics stemming from differences in definition criteria among previous EHRM literature. We found that this spectrum of criteria identified between 15.6% and 100.0% of the EHRMs within our dataset. We conclude that variability in terminology and definition criteria previously used for EHRM detection hinders useful comparisons between studies. The Moving-Window approach to EHRM detection introduced here, along with proposed methodology guidelines for future EHRM studies, should allow researchers to better investigate and understand these behaviors across a variety of taxa.</p>
Ultrasound to Detect Vocal Fold Movement in Neurological Disease
ClinicalTrials.gov study NCT05493397. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Use of Eye Movement Tracking to Detect Oculomotor Abnormality in Traumatic Brain Injury Patients
ClinicalTrials.gov study NCT02776462. IPD Sharing: NO. Countries: 1. Publications: 3.
A novel method for detecting extra-home range movements (EHRMs) by animals and recommendations for future EHRM studies
Open the record for dataset details and reuse information.
Detection of siRNA movement in Arabidopsis thaliana using P19 under root cell layer specific expression
GEO Series GSE113029. Arabidopsis thaliana. 8 samples. Type: Expression profiling by high throughput sequencing.
Testing a Wearable Monitor for Fetal Heart Rate Estimation, Fetal Movement and Uterine Activity Detection
ClinicalTrials.gov study NCT04450251. IPD Sharing: NO. Countries: 1. Publications: 0.
Development of a Seizure Detection Algorithm Based on Heart Rate and Movement Analysis
ClinicalTrials.gov study NCT05637762. IPD Sharing: NO. Countries: 1. Publications: 0.
Computed Tomography in Detecting Movement of the Esophagus in Patients Undergoing Radiation Therapy to the Chest
ClinicalTrials.gov study NCT00433524. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Eye Movement Tracking to Detect Impairment Due to Acute Cannabis Intoxication
ClinicalTrials.gov study NCT04799093. IPD Sharing: NO. Countries: 1. Publications: 0.
Detecting Absence Seizures Using Hyperventilation and Eye Movement Recordings
ClinicalTrials.gov study NCT06093490. IPD Sharing: NO. Countries: 1. Publications: 0.
The RestEaze Ambulatory Sleep Monitor for Detection of Leg Movements During Sleep in Adults and Children With a Sleep Disturbance
ClinicalTrials.gov study NCT04508595. IPD Sharing: NO. Countries: 1. Publications: 0.
Detecting Malingering Detection Using Eye Movements and Response Time (MDER)
ClinicalTrials.gov study NCT03201887. IPD Sharing: NO. Countries: 0. Publications: 0.
Detecting Acetabulum Movement After Total Hip Arthroplasty From Serial Plain Radiographs
ClinicalTrials.gov study NCT04779112. IPD Sharing: Not stated. Countries: 0. 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.