Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
61
datasets available to search
ShareScore release 0.9.0
Dataset results
61 results for “ADL”
PAAL ADL Accelerometry dataset v2.0
<p>The PAAL ADL Accelerometry dataset (v2.0) has been acquired with a high-quality wearable multisensor device, the <a href="https://www.empatica.com/research/e4/">Empatica E4</a>. In this dataset, among the signals collected by the sensors embedded in the Empatica E4, only the acceleration has been extracted to monitor the users performing different activities of daily living (ADLs). To promote the real-life acquisition procedure, subjects acted in their natural environment, with no instructions about how and for how long to perform each activity (other than a minimum time). The device was worn on the dominant hand.</p> <p>The dataset includes <strong>24 different ADLs</strong> performed using real objects. Each activity was repeated between 3 and 5 times (on average) by <strong>52 healthy subjects</strong>, characterized by a gender balance <strong>(26 women and 26 men)</strong>, and a large age range (between 18 and 77 years, mean = 44.08 years and standard deviation = 17.06 years).</p> <p>The PAAL ADL Accelerometry dataset (v2.0) is composed of three files:</p> <ul> <li>users.csv: each line contains (participant id, gender, age) of each user performing the ADLs in the dataset. <em>N.B: gender labels are 'man' and 'woman'</em>.</li> <li>ADLs.csv: each line contains (ADL id, ADL name)</li> <li>data.zip: folder with 6,072 files of accelerometer data of users performing ADLs. The name of each file indicates the name of the ADL, the user id and the repetition. Each row in the files represents the continuous gravitational force (g) applied to each of the three spacial dimensions (x, y, and z). The scale is limited to [-2g, +2g]. The sampling frequency is 32 Hz, with a resolution of 0.015 g (8 bit). More information about the format <a href="https://support.empatica.com/hc/en-us/articles/202028739-How-is-the-acceleration-data-formatted-in-E4-connect-">here</a>.</li> </ul>
→ Fig. 9. Antiarchan fish Bothriolepis leptocheira jeremejevi (Rohon, 1900), Sosnogorsk locality, Sosnogorsk Formation, lowermost Famennian, anterior median dorsal (A–G) and posterior median dorsal (H–M) plates of the trunk armour. A. IG KSC 155/5 in dorsal (A1) and visceral (A2) views. B. IG KSC 155/108 in dorsal (B1) and visceral (B2) views. C. IG KSC 155/97 in dorsal view. D. IG KSC 155/113 in dorsal (D1) and visceral (D2) views. E. IG KSC 155/140 in dorsal (E1) and visceral (E2) views. F. Impression of the dorsal surface of IG KSC 155/42. G. IG KSC 155/44 in dorsal view. H. Fragment of IG KSC 155/7 in dorsal view. I. IG KSC 155/1 in dorsal (I1) and visceral (I2) views. J. IG KSC 155/71 in dorsal view. K. Slightly deformed IG KSC 155/70 in dorsal (K1) and visceral (K2) views. L. IG KSC 155/158 in dorsal view. M. IG KSC 155/157 in dorsal (M1) and visceral (M2) views. Abbreviations: ADL, anterior dorso-lateral plate; alr, postlevator thickening; AMD, anterior median dorsal plate; cf.ADL, cf.AMD, and cf.MxL, area overlapping ADL, AMD or MxL respectively; cr.tp, posterior transversal internal crest; dlg1 and dlg2, anterior and posterior oblique dorsal sensory line groove; dma, tergal angle; dmr, dorsal median ridge; f.retr, levator fossa; grm, ventral median groove; l, lateral corner; mvr, median ventral ridge; MxL, mixilateral plate; npn, postnuchal notch; oa.ADL, oa.MxL and oa.PMD, area overlapped by ADL, MxL or PMD respectively; pa, posterior corner; pma, posterior marginal area; PMD, posterior median dorsal plate; pr.p, posterior process of AMD; pr.pl, external postlevator process; prv2, posterior ventral process of dorsal wall of trunk armour; pt1 and pt2, anterior and posterior ventral pit; pua, posterior unornamented area of PMD; rf, "round fossula"; sna, supranuchal area; tb, ventral tuberosity. in A new assessment of the Late Devonian antiarchan fish Bothriolepis leptocheira from South Timan (Russia) and the biotic crisis near the Frasnian-Famennian boundary
→ Fig. 9. Antiarchan fish Bothriolepis leptocheira jeremejevi (Rohon, 1900), Sosnogorsk locality, Sosnogorsk Formation, lowermost Famennian, anterior median dorsal (A–G) and posterior median dorsal (H–M) plates of the trunk armour. A. IG KSC 155/5 in dorsal (A1) and visceral (A2) views. B. IG KSC 155/108 in dorsal (B1) and visceral (B2) views. C. IG KSC 155/97 in dorsal view. D. IG KSC 155/113 in dorsal (D1) and visceral (D2) views. E. IG KSC 155/140 in dorsal (E1) and visceral (E2) views. F. Impression of the dorsal surface of IG KSC 155/42. G. IG KSC 155/44 in dorsal view. H. Fragment of IG KSC 155/7 in dorsal view. I. IG KSC 155/1 in dorsal (I1) and visceral (I2) views. J. IG KSC 155/71 in dorsal view. K. Slightly deformed IG KSC 155/70 in dorsal (K1) and visceral (K2) views. L. IG KSC 155/158 in dorsal view. M. IG KSC 155/157 in dorsal (M1) and visceral (M2) views. Abbreviations: ADL, anterior dorso-lateral plate; alr, postlevator thickening; AMD, anterior median dorsal plate; cf.ADL, cf.AMD, and cf.MxL, area overlapping ADL, AMD or MxL respectively; cr.tp, posterior transversal internal crest; dlg1 and dlg2, anterior and posterior oblique dorsal sensory line groove; dma, tergal angle; dmr, dorsal median ridge; f.retr, levator fossa; grm, ventral median groove; l, lateral corner; mvr, median ventral ridge; MxL, mixilateral plate; npn, postnuchal notch; oa.ADL, oa.MxL and oa.PMD, area overlapped by ADL, MxL or PMD respectively; pa, posterior corner; pma, posterior marginal area; PMD, posterior median dorsal plate; pr.p, posterior process of AMD; pr.pl, external postlevator process; prv2, posterior ventral process of dorsal wall of trunk armour; pt1 and pt2, anterior and posterior ventral pit; pua, posterior unornamented area of PMD; rf, "round fossula"; sna, supranuchal area; tb, ventral tuberosity.
Cryoneurolysis for Improvements in Pain, ADL and QOL in Patients With Ankle Osteoarthritis
ClinicalTrials.gov study NCT03567187. IPD Sharing: NO. Countries: 1. Publications: 13.
Effects of Device-assisted Practice of ADL on Arm/Hand Recovery in Individuals With Moderate to Severe Stroke
ClinicalTrials.gov study NCT04077073. IPD Sharing: NO. Countries: 1. Publications: 2.
ShimFall&ADL: Triaxial accelerometer fall and activities of daily living detection dataset
<p> </p> <p><strong>ShimFall&ADL dataset</strong></p> <p> </p> <p><strong>Version </strong>1.0 (2020-06-19)</p> <p><strong>Please cite as:</strong> "T. Althobaiti, S. Katsigiannis, N. Ramzan, Triaxial accelerometer-based Fall and Activities of Daily Life detection using machine learning, Sensors, 20(13), 3777, 2020. doi: 10.3390/s20133777"</p> <p> </p> <p><strong>Disclaimer</strong><br> While every care has been taken to ensure the accuracy of the data included in the ShimFall&ADL dataset, the authors and the University of the West of Scotland do not provide any guaranties and disclaim all responsibility and all liability (including without limitation, liability in negligence) for all expenses, losses, damages (including indirect or consequential damage) and costs which you might incur as a result of the provided data being inaccurate or incomplete in any way and for any reason. 2020, University of the West of Scotland, Scotland, United Kingdom.</p> <p><br> <strong>Contact</strong><br> For inquiries regarding the ShimFall&ADL dataset, please contact:<br> Dr Stamos Katsigiannis, Stamos.Katsigiannis@uws.ac.uk, University of the West of Scotland<br> Prof. Naeem Ramzan, Naeem.Ramzan@uws.ac.uk, University of the West of Scotland</p> <p> </p> <p><strong>Acknowledgment</strong></p> <p>The authors would like to thank Md. Hasan Shahriar for the data collection under his MSc project.</p> <p> </p> <p><strong>Dataset summary</strong><br> The ShimFall&ADL dataset contains recordings from 35 individuals, acquired using a chest-strapped Shimmer v2 tri-axial accelerometer, recording at a 50Hz sampling rate. Experiments were conducted in a controlled environment at a research lab in the University of the West of Scotland. Thirty five (35) healthy individuals were recruited among young or mid-aged volunteers, aged between 19 and 34 years old, having a body weight between 52 and 113 kg, and a body height between 1.45 and 1.82 m.</p> <p>Participants performed the following activities of daily living (ADL):<br> Jumping<br> Lying down<br> Bending/picking up<br> Sitting to a chair<br> Standing up from a chair<br> Walking</p> <p>Participants performed the following falls:<br> Steep (hard)<br> Front (soft)<br> Front (hard)<br> Left (soft)<br> Left (hard)<br> Right (soft)<br> Right (hard)<br> Back (soft)<br> Back (hard)</p> <p><br> <strong>Data</strong><br> Each ".dat" file in the dataset corresponds to one event for one individual and contains 101 accelerometer samples corresponding to the event. Each row of the file corresponds to one 3-channel sample, dividing the x, y, z axes values using the "\t" character, as follows:<br> Row 1: x1\ty1\tz1<br> Row 2: x2\ty2\tz2<br> ...<br> Row N: xN\tyN\tzN</p> <p>The files within the dataset are named as follows:<br> adl_<ADL activity>_<Participant ID>.dat<br> <Fall Type>fall_<soft,hard>_<Participant ID>.dat</p> <p>For example, the file "adl_standingfromchair_18.dat" corresponds to the accelerometer recording of the 18th participant, performing the "standing up from chair" ADL. The file, "leftfall_soft_11.dat" corresponds to the accelerometer recording of the 11th participant, performing a soft left fall.</p> <p><br> <strong>Additional information</strong><br> For additional information regarding the creation of the ShimFall&ADL dataset, please refer to the associated publication: "T. Althobaiti, S. Katsigiannis, N. Ramzan, Triaxial accelerometer-based Fall and Activities of Daily Life detection using machine learning, Sensors, 20(13), 3777, 2020. doi: 10.3390/s20133777"</p>
Effects of Tai Chi on Cognition, I-ADLs, and HRQOL in Older People With MCI
ClinicalTrials.gov study NCT03404765. IPD Sharing: YES. Countries: 1. Publications: 2.
Glittre ADL-test: Responsiveness to Acute Bronchodilation in Chronic Obstructive Pulmonary Disease (COPD)
ClinicalTrials.gov study NCT03071731. IPD Sharing: YES. Countries: 1. Publications: 12.
Effects of Assistive Device on ADL Function in Patients With Nerve Injury
ClinicalTrials.gov study NCT05302141. IPD Sharing: NO. Countries: 1. Publications: 28.
Arm Motor Control on Bi and Uni ADLs
ClinicalTrials.gov study NCT02778529. IPD Sharing: NO. Countries: 1. Publications: 2.
Randomized Controlled Study to Investigate the Impact of Different Intensities Training on ADL and BODE Index in COPD
ClinicalTrials.gov study NCT01977469. IPD Sharing: Not stated. Countries: 1. Publications: 16.
Comparison of Upper Extremity Exercise Capacity and ADL Between Subjects With Bronchiectasis and Healthy Controls
ClinicalTrials.gov study NCT05084547. IPD Sharing: NO. Countries: 1. Publications: 1.
Minimal Important Difference for the Glittre-ADL Test and London Chest Activity of Daily Living Scale
ClinicalTrials.gov study NCT03251781. IPD Sharing: NO. Countries: 1. Publications: 10.
Assessment of Advanced Glaucomatous Visual Field Loss and Its Impact on Visual Exploration, Activities of Daily Living (ADL) and Quality of Life (QoL)
ClinicalTrials.gov study NCT01372319. IPD Sharing: Not stated. Countries: 1. Publications: 3.
ADL-PDT Under Routine Clinical Conditions in Patients With Actinic Keratosis
ClinicalTrials.gov study NCT05725213. IPD Sharing: NO. Countries: 1. Publications: 1.
Cognitive-driven ADL Impairment as a Predictor for PDD
ClinicalTrials.gov study NCT03687203. IPD Sharing: UNDECIDED. Countries: 1. Publications: 1.
Effect of Combined Endurance Training on ADL and Walking in COPD Patients
ClinicalTrials.gov study NCT05708443. IPD Sharing: Not stated. Countries: 1. Publications: 29.
Comparison of TTE and LTTBT on Trunk Control, Balance and ADL's in Stroke Patients
ClinicalTrials.gov study NCT07248618. IPD Sharing: NO. Countries: 1. Publications: 12.
Hand Exercises for Women With Rheumatoid Arthritis and Impaired ADL Ability: an Exploratory Trial
ClinicalTrials.gov study NCT02140866. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Progression in Cognitive ADLs in Parkinson's Disease
ClinicalTrials.gov study NCT05806866. IPD Sharing: YES. Countries: 1. Publications: 4.
Effect of Group-Task-Oriented Training on GMFM and ADL in Children With DS
ClinicalTrials.gov study NCT06459440. IPD Sharing: NO. Countries: 1. Publications: 1.
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.