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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Ecological validity of a deep learning algorithm to detect gait events from real-life walking bouts in mobility-limiting diseases
|
|---|---|
| Published in |
Frontiers in Neurology, October 2023
|
| DOI | 10.3389/fneur.2023.1247532 |
| Pubmed ID | |
| Authors |
Robbin Romijnders, Francesca Salis, Clint Hansen, Arne Küderle, Anisoara Paraschiv-Ionescu, Andrea Cereatti, Lisa Alcock, Kamiar Aminian, Clemens Becker, Stefano Bertuletti, Tecla Bonci, Philip Brown, Ellen Buckley, Alma Cantu, Anne-Elie Carsin, Marco Caruso, Brian Caulfield, Lorenzo Chiari, Ilaria D'Ascanio, Silvia Del Din, Björn Eskofier, Sara Johansson Fernstad, Marceli Stanislaw Fröhlich, Judith Garcia Aymerich, Eran Gazit, Jeffrey M. Hausdorff, Hugo Hiden, Emily Hume, Alison Keogh, Cameron Kirk, Felix Kluge, Sarah Koch, Claudia Mazzà, Dimitrios Megaritis, Encarna Micó-Amigo, Arne Müller, Luca Palmerini, Lynn Rochester, Lars Schwickert, Kirsty Scott, Basil Sharrack, David Singleton, Abolfazl Soltani, Martin Ullrich, Beatrix Vereijken, Ioannis Vogiatzis, Alison Yarnall, Gerhard Schmidt, Walter Maetzler |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 23 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 23 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Other | 4 | 17% |
| Researcher | 4 | 17% |
| Student > Doctoral Student | 2 | 9% |
| Student > Master | 2 | 9% |
| Student > Bachelor | 1 | 4% |
| Other | 1 | 4% |
| Unknown | 9 | 39% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 3 | 13% |
| Nursing and Health Professions | 2 | 9% |
| Medicine and Dentistry | 2 | 9% |
| Computer Science | 1 | 4% |
| Social Sciences | 1 | 4% |
| Other | 2 | 9% |
| Unknown | 12 | 52% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 16 October 2023.
All research outputs
#22,067,759
of 24,625,114 outputs
Outputs from Frontiers in Neurology
#10,087
of 13,701 outputs
Outputs of similar age
#137,735
of 172,044 outputs
Outputs of similar age from Frontiers in Neurology
#112
of 285 outputs
Altmetric has tracked 24,625,114 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,701 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.4. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 172,044 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 285 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.