You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
Mendeley readers
| Chapter title |
An Interpretable Machine Learning Model for Human Fall Detection Systems Using Hybrid Intelligent Models
|
|---|---|
| Chapter number | 8 |
| Book title |
Challenges and Trends in Multimodal Fall Detection for Healthcare
|
| Published by |
Springer, Cham, January 2020
|
| DOI | 10.1007/978-3-030-38748-8_8 |
| Book ISBNs |
978-3-03-038747-1, 978-3-03-038748-8
|
| Authors |
Paulo Vitor C. Souza, Augusto J. Guimaraes, Vanessa S. Araujo, Lucas O. Batista, Thiago S. Rezende, Souza, Paulo Vitor C., Guimaraes, Augusto J., Araujo, Vanessa S., Batista, Lucas O., Rezende, Thiago S. |
Mendeley readers
The data shown below were compiled from readership statistics for 18 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 18 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 4 | 22% |
| Researcher | 3 | 17% |
| Lecturer | 2 | 11% |
| Student > Master | 2 | 11% |
| Professor | 1 | 6% |
| Other | 1 | 6% |
| Unknown | 5 | 28% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 3 | 17% |
| Engineering | 2 | 11% |
| Social Sciences | 1 | 6% |
| Pharmacology, Toxicology and Pharmaceutical Science | 1 | 6% |
| Neuroscience | 1 | 6% |
| Other | 1 | 6% |
| Unknown | 9 | 50% |