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 |
Detecting Epilepsy in EEG Signals Using Time, Frequency and Time-Frequency Domain Features
|
|---|---|
| Chapter number | 9 |
| Book title |
Computer Science and Engineering—Theory and Applications
|
| Published by |
Springer, Cham, January 2018
|
| DOI | 10.1007/978-3-319-74060-7_9 |
| Book ISBNs |
978-3-31-974059-1, 978-3-31-974060-7
|
| Authors |
D. E. Hernández, L. Trujillo, E. Z-Flores, O. M. Villanueva, O. Romo-Fewell |
Mendeley readers
The data shown below were compiled from readership statistics for 33 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 33 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 7 | 21% |
| Student > Ph. D. Student | 5 | 15% |
| Student > Master | 5 | 15% |
| Lecturer | 3 | 9% |
| Lecturer > Senior Lecturer | 2 | 6% |
| Other | 5 | 15% |
| Unknown | 6 | 18% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 12 | 36% |
| Computer Science | 6 | 18% |
| Physics and Astronomy | 1 | 3% |
| Unspecified | 1 | 3% |
| Neuroscience | 1 | 3% |
| Other | 1 | 3% |
| Unknown | 11 | 33% |