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Mendeley readers
| Chapter title |
Short Time Frequency Analysis of Theta Activity for the Diagnosis of Bruxism on EEG Sleep Record
|
|---|---|
| Chapter number | 4 |
| Book title |
Advanced Computational Intelligence Techniques for Virtual Reality in Healthcare
|
| Published by |
Springer, Cham, January 2020
|
| DOI | 10.1007/978-3-030-35252-3_4 |
| Book ISBNs |
978-3-03-035251-6, 978-3-03-035252-3
|
| Authors |
Md Belal Bin Heyat, Dakun Lai, Faijan Akhtar, Mohd Ammar Bin Hayat, Shajan Azad, Heyat, Md Belal Bin, Lai, Dakun, Akhtar, Faijan, Hayat, Mohd Ammar Bin, Azad, Shajan |
Mendeley readers
The data shown below were compiled from readership statistics for 21 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 21 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 4 | 19% |
| Professor > Associate Professor | 3 | 14% |
| Student > Master | 3 | 14% |
| Student > Bachelor | 3 | 14% |
| Lecturer > Senior Lecturer | 1 | 5% |
| Other | 2 | 10% |
| Unknown | 5 | 24% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 6 | 29% |
| Computer Science | 3 | 14% |
| Medicine and Dentistry | 3 | 14% |
| Earth and Planetary Sciences | 1 | 5% |
| Business, Management and Accounting | 1 | 5% |
| Other | 2 | 10% |
| Unknown | 5 | 24% |