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Mendeley readers
| Title |
Deep Learning-Based Human Activity Recognition for Continuous Activity and Gesture Monitoring for Schizophrenia Patients With Negative Symptoms
|
|---|---|
| Published in |
Frontiers in Psychiatry, September 2020
|
| DOI | 10.3389/fpsyt.2020.574375 |
| Pubmed ID | |
| Authors |
Daniel Umbricht, Wei-Yi Cheng, Florian Lipsmeier, Atieh Bamdadian, Michael Lindemann |
Mendeley readers
The data shown below were compiled from readership statistics for 72 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 72 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 11 | 15% |
| Student > Ph. D. Student | 10 | 14% |
| Student > Bachelor | 9 | 13% |
| Student > Master | 7 | 10% |
| Other | 4 | 6% |
| Other | 6 | 8% |
| Unknown | 25 | 35% |
| Readers by discipline | Count | As % |
|---|---|---|
| Psychology | 9 | 13% |
| Medicine and Dentistry | 8 | 11% |
| Neuroscience | 6 | 8% |
| Computer Science | 4 | 6% |
| Engineering | 4 | 6% |
| Other | 13 | 18% |
| Unknown | 28 | 39% |