Zhiguo Zheng
Biographic Data
| ID | 7532914 |
|---|---|
| NAME | Zhiguo Zheng |
| GIVEN NAMES | Zhiguo |
| FAMILY NAME | Zheng |
| SIGNATURE | ZHENG Z |
| AFFILIATIONS | Hainan University |
| ORCID | 0009-0004-3588-7729 |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 2 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2024 |
| LATEST PUBLICATION YEAR | 2024 |
| H-INDEX | 0 |
Enhanced classification and severity prediction of major depressive disorder using acoustic features and machine learning
The vocal acoustic features can not only effectively classify the major depression and the healthy control groups, but also accurately predict the severity of depressive symptoms
Diagnosing and tracking depression based on eye movement in response to virtual reality
The results suggest that eye movement indices obtained using a VR eye tracker can serve as useful biomarkers for detecting depression symptoms. Specifically, the fixation and saccade indices showed promise in predicting depression. Furthermore, CCBT demonstrated effectiveness in treating depression, as evidenced by the observed changes in eye movement indices and PHQ-9 scores. In conclusion, this study presents a novel approach for depression det…
No prominent works on this page.
Enhanced classification and severity prediction of major depressive disorder using acoustic features and machine learning
The vocal acoustic features can not only effectively classify the major depression and the healthy control groups, but also accurately predict the severity of depressive symptoms
Diagnosing and tracking depression based on eye movement in response to virtual reality
The results suggest that eye movement indices obtained using a VR eye tracker can serve as useful biomarkers for detecting depression symptoms. Specifically, the fixation and saccade indices showed promise in predicting depression. Furthermore, CCBT demonstrated effectiveness in treating depression, as evidenced by the observed changes in eye movement indices and PHQ-9 scores. In conclusion, this study presents a novel approach for depression det…
Artificial Intelligence (2 works) · Computer Science (2 works) · Depression (economics (2 works) · Machine learning (2 works) · Medicine (2 works) · Mental Health Research Topics (2 works) · Psychology (2 works) · Anxiety (1 works) · Artificial neural network (1 works) · Audiology (1 works)