Yixia Zhu
Biographic Data
| ID | 7968166 |
|---|---|
| NAME | Yixia Zhu |
| GIVEN NAMES | Yixia |
| FAMILY NAME | Zhu |
| SIGNATURE | ZHU Y |
| AFFILIATIONS | Jinhua Academy of Agricultural Sciences |
| ORCID | 0000-0001-6342-5266 |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 2 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2024 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
Multidimensional EEG features integration with feature selection strategy for precision diagnosis of depressive disorders
Depressive disorder (DD), a leading global cause of disability, lacks objective diagnostic biomarkers due to reliance on subjective clinical criteria. This study introduces an algorithm-driven framework integrating multidimensional EEG features, dynamic time-window optimization, feature selection and machine learning to address this gap. Resting-state EEG signals were acquired from 70 DD patients and 30 healthy controls (HC). Three-dimensional ne…
Effects of gender and age on sleep EEG functional connectivity differences in subjects with mild difficulty falling asleep
The results showed that: (1) The functional connectivity of each sleep rhythm wave differed significantly across sleep stages, with delta and beta functional connectivity differing significantly across sleep stages. (2) Significant differences in functional connections among young and middle-aged groups, and among young and elderly groups, but no significant difference between middle-aged and elderly groups. (3) Female functional connectivity str…
No prominent works on this page.
Effects of gender and age on sleep EEG functional connectivity differences in subjects with mild difficulty falling asleep
The results showed that: (1) The functional connectivity of each sleep rhythm wave differed significantly across sleep stages, with delta and beta functional connectivity differing significantly across sleep stages. (2) Significant differences in functional connections among young and middle-aged groups, and among young and elderly groups, but no significant difference between middle-aged and elderly groups. (3) Female functional connectivity str…
Multidimensional EEG features integration with feature selection strategy for precision diagnosis of depressive disorders
Depressive disorder (DD), a leading global cause of disability, lacks objective diagnostic biomarkers due to reliance on subjective clinical criteria. This study introduces an algorithm-driven framework integrating multidimensional EEG features, dynamic time-window optimization, feature selection and machine learning to address this gap. Resting-state EEG signals were acquired from 70 DD patients and 30 healthy controls (HC). Three-dimensional ne…
EEG and Brain-Computer Interfaces (2 works) · Electroencephalography (2 works) · Analysis of variance (1 work) · Audiology (1 work) · Computer Science (1 work) · Delta wave (1 work) · Discriminative model (1 work) · Emotion and Mood Recognition (1 work) · Entropy (arrow of time (1 work) · Feature (linguistics (1 work)