AI-based Multi-center Research on Identification/Classification/Aided Diagnosis of Mood Disorder
Recognition/Classification/Auxiliary Diagnosis of Affective Disorder Based on AI:A Multi-center Study
1 other identifier
observational
960
1 country
1
Brief Summary
At present, diagnosis and recognition of depression and bipolar disorder are mainly based on subjective evidence such as clinical interview and scale evaluation. The corresponding diagnosis basis has some shortcomings, such as poor diagnostic reliability and failure in early identification of bipolar disorder. Therefore, it is of great significance to explore objective diagnostic indicators to remedy the deficiencies. Therefore,the investigators collect psychological and physiological information data of patients with bipolar disorder and depression.Then the investigators aim to construct and verify the multidimensional emotion recognition model to analyze the personality characteristics, negative emotions and cognitive reactions of different individuals, and form a systematic accurate recognition and evaluation tool.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P75+ for all trials
Started Dec 2022
Typical duration for all trials
1 active site
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
Click on a node to explore related trials.
Study Timeline
Key milestones and dates
First Submitted
Initial submission to the registry
September 28, 2022
CompletedFirst Posted
Study publicly available on registry
November 8, 2022
CompletedStudy Start
First participant enrolled
December 1, 2022
CompletedPrimary Completion
Last participant's last visit for primary outcome
December 1, 2024
CompletedStudy Completion
Last participant's last visit for all outcomes
December 1, 2025
CompletedMarch 10, 2023
March 1, 2023
2 years
September 28, 2022
March 9, 2023
Conditions
Keywords
Outcome Measures
Primary Outcomes (3)
facial action unit detection
The research recruits subjects to look at pictures and videos and then use cameras to record facial microexpressions. Finally, the research uses machine learning methods to analyze facial micro-expressions. Facial micro-expressions (MEs) are involuntary movements of the face that occur spontaneously when a person experiences an emotion but attempts to suppress or repress the facial expression, typically found in a high-stakes environment.
Baseline
event-related potentials
An electroencephalogram (EEG) is a test that measures electrical activity in the brain using small, metal discs (electrodes) attached to the scalp. Brain cells communicate via electrical impulses and are active all the time, even during asleep. This activity shows up as wavy lines on an EEG recording. The research recruits subjects to look at videos and pictures and use electroencephalography to record event-related potentials. Finally, we use time domain analysis and frequency analysis to get the results
Baseline
Galvanic skin response
The skin also has electrical activity, which is in constant, slight variation, and can be measured and charted. The skin's electrical conductivity fluctuates based on certain bodily conditions, and this fluctuation is called the galvanic skin response.We recruited subjects to watch videos and pictures and record galvanic skin response. Finally, we use time domain analysis and frequency analysis to get the results
Baseline
Eligibility Criteria
The study will be conducted primarily at the First Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China, starting from October 1, 2021, with an estimated total enrollment of 120 participants. Other participating centers include Peking University Sixth Hospital, At the Third Affiliated Hospital of Sun Yat-sen University, At the Second Affiliated Hospital of Kunming Medical University, At Wuhan People's Hospital, At Xiaoshan Hospital in Zhejiang Province, At Wenzhou seventh People's Hospital, At Ruian Fifth People's Hospital, respectively an evaluated 120 participants to be recruited.All research centers of the participants are from China. In screening interviews, the above criteria were carefully examined by two independent investigators.
You may qualify if:
- Age 15-55, regardless of gender;
- The brief International Neuropsychiatric Interview Chinese version (MINI) was used to meet the diagnostic criteria for DSM-IV-TR depressive disorder or bipolar disorder (type I);
- Total score of Hamilton Depression Scale (HAMD-17) ≥17, and Young's Manic Scale (YMRS) ≤6;
- Junior high school or above.
You may not qualify if:
- The patient conforms to DSM-IV schizophrenia and related spectrum disorders.
- The patient has a history of severe head trauma (loss of consciousness for more than 5 minutes), current or previous history of epilepsy, intracranial hypertension, or other serious neurological diseases;
- Had a history of alcohol or psychoactive substance abuse/dependence in the 6 months prior to the test;
Contact the study team to confirm eligibility.
Sponsors & Collaborators
Study Sites (1)
The First Affiliated Hospital of Zhejiang University
Hangzhou, Zhejiang, 310000, China
MeSH Terms
Conditions
Condition Hierarchy (Ancestors)
Central Study Contacts
Study Design
- Study Type
- observational
- Observational Model
- CASE CONTROL
- Time Perspective
- CROSS SECTIONAL
- Sponsor Type
- OTHER
- Responsible Party
- PRINCIPAL INVESTIGATOR
- PI Title
- Head of Department of Psychaitry , First Affiliated Hospital of Zhejiang University Affiliation: First Affiliated Hospital of Zhejiang University
Study Record Dates
First Submitted
September 28, 2022
First Posted
November 8, 2022
Study Start
December 1, 2022
Primary Completion
December 1, 2024
Study Completion
December 1, 2025
Last Updated
March 10, 2023
Record last verified: 2023-03