Ignite Creation Date:
2025-12-24 @ 10:21 PM
Ignite Modification Date:
2025-12-28 @ 7:09 PM
Study NCT ID:
NCT05608135
Status:
RECRUITING
Last Update Posted:
2023-03-10
First Post:
2022-09-28
Is NOT Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
AI-based Multi-center Research on Identification/Classification/Aided Diagnosis of Mood Disorder
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D001714', 'term': 'Bipolar Disorder'}, {'id': 'D003865', 'term': 'Depressive Disorder, Major'}], 'ancestors': [{'id': 'D000068105', 'term': 'Bipolar and Related Disorders'}, {'id': 'D019964', 'term': 'Mood Disorders'}, {'id': 'D001523', 'term': 'Mental Disorders'}, {'id': 'D003866', 'term': 'Depressive Disorder'}]}}, 'protocolSection': {'designModule': {'studyType': 'OBSERVATIONAL', 'designInfo': {'timePerspective': 'CROSS_SECTIONAL', 'observationalModel': 'CASE_CONTROL'}, 'enrollmentInfo': {'type': 'ESTIMATED', 'count': 960}, 'patientRegistry': False}, 'statusModule': {'overallStatus': 'RECRUITING', 'startDateStruct': {'date': '2022-12-01', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2023-03', 'completionDateStruct': {'date': '2025-12', 'type': 'ESTIMATED'}, 'lastUpdateSubmitDate': '2023-03-09', 'studyFirstSubmitDate': '2022-09-28', 'studyFirstSubmitQcDate': '2022-11-07', 'lastUpdatePostDateStruct': {'date': '2023-03-10', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2022-11-08', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2024-12', 'type': 'ESTIMATED'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'facial action unit detection', 'timeFrame': 'Baseline', 'description': '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.'}, {'measure': 'event-related potentials', 'timeFrame': 'Baseline', 'description': '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'}, {'measure': 'Galvanic skin response', 'timeFrame': 'Baseline', 'description': "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"}]}, 'oversightModule': {'oversightHasDmc': False, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'keywords': ['Bipolar Disorder Depression', 'Major Depression', 'Machine Learning', 'Skin Potential', 'Micro-Facial Expression', 'Electroencephalogram'], 'conditions': ['Bipolar Disorder Depression', 'Major Depression']}, 'descriptionModule': {'briefSummary': '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.\n\nTherefore，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.'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['CHILD', 'ADULT'], 'maximumAge': '55 Years', 'minimumAge': '15 Years', 'samplingMethod': 'NON_PROBABILITY_SAMPLE', 'studyPopulation': "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.", 'healthyVolunteers': True, 'eligibilityCriteria': "Inclusion Criteria:\n\n1. Age 15-55, regardless of gender;\n2. 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);\n3. Total score of Hamilton Depression Scale (HAMD-17) ≥17, and Young's Manic Scale (YMRS) ≤6;\n4. Junior high school or above.\n\nExclusion Criteria:\n\n1. The patient conforms to DSM-IV schizophrenia and related spectrum disorders.\n2. 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;\n3. Had a history of alcohol or psychoactive substance abuse/dependence in the 6 months prior to the test;\n4. Those considered unsuitable for inclusion by the researcher."}, 'identificationModule': {'nctId': 'NCT05608135', 'briefTitle': 'AI-based Multi-center Research on Identification/Classification/Aided Diagnosis of Mood Disorder', 'organization': {'class': 'OTHER', 'fullName': 'First Affiliated Hospital of Zhejiang University'}, 'officialTitle': 'Recognition/Classification/Auxiliary Diagnosis of Affective Disorder Based on AI:A Multi-center Study', 'orgStudyIdInfo': {'id': 'IIT20210021B-R2'}}, 'contactsLocationsModule': {'locations': [{'zip': '310000', 'city': 'Hangzhou', 'state': 'Zhejiang', 'status': 'RECRUITING', 'country': 'China', 'contacts': [{'name': 'Hu ShaoHua', 'role': 'CONTACT', 'email': 'dorhushaohua@zju.edu.cn', 'phone': '13957162903'}], 'facility': 'The First Affiliated Hospital of Zhejiang University', 'geoPoint': {'lat': 30.29365, 'lon': 120.16142}}], 'centralContacts': [{'name': 'Hu ShaoHua, M.D', 'role': 'CONTACT', 'email': 'dorhushaohua@zju.edu.cn', 'phone': '+86 13357169115'}, {'name': 'Lv HaiLong, M.D', 'role': 'CONTACT', 'email': 'hailonglyu@zju.edu.cn', 'phone': '+86 13858007467'}]}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'First Affiliated Hospital of Zhejiang University', 'class': 'OTHER'}, 'responsibleParty': {'type': 'PRINCIPAL_INVESTIGATOR', 'investigatorTitle': 'Head of Department of Psychaitry , First Affiliated Hospital of Zhejiang University Affiliation: First Affiliated Hospital of Zhejiang University', 'investigatorFullName': 'Hu ShaoHua', 'investigatorAffiliation': 'First Affiliated Hospital of Zhejiang University'}}}}