Research on Voice Intelligent Monitoring Technology for Early Warning of Recurrence of Depression Disorder

NCT04685083 | Unknown

• 1 other identifier: 2020VIMT
• Study Type: observational
• Target: 240
• Locations: 1 country
• Sites: 1

Brief Summary

This study aims to collect the voice output of depression patients and healthy subjects, extract the acoustic and semantic parameters, compare the similarities and differences between the depression group and the healthy control group horizontally, and track the depression patients' changes in the rehabilitation stage to construct a voice-based early warning model of depression recurrence. At the same time, the use of EEG technology, nuclear magnetic resonance and near-infrared brain imaging technology to record and analyze the neural activity characteristics behind the voice variation of depression patients, and build a neural mechanism model. And construct the facial recognition function through the convolutional neural network, extract the facial parameters to enrich the intelligent monitoring and early warning technology.

1. 1.Collect linguistic data of depression patients and healthy people collected in the laboratory, as well as data related to changes in the condition of depression patients in daily life and home care after treatment, and construct comparative data and dynamic observations Large database to analyze its voice mutation characteristics;
2. 2.Using EEG technology, nuclear magnetic resonance, and near-infrared brain imaging to record and analyze the neural activity characteristics behind the voice variation of depression patients, and build a neural mechanism model.
3. 3.Use the convolutional neural network to realize the facial recognition function, and extract the facial parameters to enrich the monitoring indicators.
4. 4.Based on the dynamic observation big data of depression speech mutation, construct the speech feature parameter vector of depression recurrence, and use adaptive personalized intelligent learning algorithm to develop intelligent monitoring and early warning technology.
5. 5.Establish monitoring and diagnostic indicators for recurrence early warning, verify the application of the above-mentioned intelligent monitoring and early warning technology in rehabilitation guidance, and make a comprehensive assessment.

Conditions

Depressive Disorder

Outcome Measures

Primary Outcomes (5)

• Acoustic parameters

  Acoustic parameters of depression patients and healthy subjects are extracted through voice recording.

  2022.6

• Neural activity parameters of EEG

  Neural activity parameters of depression patients and healthy subjects are extracted through EEG technology.

  2022.6

• Neural activity parameters of MRI

  Neural activity parameters of depression patients and healthy subjects are extracted through MRI.

  2022.6

• Neural activity parameters of near-infrared brain imaging

  Neural activity parameters of depression patients and healthy subjects are extracted through near-infrared brain imaging.

  2022.6

• Facial action parameters of facial expression recognition technology

  The facial expression recognition technology is implemented by convolutional neural network to extract facial action parameters.

  2022.6

Study Arms (3)

Patients with Depression in consolidation phase

Patients with Depression in acute onset

Healthy subjects

Eligibility Criteria

• Age: 18 Years - 65 Years
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

It is planned to collect 80 patients with depression in the consolidating stage, 80 patients with depression in the acute stage, and 80 healthy controls recruited by advertisement in the psychological consultation clinic and psychiatric clinic of Shanghai Mental Health Center.

You may qualify if:

• Patients with depression in the consolidation/maintenance phase
• years old, no gender limit;
• Meet the DSM-5 diagnostic criteria for depression;
• Currently in the consolidation/maintenance phase, with stable condition, HAMD-17 \<7 points;
• Patients and their guardians understand the nature of this study and sign an informed consent form.
• Have sufficient audiovisual level to complete the necessary inspections for research;
• Han nationality
• Willing to participate in this research;
• Education level is junior high school and above.
• Patients with depression in acute onset:
• years old, no gender limit;
• Meet the DSM-5 diagnostic criteria for depression;
• Currently in depressive episode, HAMD-17\>17 points;
• Patients and their guardians understand the nature of this study and sign an informed consent form.
• Have sufficient audiovisual level to complete the necessary inspections for research;

You may not qualify if:

• Patients with depression in the consolidation/maintenance phase
• Patients with severe brain diseases and other severe physical diseases;
• Diagnosis of other mental diseases such as schizophrenia and bipolar disorder;
• There are negative beliefs or a higher risk of suicide;
• People who are addicted to psychoactive substances such as alcohol or drugs;
• Women who are pregnant or about to become pregnant recently, and women who are breastfeeding;
• There are metal implants in the body: there is a pacemaker, intracranial silver clip, metal denture, arterial stent, arterial clip, joint metal fixation, or other metal implant conditions, or non-right-handed (this standard (Only for MRI testers);
• Failure to sign or refuse to sign the informed consent form.
• Patients with depression in acute onset:
• Patients with severe brain diseases and other severe physical diseases;
• Diagnosis of other mental diseases such as schizophrenia and bipolar disorder;
• There are negative beliefs or a higher risk of suicide;
• People who are addicted to psychoactive substances such as alcohol or drugs;
• Women who are pregnant or about to become pregnant recently, and women who are breastfeeding;
• There are metal implants in the body: there is a pacemaker, intracranial silver clip, metal denture, arterial stent, arterial clip, joint metal fixation, or other metal implant conditions, or non-right-handed (this standard (Only for MRI testers);

Sponsors & Collaborators

• Shanghai Mental Health Center: lead

Study Sites (1)

Shanghai Mental Health Center

Shanghai, Shanghai Municipality, 200030, China

RECRUITING

MeSH Terms

Conditions

Depressive Disorder

Condition Hierarchy (Ancestors)

Mood Disorders; Mental Disorders

Central Study Contacts

Qing Fan

CONTACT

13916436072; fanqing_98@vip.sina.com

Study Design

• Study Type: observational
• Observational Model: CASE CONTROL
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: November 18, 2020
• First Posted: December 28, 2020
• Study Start: December 31, 2020
• Primary Completion: December 31, 2021
• Study Completion: December 31, 2022
• Last Updated: May 19, 2021

Record last verified: 2020-11

Locations

CN (1)