Healthy Control, Multiple System Atrophy, Parkinson's Disease, Progressive Supranuclear Palsy(PSP)
Conditions
Brief summary
This research employs AI to analyze facial expressions and speech patterns, aiming to develop new digital tools for diagnosing and differentiating Parkinson's disease and similar disorders.
Interventions
OTHERvideo recording
The patient's facial expressions and speech characteristics were recorded via video for assessment purposes.
Sponsors
Beijing Tiantan Hospital
Study design
Observational model
COHORT
Time perspective
CROSS_SECTIONAL
Eligibility
Sex/Gender
ALL
Age
15 Years to 75 Years
Healthy volunteers
Yes
Inclusion criteria
1. Inclusion Criteria for Parkinson's Disease (PD) Group: (1) Diagnostic Criteria: Meet the diagnostic criteria for Parkinson's disease established by the Movement Disorder Society (MDS) in 2015. (2) Age Range: 18-75 years old. (3) Disease Severity: Early-stage PD: Hoehn-Yahr score ≤ 2.5 points. Mid-to-late-stage PD: Hoehn-Yahr score 2.5-5 points. (4) Consent for Data Collection: Willing to undergo facial expression video and speech audio recording. (5) Informed Consent: Signed informed consent form. 2. Inclusion Criteria for Parkinson's Plus Syndromes (MSA-P, PSP) Group: (1) Age Range: 18-75 years old. (2) Diagnostic Criteria: MSA patients must meet the diagnostic criteria established by the \[Chinese Expert Consensus on the Diagnosis of Multiple System Atrophy, 2017\]. PSP patients must meet the diagnostic criteria established by the \[Chinese Clinical Diagnostic Criteria for Progressive Supranuclear Palsy, 2016 Edition\]. (3) Consent for Data Collection: Willing to undergo facial expression video and speech audio recording. (4) Informed Consent: Signed informed consent form.
Exclusion criteria
1. History of cerebrovascular disease, head trauma, hydrocephalus, brain tumors, or intracranial surgery. 2. Presence of metal implants, cardiac pacemakers, or other metallic foreign bodies (applies to PD patients). 3. Severe dyskinesia in PD patients that would compromise cooperation with video/audio recording. 4. Mini-Mental State Examination (MMSE) score ≤ 24 points.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Diagnostic Accuracy of the AI Model in Assessing [ Disease/Condition ] Severity | Baseline | The effectiveness of the model was demonstrated through a comparison between model-predicted scores and human expert ratings. |
Countries
China
Contacts
CONTACTLingyan Ma, M.D.
Outcome results
None listed