Study on Artificial Intelligence-Based Facial and Speech-Related Patterns in Parkinson's Disease and Their Digital Biomarkers

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.

Eligibility

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.

Conditions4

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