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.
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.
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.
History of cerebrovascular disease, head trauma, hydrocephalus, brain tumors, or intracranial surgery.
Presence of metal implants, cardiac pacemakers, or other metallic foreign bodies (applies to PD patients).
Severe dyskinesia in PD patients that would compromise cooperation with video/audio recording.
Mini-Mental State Examination (MMSE) score ≤ 24 points.
In this study, participants were recruited from a single center in China. They were enrolled through outpatient assessment and screening.
Cohort
Cross-sectional
video recording
Other interventionThe patient's facial expressions and speech characteristics were recorded via video for assessment purposes.
Diagnostic Accuracy of the AI Model in Assessing [ Disease/Condition ] Severity
The effectiveness of the model was demonstrated through a comparison between model-predicted scores and human expert ratings.
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