Written with: Max Fikes
Using Artificial Intelligence to Measure the Progression of Parkinson’s Disease
Parkinson’s disease is a neurodegenerative disorder that affects dopamine-producing neurons in the brain’s substantia nigra. Recent studies have shown significant advances in treating the disease, particularly in measuring and monitoring motor symptoms.
Innovation at the University of California, San Francisco
Researchers at the University of California, San Francisco, have developed a video-based machine learning system to accurately measure symptom progression in Parkinson’s disease patients without needing specialized movement labs. The system uses videos captured on devices like smartphones to predict the severity of motor symptoms. They also developed a system allowing patients to visit a clinic where their symptoms can be quantified and measured.
Benefits of Artificial Intelligence
The AI system addresses limitations in previous research by extracting important motion features to train machine learning models capable of predicting motor impairment. Using videos from everyday devices such as smartphones allows for easier tracking of symptoms outside clinical settings, providing new options for medical treatment. The technology can measure symptoms like tremors, stiffness, and slowed movement.
Drawbacks
However, there are some drawbacks to using AI. Since it relies on smartphone technology, issues like battery life, camera quality, and environmental sensitivity arise. Machine learning models trained on clean data may not perform well in noisy home environments, limiting their effectiveness. Additionally, some patients may be hesitant to trust this type of treatment.
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