More information: Rana M. Khalil et al, Simplification of Mobility Tests and Data Processing to Increase Applicability of Wearable Sensors as Diagnostic Tools for Parkinson's Disease, Sensors (2024).

What the trained eye cannot see: Detecting movement defects in early stage Parkinson's disease Date: August 15, 2024 Source: University of Florida Summary: Using machine learning to analyze video ...

AI techniques primarily use machine learning and deep learning algorithms trained on extensive data sets from simple voice recordings from Parkinson’s patients and healthy controls.

Machine learning technology reveals that high speed movements are the first affected behaviors in early stages of Parkinson’s disease. Levodopa repairs the speed—not the structure ...

Wearable sensor data combined with machine learning predicts fall risk in Parkinson's patients, enhancing preventive care and clinical outcomes over five years.

Researchers have identified a neurochemical signature that sets Parkinson's disease apart from essential tremor—two of the ...

Researchers videotaped facial expressions of 1,452 people, including 391 with Parkinson's disease – 300 who were clinically diagnosed and 91 who self-reported their condition.

A team of researchers at UCLA has developed a high-tech diagnostic pen that can detect signs of Parkinson’s disease with over 96% accuracy.

Explore Parkinson’s disease symptoms, diagnosis, and emerging therapies—including research on inflammation, biomarkers, and future treatments.