A Self-Administered, Digitized Approach to Quantifying the Cardinal Motor Symptoms in Parkinson's Disease

Area of Science:

• Neurology
• Biomedical Engineering
• Digital Health

Background:

• Parkinson's disease (PD) care is often suboptimal due to limited neurologist access and reliance on subjective symptom ratings.
• Objective, quantitative measures are needed for accurate PD motor symptom assessment and treatment decisions.

Purpose of the Study:

• To validate the Ceraxis Insight platform's quantitative motor symptom metrics against gold-standard clinical assessments in people with Parkinson's disease (PwPD).

Main Methods:

• Nineteen PwPD underwent clinical examination and completed nine Ceraxis Insight tablet-based assessments with a sensor stylus.
• Quantitative metrics were derived from IMU, force transducer, and touchscreen data.
• Statistical analyses included mixed-effect models, correlation, and logistic regression.

Main Results:

• Ceraxis Insight metrics significantly correlated with (r > 0.70) and predicted (p < 0.05) MDS-UPDRS III scores for total, bradykinesia, tremor, rigidity, and gait difficulty.
• Metrics effectively discriminated between ON- and OFF-deep brain stimulation (DBS) states (AUC > 0.70).

Conclusions:

• The Ceraxis Insight platform provides a validated, objective tool for assessing PD motor symptoms.
• This technology can support data-driven treatment decisions in clinical or remote settings, enhancing care for PwPD.