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Dynamic Digital Biomarkers of Motor and Cognitive Function in Parkinson's Disease
Published on: July 24, 2019
Computer model for leg agility quantification and assessment for Parkinson's disease patients
Christopher Ornelas-Vences1, Luis Pastor Sánchez-Fernández2, Luis Alejandro Sánchez-Pérez2,3
1Centro de Investigación en Computación, Instituto Politécnico Nacional, Juan de Dios Bátiz Avenue, 07738, Mexico City, Mexico. chrorn9@gmail.com.
Medical & Biological Engineering & Computing
|September 15, 2018
Summary
This study introduces a new method using inertial sensors to objectively assess Parkinson's disease (PD) leg agility. The developed fuzzy model achieves high accuracy, improving patient monitoring beyond subjective visual exams.
Area of Science:
- Biomedical Engineering
- Neurology
- Data Science
Background:
- Parkinson's disease (PD) is a progressive neurodegenerative disorder impacting motor control.
- The Movement Disorder Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS) relies on subjective visual assessment for disease progression.
- Leg agility assessment within the MDS-UPDRS is prone to examiner subjectivity and limitations of discrete scales.
Purpose of the Study:
- To develop an objective, quantitative method for assessing leg agility in Parkinson's disease patients.
- To reduce subjectivity in Parkinson's disease motor assessment using wearable inertial sensors.
- To create a continuous assessment scale that overcomes the 'floor/ceil' effects of discrete clinical scales.
Main Methods:
- Fifty Parkinson's disease patients performed the leg agility task while wearing inertial sensor units on each ankle.
- Quantified kinematic features were extracted and analyzed based on MDS-UPDRS criteria.
- A fuzzy inference model was designed to integrate clinical knowledge and quantify leg agility objectively.
Main Results:
- The fuzzy inference model achieved 92.35% coincidence with expert clinical assessments.
- The system accurately captured leg agility features irrespective of task speed, reducing observational uncertainty.
- A continuous output scale was implemented, mitigating the limitations of discrete rating scales.
Conclusions:
- Inertial sensor-based quantification of leg agility is feasible for Parkinson's disease assessment.
- The developed computer model offers repeatable and objective measurements for improved patient follow-up.
- This approach enhances the objective monitoring of Parkinson's disease progression compared to visual examination.
