A pervasive assessment of motor function: a lightweight grip strength tracking system

Area of Science:

• Biomedical Engineering
• Neurology
• Rehabilitation Technology

Background:

• Chronic neuro-degenerative diseases pose significant diagnostic and treatment costs.
• Early detection of motor function deficits is crucial for effective management.
• Portable monitoring systems offer a promising solution for accessible patient assessment.

Purpose of the Study:

• To introduce a mobile, cost-effective monitoring system for quantifying upper-limb performance in patients with movement disorders.
• To develop and validate an ailment-based analysis framework for patient data classification.
• To assess the system's utility as a preliminary diagnostic tool for hand-movement performance.

Main Methods:

• Development of a portable sensing hardware for upper-limb movement quantification.
• Implementation of a general motor performance analysis approach.
• Application of a significant-feature identification algorithm for ailment-based, cross-patient data analysis and classification.

Main Results:

• The system effectively quantifies general motor performance and hand-movement abilities.
• Ailment-based analysis achieved high classification accuracy for different patient groups.
• Cerebral vascular accident (CVA) patients were classified with up to 95.00% accuracy.
• Chronic inflammatory demyelinating polyneuropathy (CIDP) patients were classified with up to 91.42% accuracy.

Conclusions:

• The developed portable monitoring system is a viable preliminary diagnostic tool for assessing hand-movement performance.
• The ailment-based analysis framework demonstrates effectiveness in differentiating between CVA, CIDP, and healthy individuals.
• This technology has the potential to improve early diagnosis and insight into motor function in neuro-degenerative diseases.