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Published on: August 8, 2019
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From Lab to Life: Correlating Lab-Based Motion Capture and Field-Based Wearable Sensor Metrics to Assess Motor
Summary
Wearable sensors and lab tests can track multiple sclerosis (MS) motor dysfunction. Hand movement differences in lab tasks correlate with disease severity, showing wearable sensors
Area of Science:
- Neurology
- Biomedical Engineering
- Rehabilitation Science
Background:
- Multiple Sclerosis (MS) causes progressive motor dysfunction, impacting daily life.
- Accurate and scalable methods for tracking MS progression are crucial for effective management.
- Lab-based kinematic analysis and wearable sensors offer potential for motor assessment.
Purpose of the Study:
- To investigate the correlation between laboratory-based kinematic metrics and real-world wearable sensor data in individuals with MS.
- To evaluate the utility of these metrics as potential biomarkers for MS disease severity and progression.
- To explore the role of inertial measurement units (IMUs) in monitoring motor impairments in activities of daily living (ADLs).
Main Methods:
- Participants performed standardized Tea Making and Drinking tasks in a laboratory setting, captured via motion analysis.
- Wrist-worn inertial measurement units (IMUs) collected data during various activities of daily living.
- Correlation analyses were performed between lab-derived kinematic metrics (e.g., Path Length hand differences - PL_Diff) and Expanded Disability Status Scale (EDSS) scores, as well as between lab and wearable sensor data.
Main Results:
- Path length hand differences (PL_Diff) during lab tasks showed a significant correlation with EDSS scores (r=0.64, adjusted p=0.02).
- Consistent correlations were observed between lab-based kinematics and wearable IMU metrics across different ADLs.
- These findings suggest that IMU data can effectively reflect real-world motor function related to lab-based assessments.
Conclusions:
- Lab-based kinematic metrics, particularly hand movement differences, show promise as sensitive markers for MS disease severity.
- Wearable sensor data, specifically from IMUs, can provide valuable real-world insights into motor impairment in MS.
- Integrating wearable assessments can enhance the sensitivity and scalability of tracking MS progression and informing clinical interventions.
