Barcoding human physical activity to assess chronic pain conditions.

Area of Science:

• Biomedical Engineering
• Rehabilitation Medicine
• Pain Management

Background:

• Chronic pain is a complex, multidimensional experience impacting physical, emotional, and social functioning.
• Current pain assessment tools rely on subjective self-reporting, lacking objective measures.
• Developing reliable tools to capture chronic pain's impact has been a long-standing challenge.

Purpose of the Study:

• To investigate if comprehensive analysis of real-life physical activity (PA) can objectively capture behavioral aspects reflecting physical and emotional functioning in chronic pain patients.
• To introduce and validate the concept of PA 'barcoding' for assessing pain-related activity behaviors.

Main Methods:

• Physical activity was monitored for five consecutive days in 60 chronic pain patients and 15 healthy controls.
• PA 'barcoding' was developed by combining PA features (type, intensity, duration) into distinct PA states, visualized as temporal sequences.
• Structural complexity metrics (entropy, Lempel-Ziv complexity) and composite scores quantified PA barcode information, with reliability assessed by comparing pain intensity groups.

Main Results:

• PA barcodes demonstrated significant discriminative features for characterizing chronic pain conditions.
• The structural complexity of PA barcodes decreased with increasing pain intensity, indicating reduced activity and variety.
• Objective measures derived from PA analysis correlated with subjective pain intensity.

Conclusions:

• Comprehensive analysis of daily-life physical activity provides an objective appraisal of pain intensity.
• PA barcode structural complexity effectively captures pain-related functional limitations.
• This approach offers a promising objective method for assessing chronic pain, complementing subjective reports.