Pain-Related Autonomic Dysregulation During Sleep in Multiple Sclerosis: Insights from Wearable Sensor Data

Area of Science:

• Neurology
• Biomedical Engineering
• Sleep Science

Background:

• Pain is a prevalent and debilitating symptom in Multiple Sclerosis (MS).
• Pain in MS can be nociceptive or neuropathic, impacting the autonomic nervous system (ANS) and sleep quality.
• Wearable sensors offer a viable method for real-world physiological monitoring.

Purpose of the Study:

• To investigate sleep-related autonomic nervous system (ANS) activity in MS patients with different pain types using wearable sensors.
• To analyze physiological signals including photoplethysmography (PPG), electrodermal activity (EDA), skin temperature (SKT), and accelerometer (ACC) data.
• To identify associations between pain, sleep patterns, and autonomic function in MS.

Main Methods:

• Utilized a wrist-worn medical device to collect physiological data during sleep in MS patients.
• Extracted features from PPG, EDA, SKT, and ACC signals.
• Employed Linear Mixed Effects Models to analyze the collected data and identify significant patterns.

Main Results:

• Neuropathic pain was associated with fewer wakes after sleep onset and higher sleep efficiency.
• Significant autonomic dysregulation was observed in both nociceptive and neuropathic pain groups.
• Specific EDA metrics (mean slope, SympatheticN, autocorrelation) indicated autonomic dysfunction.

Conclusions:

• Pain in MS is significantly associated with altered autonomic nervous system (ANS) patterns during sleep.
• Wearable devices provide objective physiological data for monitoring pain-related autonomic dysregulation.
• Further research with larger cohorts is warranted to elucidate underlying mechanisms and inform personalized pain management.