Wearable sensor technologies for individuals with back pain: a scoping review

Area of Science:

• Biomedical Engineering
• Rehabilitation Technology
• Digital Health

Background:

• Wearable sensor technologies enable real-time collection of biosignals crucial for understanding spinal function and back pain.
• These advancements hold significant potential to transform back pain treatment paradigms, enhance diagnostic movement phenotyping, and enable longitudinal tracking of treatment effectiveness.
• Historically, wearable sensor data for spinal applications were limited in scope, often relying on single devices and traditional statistical analyses.

Purpose of the Study:

• To conduct a scoping review investigating the development status and trends in wearable sensor technologies for measuring biosignals related to spinal function and back pain.
• To identify key advancements and emerging future trends within this rapidly evolving field.
• To synthesize current literature on wearable sensors for spine applications.

Main Methods:

• Comprehensive literature search across major databases including PubMed, Web of Science, and EMBASE.
• Systematic review of articles published up to April 9, 2025.
• Analysis of trends in wearable sensor types, data collection methods, and analytical techniques.

Main Results:

• The field of wearable sensors for spine applications has reached an inflection point, overcoming previous technological and analytical limitations.
• There is a growing diversity in wearable sensor types available for spinal monitoring.
• Integration of real-time interpretation through machine-learning algorithms is becoming prevalent, moving beyond traditional statistical modeling.

Conclusions:

• Wearable sensor technology is rapidly advancing, offering objective and comprehensive evaluations of spinal movements.
• The convergence of diverse sensor technologies and machine learning algorithms is paving the way for significant progress in back pain research and clinical practice.
• Future trends indicate a move towards more sophisticated, multi-modal sensor systems and advanced data analytics for personalized back pain management.