Wearable sensor technologies for individuals with back pain: a scoping review
Jordan J Ryan1, Emma Bowden1, Matthew M Hancock1
1Mechanical Engineering Department, Brigham Young University, Provo, UT, USA.
Abstract:
Recent advancements in wearable data measurement technologies have allowed for real-time collection of biosignals related to spinal function and back pain. These data also have the potential to completely transform back pain treatment paradigms, to improve diagnostic movement phenotyping and to track treatment effectiveness longitudinally. The primary objective of the present scoping review was to investigate the status of development and trends in the use of wearable sensor technologies employed to measure biosignals related to spinal function and back pain, to identify the major developments and future trends for this field.Until recently, much of the wearable sensor data related to spinal function and back pain have come from a relatively small number of technologies, were sampled by a judiciously placed single device, and were analyzed using traditional statistical modeling techniques. However, based on the state of the literature, the field of wearable sensors for spine appears to have reached an inflection point where the previous limiting factors are no longer significant barriers. The growing number of wearable sensor types, combined with real-time interpretation using machine-learning algorithms, is paving the way for objective and comprehensive evaluations of spinal movements that can guide both research and clinical practice.Literature Search: PubMed, Web of Science and EMBASE, all articles prior to 9 April 2025.
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