Leroux Andrew, Rzasa-Lynn Rachael, Crainiceanu Ciprian, Sharma Tushar
Department of Biostatistics and Informatics, Colorado School of Public Health, Aurora, Colorado, USA.
Department of Anesthesiology, University of Colorado, Aurora, Colorado, USA.
Digit Biomark. 2021 Apr 19;5(1):89-102. doi: 10.1159/000515576. eCollection 2021 Jan-Apr.
We investigated the possibilities and opportunities for using wearable devices that measure physical activity and physiometric signals in conjunction with ecological momentary assessment (EMA) data to improve the assessment and treatment of pain.
We considered studies with cross-sectional and longitudinal designs as well as interventional or observational studies correlating pain scores with measures derived from wearable devices. A search was also performed on studies that investigated physical activity and physiometric signals among patients with pain.
Few studies have assessed the possibility of incorporating wearable devices as objective tools for contextualizing pain and physical function in free-living environments. Of the studies that have been conducted, most focus solely on physical activity and functional outcomes as measured by a wearable accelerometer. Several studies report promising correlations between pain scores and signals derived from wearable devices, objectively measured physical activity, and physical function. In addition, there is a known association between physiologic signals that can be measured by wearable devices and pain, though studies using wearable devices to measure these signals and associate them with pain in free-living environments are limited.
There exists a great opportunity to study the complex interplay between physiometric signals, physical function, and pain in a real-time fashion in free-living environments. The literature supports the hypothesis that wearable devices can be used to develop reproducible biosignals that correlate with pain. The combination of wearable devices and EMA will likely lead to the development of clinically meaningful endpoints that will transform how we understand and treat pain patients.
我们研究了结合生态瞬时评估(EMA)数据使用可穿戴设备来测量身体活动和生理信号,以改善疼痛评估和治疗的可能性与机会。
我们考虑了采用横断面和纵向设计的研究,以及将疼痛评分与可穿戴设备得出的测量结果相关联的干预性或观察性研究。还对调查疼痛患者身体活动和生理信号的研究进行了检索。
很少有研究评估在自由生活环境中将可穿戴设备作为客观工具来描述疼痛和身体功能的可能性。在已开展的研究中,大多数仅关注可穿戴加速度计测量的身体活动和功能结果。几项研究报告了疼痛评分与可穿戴设备得出的信号、客观测量的身体活动及身体功能之间有前景的相关性。此外,可穿戴设备能够测量的生理信号与疼痛之间存在已知关联,不过在自由生活环境中使用可穿戴设备测量这些信号并将其与疼痛相关联的研究有限。
在自由生活环境中以实时方式研究生理信号、身体功能和疼痛之间的复杂相互作用存在巨大机会。文献支持可穿戴设备可用于开发与疼痛相关的可重复生物信号这一假设。可穿戴设备与EMA相结合可能会导致产生具有临床意义的终点指标,这将改变我们理解和治疗疼痛患者的方式。