Department of Mechanical Engineering, Brigham Young University, Provo, UT, United States.
Department of Exercise Sciences, Brigham Young University, Provo, UT, United States.
Pain Med. 2023 Aug 4;24(Suppl 1):S160-S174. doi: 10.1093/pm/pnad017.
Chronic low back pain (cLBP) is a prevalent and multifactorial ailment. No single treatment has been shown to dramatically improve outcomes for all cLBP patients, and current techniques of linking a patient with their most effective treatment lack validation. It has long been recognized that spinal pathology alters motion. Therefore, one potential method to identify optimal treatments is to evaluate patient movement patterns (ie, motion-based phenotypes). Biomechanists, physical therapists, and surgeons each utilize a variety of tools and techniques to qualitatively assess movement as a critical element in their treatment paradigms. However, objectively characterizing and communicating this information is challenging due to the lack of economical, objective, and accurate clinical tools. In response to that need, we have developed a wearable array of nanocomposite stretch sensors that accurately capture the lumbar spinal kinematics, the SPINE Sense System. Data collected from this device are used to identify movement-based phenotypes and analyze correlations between spinal kinematics and patient-reported outcomes. The purpose of this paper is twofold: first, to describe the design and validity of the SPINE Sense System; and second, to describe the protocol and data analysis toward the application of this equipment to enhance understanding of the relationship between spinal movement patterns and patient metrics, which will facilitate the identification of optimal treatment paradigms for cLBP.
慢性下背痛(cLBP)是一种普遍存在且多因素的疾病。没有单一的治疗方法被证明可以显著改善所有 cLBP 患者的结局,目前将患者与最有效的治疗方法联系起来的技术缺乏验证。人们早就认识到脊柱病理学改变运动。因此,一种潜在的方法是评估患者的运动模式(即基于运动的表型)来识别最佳治疗方法。生物力学专家、物理治疗师和外科医生都使用各种工具和技术来定性评估运动,因为运动是他们治疗模式中的关键因素。然而,由于缺乏经济、客观和准确的临床工具,客观地描述和传达这些信息具有挑战性。为了满足这一需求,我们开发了一种由纳米复合拉伸传感器组成的可穿戴阵列,该阵列可以准确地捕捉腰椎运动,即 SPINE Sense 系统。该设备收集的数据用于识别基于运动的表型,并分析脊柱运动与患者报告结果之间的相关性。本文的目的有两个:首先,描述 SPINE Sense 系统的设计和有效性;其次,描述应用该设备的方案和数据分析,以增强对脊柱运动模式与患者指标之间关系的理解,这将有助于确定 cLBP 的最佳治疗方案。