Department of Trauma and Reconstructive Surgery, Eberhard-Karls-University Tuebingen, BG Unfallklinik, 72076 Tuebingen, Germany.
Human Motion, Orthopaedics, Sports Medicine and Digital Methods Group, Department Precision Health, Luxembourg Institute of Health, 1445 Luxembourg, Luxembourg.
Medicina (Kaunas). 2023 Feb 19;59(2):403. doi: 10.3390/medicina59020403.
: Outcome data from wearable devices are increasingly used in both research and clinics. Traditionally, a dedicated device is chosen for a given study or clinical application to collect outcome data as soon as the patient is included in a study or undergoes a procedure. The current study introduces a new measurement strategy, whereby patients' own devices are utilized, allowing for both a pre-injury baseline measure and ability to show achievable results. : Patients with a pre-existing musculoskeletal injury of the upper and lower extremity were included in this exploratory, proof-of-concept study. They were followed up for a minimum of 6 weeks after injury, and their wearable outcome data (from a smartphone and/or a body-worn sensor) were continuously acquired during this period. A descriptive analysis of the screening characteristics and the observed and achievable outcome patterns was performed. : A total of 432 patients was continuously screened for the study, and their screening was analyzed. The highest success rate for successful inclusion was in younger patients. Forty-eight patients were included in the analysis. The most prevalent outcome was step count. Three distinctive activity data patterns were observed: patients recovering, patients with slow or no recovery, and patients needing additional measures to determine treatment outcomes. : Measuring outcomes in trauma patients with the Bring Your Own Device (BYOD) strategy is feasible. With this approach, patients were able to provide continuous activity data without any dedicated equipment given to them. The measurement technique is especially suited to particular patient groups. Our study's screening log and inclusion characteristics can help inform future studies wishing to employ the BYOD design.
可穿戴设备的结果数据在研究和临床中越来越多地被使用。传统上，会为特定的研究或临床应用选择专用设备来收集结果数据，只要患者被纳入研究或接受治疗程序。本研究引入了一种新的测量策略，即利用患者自己的设备，既能进行受伤前的基线测量，也能展示可实现的结果。
本探索性、概念验证研究纳入了上肢和下肢有预先存在的肌肉骨骼损伤的患者。他们在受伤后至少随访 6 周，在此期间持续获取可穿戴的结果数据（来自智能手机和/或身体佩戴式传感器）。对筛选特征和观察到的和可实现的结果模式进行了描述性分析。
共有 432 名患者被连续筛选入组进行研究，并对其筛选进行了分析。年轻患者的入组成功率最高。有 48 名患者纳入分析。最常见的结果是步数。观察到三种不同的活动数据模式：恢复中的患者、恢复缓慢或无恢复的患者，以及需要额外措施来确定治疗结果的患者。
使用自带设备（Bring Your Own Device，BYOD）策略来测量创伤患者的结果是可行的。通过这种方法，患者可以提供连续的活动数据，而无需提供专用设备。这种测量技术尤其适合特定的患者群体。我们的研究筛选日志和纳入特征可以为希望采用 BYOD 设计的未来研究提供信息。
