Mueller Arne, Hoefling Holger, Nuritdinow Timur, Holway Nicholas, Schieker Matthias, Daumer Martin, Clay Ieuan
Translational Medicine, Novartis Institutes for Biomedical Research, Forum 1, Novartis Campus, Basel, Switzerland.
NIBR Informatics, Novartis Institutes for Biomedical Research, Forum 1, Novartis Campus, Basel, Switzerland.
Digit Biomark. 2018 Aug 2;2(2):79-89. doi: 10.1159/000490919. eCollection 2018 May-Aug.
Continuous patient activity monitoring during rehabilitation, enabled by digital technologies, will allow the objective capture of real-world mobility and aligning treatment to each individual's recovery trajectory in real time. To explore the feasibility and added value of such approaches, we present a case study of a 36-year-old male participant monitored continuously for activity levels and gait parameters using a waist-worn inertial sensor following a tibial plateau fracture on the right side, sustained as a result of a high-energy trauma during a sporting accident. During rehabilitation, data were collected for a period of 553 days, with > 80% daytime compliance, until the participant returned to near full mobility. The participant completed a daily diary with the annotation of major events (falls, near falls, cycling periods, or physiotherapy sessions) and key dates in the patient's recovery, including medical interventions, transitioning off crutches, and returning to work. We demonstrate the feasibility of collecting, storing, and mining of continuous digital mobility data and show that such data can detect changes in mobility and provide insights into long-term rehabilitation. We make both raw data and annotations available as a resource with the aspiration that further methods and insights will be built on this initial exploration of added value and continue to demonstrate that continuous monitoring can be deployed to aid rehabilitation.
通过数字技术实现的康复期间患者活动连续监测，将能够客观捕捉现实世界中的活动能力，并实时根据每个个体的恢复轨迹调整治疗方案。为探索此类方法的可行性和附加价值，我们展示了一个案例研究，对象是一名36岁男性参与者，其在一次体育事故中因高能创伤导致右侧胫骨平台骨折后，使用腰部佩戴的惯性传感器对其活动水平和步态参数进行连续监测。在康复期间，持续收集了553天的数据，日间依从率超过80%，直至参与者恢复到接近完全活动能力。参与者完成了一本日记，记录了重大事件（跌倒、险些跌倒、骑行时段或物理治疗课程）以及患者恢复过程中的关键日期，包括医疗干预、停用拐杖和重返工作岗位。我们证明了收集、存储和挖掘连续数字活动数据的可行性，并表明此类数据能够检测活动能力的变化，并为长期康复提供见解。我们将原始数据和注释作为一种资源提供，期望在此对附加价值的初步探索基础上构建更多方法和见解，并继续证明连续监测可用于辅助康复。
