Straczkiewicz Marcin, Burke Katherine M, Calcagno Narghes, Premasiri Alan, Vieira Fernando G, Onnela Jukka-Pekka, Berry James D
Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
Neurological Clinical Research Institute and Sean M. Healey & AMG Center for ALS, Boston, MA, USA.
J Neuroeng Rehabil. 2024 Dec 21;21(1):223. doi: 10.1186/s12984-024-01514-7.
Wearable technology offers objective and remote quantification of disease progression in neurological diseases such as amyotrophic lateral sclerosis (ALS). Large population studies are needed to determine generalization and reproducibility of findings from pilot studies.
A large cohort of patients with ALS (N = 202) wore wearable accelerometers on their dominant and non-dominant wrists for a week every two to four weeks and self-entered the ALS Functional Rating Scale-Revised (ALSFRS-RSE) in similar time intervals. Wearable device data were processed to quantify digital biomarkers on four upper limb movements: flexion, extension, supination, and pronation using previously developed and validated open-source methodology. In this study, we determined the association between digital biomarkers and disease progression, studied the impact of study design in terms of required sensor wear-time and sensor position, and determined the impact of self-reported disease onset location on upper limb movements.
The main investigation considered data from a sensor placed on the non-dominant wrist. Participants with higher ALSFRS-RSE scores performed more frequent and faster upper limb movements compared to participants with more advanced disease status. Digital biomarkers exhibited statistically significant change over time while their rate of change was more profound compared to survey responses. Using data from the dominant wrist and changing data inclusion criteria did not alter our findings. ALS disease onset location significantly impacted use of upper limbs. Results presented here were comparable to an earlier study on twenty patients with ALS.
Digital health technologies provide sensitive and objective means to quantify ALS disease progression. Interpretable approaches, such as the one used in this paper, can improve patient evaluation and hasten therapeutic development.
可穿戴技术能够对诸如肌萎缩侧索硬化症（ALS）等神经疾病的疾病进展进行客观且远程的量化。需要开展大规模人群研究来确定初步研究结果的普遍性和可重复性。
一大群ALS患者（N = 202）每两到四周在其优势手腕和非优势手腕上佩戴可穿戴加速度计一周，并在相似的时间间隔内自行录入修订版ALS功能评定量表（ALSFRS-RSE）。使用先前开发并经验证的开源方法对可穿戴设备数据进行处理，以量化四种上肢运动（屈曲、伸展、旋后和旋前）的数字生物标志物。在本研究中，我们确定了数字生物标志物与疾病进展之间的关联，研究了研究设计在所需传感器佩戴时间和传感器位置方面的影响，并确定了自我报告的疾病发病部位对上肢运动的影响。
主要调查考虑了来自放置在非优势手腕上的传感器的数据。与疾病状态更严重的参与者相比，ALSFRS-RSE得分较高的参与者进行上肢运动的频率更高且速度更快。数字生物标志物随时间呈现出具有统计学意义的变化，而其变化率与调查反应相比更为显著。使用来自优势手腕的数据并改变数据纳入标准并未改变我们的研究结果。ALS疾病发病部位对上肢的使用有显著影响。此处呈现的结果与早期一项针对20名ALS患者的研究结果相当。
数字健康技术提供了敏感且客观的手段来量化ALS疾病进展。可解释的方法，如本文中使用的方法，可以改善患者评估并加速治疗开发。
