论文标题
将帕金森氏病的复杂双面智能手表检查减少到有效的单面检查机器学习精度
Reducing a complex two-sided smartwatch examination for Parkinson's Disease to an efficient one-sided examination preserving machine learning accuracy
论文作者
论文摘要
近年来，来自智能消费者设备的传感器在鉴定运动障碍中充当数字生物标志物具有很高的潜力。通过使用广泛可用的智能手表，我们记录了参与者在研究帕金森氏病（PD）的一项前瞻性研究中进行基于技术的评估。总共有504名参与者，包括PD患者，鉴别诊断（DD）和健康对照组（HC），使用了两个智能手表和两台智能手机的全面系统捕获。据我们所知，这项研究提供了最大的双手同步智能手表测量值的PD样本量。为了在PD筛选中建立未来易于使用的家庭评估系统，我们根据仅采用单方面措施大大减少的评估集并进行了评估，系统地评估了系统的性能。
Sensors from smart consumer devices have demonstrated high potential to serve as digital biomarkers in the identification of movement disorders in recent years. With the usage of broadly available smartwatches we have recorded participants performing technology-based assessments in a prospective study to research Parkinson's Disease (PD). In total, 504 participants, including PD patients, differential diagnoses (DD) and healthy controls (HC), were captured with a comprehensive system utilizing two smartwatches and two smartphones. To the best of our knowledge, this study provided the largest PD sample size of two-hand synchronous smartwatch measurements. To establish a future easy-to use home-based assessment system in PD screening, we systematically evaluated the performance of the system based on a significantly reduced set of assessments with only one-sided measures and assessed, whether we can maintain classification accuracy.
