Division of Biokinesiology and Physical Therapy, Herman Ostrow School of Dentistry, University of Southern California, Los Angeles, CA 90033, USA.
Children's Hospital Los Angeles, Los Angeles, CA 90027, USA.
Sensors (Basel). 2020 Sep 18;20(18):5344. doi: 10.3390/s20185344.
Movement characteristics can differentiate between infants at risk and infants with typical development. However, it is unknown how many days are needed to accurately represent typical daily behavior for infants at risk of developmental disabilities when using wearable sensors. To consider the balance between participant burden and the amount of data collected and optimizing the efficiency of data collection, our study determined (1) how many days were necessary to represent typical movement behavior for infants at risk of developmental disabilities and (2) whether movement behavior was different on weekend days and weekdays.
We used Opal wearable sensors to collect at least 5 days of 11 infants' leg movement data. The standard (average of 5 days) was compared with four methods (average of the first 1/2/3/4 days) using the Bland-Altman plots and the Spearman correlation coefficient. We also compared the data from the average of 2 weekend days to the average of the first 2 weekdays for 8 infants.
The Spearman correlation coefficient comparing the average of the first 2 days of data and the standards were all above 0.7. The absolute differences between them were all below 10% of the standards. The Bland-Altman plots showed more than 90% of the data points comparing the average of 2 days and the standards fell into the limit of agreement for each variable. The absolute difference between weekend days and weekdays for the leg movement rate, duration, average acceleration, and peak acceleration was 15.2%, 1.7%, 6.8% and 6.3% of the corresponding standard, respectively.
Our results suggest 2 days is the optimal amount of data to represent typical daily leg movement behavior of infants at risk of developmental disabilities while minimizing participant burden. Further, leg movement behavior did not differ distinctly across weekend days and weekdays. These results provide supportive evidence for an efficient amount of data collections when using wearable sensors to evaluate movement behavior in infants at risk of developmental disabilities.
运动特征可区分有发育障碍风险的婴儿和发育正常的婴儿。然而,目前尚不清楚使用可穿戴传感器时,需要多少天才能准确代表有发育障碍风险的婴儿的典型日常行为。为了在参与者负担和收集的数据量之间取得平衡,并优化数据收集效率,我们的研究确定了:(1)需要多少天才能代表有发育障碍风险的婴儿的典型运动行为;(2)运动行为在周末和工作日是否不同。
我们使用 Opal 可穿戴传感器收集了至少 11 名婴儿腿部运动数据的 5 天数据。使用 Bland-Altman 图和 Spearman 相关系数,将标准(5 天的平均值)与四种方法(前 1/2/3/4 天的平均值)进行了比较。我们还比较了 8 名婴儿中 2 个周末日的平均值与前 2 个工作日的平均值。
比较前 2 天数据的平均值与标准的 Spearman 相关系数均高于 0.7。两者之间的绝对差异均低于标准的 10%。Bland-Altman 图显示,比较前 2 天的平均值与标准的 90%以上数据点都落入了每个变量的一致性界限内。腿部运动速度、持续时间、平均加速度和峰值加速度的周末日与工作日之间的绝对差异分别为标准值的 15.2%、1.7%、6.8%和 6.3%。
我们的结果表明,2 天是代表有发育障碍风险的婴儿典型日常腿部运动行为的最佳数据量,可以最大限度地减少参与者的负担。此外,腿部运动行为在周末日和工作日之间没有明显差异。这些结果为使用可穿戴传感器评估有发育障碍风险的婴儿的运动行为时,提供了高效的数据采集量的支持证据。