TY - JOUR AU - Boateng, George AU - Petersen, Curtis L AU - Kotz, David AU - Fortuna, Karen L AU - Masutani, Rebecca AU - Batsis, John A PY - 2022 DA - 2022/8/10 TI -老年人智能手表计步应用程序:开发和评估研究乔——JMIR老化SP - e33845六世- 5 - 3 KW -一步跟踪KW -步骤数千瓦计步器KW -可穿戴KW - smartwatch KW -老年人KW -身体活动KW -机器学习KW -走KW - mHealth KW -移动健康KW -移动应用KW -移动应用KW - app KW - uHealth AB -背景:老年人参与体育活动可以减少流动障碍和残疾的风险。短时间的步行可以改善生活质量、身体功能和心血管健康。为了鼓励老年人参加体育活动，已经实施了各种各样的项目，但保持他们的积极性仍然是一个挑战。手机和智能手表等无处不在的设备，再加上机器学习算法，可能会鼓励老年人更多地锻炼身体。目前部署在消费设备(如Fitbit)中的算法是专有的，通常不适合老年人的运动，并且已被证明在临床环境中不准确。已经为智能手表开发了计算步数的算法，但只使用来自年轻人的数据，而且通常只在受控的实验室环境中进行了验证。目的:我们试图为老年人开发和验证一款智能手表计步应用程序，并在自由生活环境中长期评估该算法。方法:我们在开源腕戴设备(Amulet)上开发并评估了一款老年人计算步数的应用程序。这款应用程序包括推算身体活动水平和计算步数的算法。 We validated the step-counting algorithm in the lab (counting steps from a video recording, n=20) and in free-living conditions—one 2-day field study (n=6) and two 12-week field studies (using the Fitbit as ground truth, n=16). During app system development, we evaluated 4 walking patterns: normal, fast, up and down a staircase, and intermittent speed. For the field studies, we evaluated 5 different cut-off values for the algorithm, using correlation and error rate as the evaluation metrics. Results: The step-counting algorithm performed well. In the lab study, for normal walking (R2=0.5), there was a stronger correlation between the Amulet steps and the video-validated steps; for all activities, the Amulet’s count was on average 3.2 (2.1%) steps lower (SD 25.9) than the video-validated count. For the 2-day field study, the best parameter settings led to an association between Amulet and Fitbit (R2=0.989) and 3.1% (SD 25.1) steps lower than Fitbit, respectively. For the 12-week field study, the best parameter setting led to an R2 value of 0.669. Conclusions: Our findings demonstrate the importance of an iterative process in algorithm development before field-based deployment. This work highlights various challenges and insights involved in developing and validating monitoring systems in real-world settings. Nonetheless, our step-counting app for older adults had good performance relative to the ground truth (a commercial Fitbit step counter). Our app could potentially be used to help improve physical activity among older adults. SN - 2561-7605 UR - https://aging.www.mybigtv.com/2022/3/e33845 UR - https://doi.org/10.2196/33845 UR - http://www.ncbi.nlm.nih.gov/pubmed/35947445 DO - 10.2196/33845 ID - info:doi/10.2196/33845 ER -