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Accurate position and orientation independent step counting algorithm for smartphones
Journal of Ambient Intelligence and Smart Environments ( IF 1.7 ) Pub Date : 2018-11-09 , DOI: 10.3233/ais-180503
Jungryul Seo 1 , Teemu H. Laine 2
Affiliation  

Step counting (SC) algorithms can be applied to different areas such as well-being applications, games, and indoor navigation. Many existing SC algorithms for smartphones use data from inertial sensors to infer the number of steps taken, but their usefulness in real-life situations is limited since typically only a few positions and orientations are supported. Moreover, the algorithms may suffer from dynamic orientation and position changes during walking. To alleviate these shortcomings, we propose the Position and Orientation Independent Step Counting Algorithm (POISCA), which uses an accelerometer and a gyroscope to count the number of steps while allowing the smartphone’s position and orientation to change dynamically. In a nutshell, the algorithm first determines the orientation of the smartphone, and then detects zero crossings with a predetermined buffer range. 48 young adults (36 males, 12 females) participated in an experiment that simulated a real-life scenario to evaluate the performance of POISCA against three other step counting algorithms. The data from 24 participants were randomly assigned to a training group, which was then used to establish threshold parameters for POISCA. The remaining 24 participants’ data were used for accuracy measurement. The results show that POISCA outperforms the other algorithms with a Symmetric Mean Absolute Percentage Error of 4.54%, which can be lower if the algorithm is calibrated for each user. The results suggest that POISCA has potential for use in real-life situations where changes in position and orientation of the smartphone are dynamic.

中文翻译:

智能手机的精确位置和方向无关的步数计算算法

步数(SC)算法可以应用于不同的领域,例如幸福感应用程序,游戏和室内导航。许多现有的用于智能手机的SC算法都使用惯性传感器的数据来推断所采取的步骤数,但由于通常仅支持少数几个位置和方向,因此它们在现实生活中的用处受到了限制。此外,算法可能会在步行过程中遭受动态方向和位置变化的困扰。为了缓解这些缺点,我们提出了位置和方向独立步数计数算法(POISCA),该算法使用加速计和陀螺仪对步数进行计数,同时允许智能手机的位置和方向动态变化。简而言之,该算法首先确定智能手机的方向,然后检测具有预定缓冲区范围的零交叉。48位年轻人(36位男性,12位女性)参加了一个模拟现实生活中的实验的实验,以评估POISCA与其他三个步骤计数算法的性能。来自24名参与者的数据被随机分配到一个训练组,然后用于建立POISCA的阈值参数。其余24名参与者的数据用于准确性测量。结果表明,POISCA的对称平均绝对百分比误差为4.54%,优于其他算法,如果为每个用户校准该算法,则误差可能会更低。结果表明,POISCA具有在智能手机的位置和方向动态变化的现实生活中使用的潜力。12位女性)参加了一个模拟现实生活场景的实验,以评估POISCA与其他三个步骤计数算法的性能。来自24名参与者的数据被随机分配到一个训练组,然后用于建立POISCA的阈值参数。其余24名参与者的数据用于准确性测量。结果表明,POISCA的对称平均绝对百分比误差为4.54%,优于其他算法,如果为每个用户校准该算法,则误差可能会更低。结果表明,POISCA具有在智能手机的位置和方向动态变化的现实生活中使用的潜力。12位女性)参加了一个模拟现实生活场景的实验,以评估POISCA与其他三个步骤计数算法的性能。来自24名参与者的数据被随机分配到一个训练组,然后用于建立POISCA的阈值参数。其余24名参与者的数据用于准确性测量。结果表明,POISCA的对称平均绝对百分比误差为4.54%,优于其他算法,如果为每个用户校准该算法,则误差可能会更低。结果表明,POISCA具有在智能手机的位置和方向动态变化的现实生活中使用的潜力。
更新日期:2018-11-09
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