Performing jump exercise can maintain a healthy lymphatic system, which keeps human body in an optimal condition and is a critical component of human immune system. Accurate jump detection and count are crucial to patients with a dysfunctional lymph system. In this article, we present a continuous jump detection framework on smartphones, SmartJump, for human jump detection and count, by leveraging the accelerometer and magnetometer ubiquitously built into smartphones. Specifically, SmartJump collects sensing data from the accelerometer and magnetometer, and processes these data through coordinate system translation and data smoothing filter. Then, jump features are extracted based on the smoothed z-axis acceleration data using the peak and valley detection algorithm and then are matched with the concluded three features from the analysis of physical jumps using a finite state machine for jump detection and count. We implement SmartJump on Samsung S6 Edge smartphones and recruit six subjects for data collection. We evaluate the accuracy of SmartJump in terms of five-fold cross-validation test, self-test, and leave-one-out cross-validation test, and the experimental results indicate that SmartJump achieves an average of 96.4 % recall, 97.2 % precision, and 96.8 % F1 score in five different scenarios.

中文翻译：

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SmartJump：智能手机上的连续跳跃检测框架

进行跳跃运动可以维持健康的淋巴系统，使人体保持最佳状态，是人体免疫系统的重要组成部分。准确的跳跃检测和计数对于淋巴系统功能障碍的患者至关重要。在本文中，我们通过利用智能手机中无处不在的加速度计和磁力计，展示了智能手机上的连续跳跃检测框架 SmartJump，用于人体跳跃检测和计数。具体来说，SmartJump 从加速度计和磁力计收集传感数据，并通过坐标系转换和数据平滑滤波器处理这些数据。然后，使用峰谷检测算法基于平滑的 z 轴加速度数据提取跳跃特征，然后与使用有限状态机进行跳跃检测和计数的物理跳跃分析得出的三个特征进行匹配。我们在三星 S6 Edge 智能手机上实施 SmartJump 并招募六个对象进行数据收集。我们通过五重交叉验证测试、自测和留一法交叉验证测试来评估 SmartJump 的准确率，实验结果表明 SmartJump 平均达到了 96.4% 的召回率，97.2% 的准确率和 96.8 % F1 分数在五种不同的情况下。