Objective: A patient's activity patterns can be informative about her/his health status. Traditionally, this type of information has been gathered using patient self-report. However, these subjective self-report data can suffer from bias, and the surveys can become burdensome to patients over long time periods. Smartphones offer a unique opportunity to address these challenges. The smartphone has built-in sensors that can be programmed to collect data objectively, unobtrusively, and continuously. Due to their widespread adoption, smartphones are also accessible to most of the population. A main challenge in smartphone-based activity recognition is in extracting information optimally from multiple sensors to identify different activities. Materials and Methods: We analyze data collected by two sensors in the phone, the accelerometer and gyroscope, which measure the phone's acceleration and angular velocity, respectively. We propose an extension to the "movelet method" that jointly incorporates both data types. We apply this proposed method to a dataset we collected and compare the joint-sensor results to those from using each sensor separately. Results: The findings show that the joint-sensor method reduces errors of the gyroscope-only method in distinguishing between standing and sitting. Also, the joint-sensor method reduces errors of the accelerometer-only method in classifying vigorous activities, such as walking, ascending stairs, and descending stairs. Conclusion: Across activities, for the given method, combining data from the two sensors performs as well as or better than using data from a single sensor. The method is transparent, personalized to the individual user, and requires less training data than competitor methods.
翻译:目标: 患者活动模式可以了解其健康状况。 传统上, 智能手机活动识别的主要挑战是如何从多个传感器中以最佳方式提取信息, 以辨别不同的活动。 材料和方法: 我们分析手机中两个传感器收集的数据, 即加速计和陀螺仪, 分别测量手机的加速度和角速。 我们建议扩展“ 移动方法 ”, 将两种数据类型合并。 我们将这一拟议方法用于我们所收集的数据集, 并将联合传感器的结果与分别使用两个传感器的结果进行比较。 结果: 发现, 联合传感器的递增和递增方法, 将数据递增方法作为比较方法, 将单个传感器的递增方法, 将单个传感器的递增方法, 将单个传感器的递增方法 降低数据的递增率, 将单个传感器的递增方法 降低 。