| In recent years, with the development of society, human daily activities based on sensor data collection and analysis on a wide range of development, and study of human activities based on sensor data has been vigorously developed. With the development of computers and sensors, the capacity of processingdata for computer is becoming more and more powerful. Sensors can also be installed embedded in mobile phones, watches and other equipment, it also makes the sensor quietlyentering into people’s lives. The research on mobile computing, health and safety monitoring, and environmental detection, andother fields has great potential research value.People sleep time is very long,it takes up about a third of the time of life. In this for a long time, Sleep quality has been particularly concerned about a topic of many people. Some people sleep well, even if sleeptime is less then they feel particularly high spirits; and sleep quality ofsome people is not ideal, they delays in entering deep sleep, and sleep time is longer then they feel exhausted.Specifically, this article will research for sensor and sensor data from the following three aspects :(1) The recognition of human daily activities. Collecting six kind of daily activities through the sensors,thenprocessing raw data to obtainedcharacteristics data, the characteristics of the data is divided into training data and test data sets, finally using support vector machine(SVM) classification method to classify.(2) The Effects of the Physical activityon sleep. In this article, we gather the data of movement during the day and the data of sleep in the evening through the device with sensors, then extract exercise and sleep features, and analyze the impact of exercise on sleep and forecast.(3) The influence of the single movement for sleep. Based on the device,collection daily movement and sleep data, and extract the feature data, then analysis of the effect of the specific movement to sleep and prediction. |
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