This paper presents a system with real-time classification of human movements based on smartphone mounted on the waist. The built-in tri-accelerometer was utilized to collect the information of body motion. At the sam...This paper presents a system with real-time classification of human movements based on smartphone mounted on the waist. The built-in tri-accelerometer was utilized to collect the information of body motion. At the same time, the smartphone is able to classify the data for activity recognition. By our algorithm, body motion can be classified into five different patterns: vertical activity, lying, sitting or static standing, horizontal activity and fall. It alarms falling by Multimedia Messaging Service (MMS) with map of suspected fall location, GPS coordinate and time etc. If a fall was suspected, an automatic MMS would be sent to preset people. The major advantage of the proposed system is the novel application of smartphone which already have the necessary sensors and can monitor fall ubiquitously without any additional devices.展开更多
文摘This paper presents a system with real-time classification of human movements based on smartphone mounted on the waist. The built-in tri-accelerometer was utilized to collect the information of body motion. At the same time, the smartphone is able to classify the data for activity recognition. By our algorithm, body motion can be classified into five different patterns: vertical activity, lying, sitting or static standing, horizontal activity and fall. It alarms falling by Multimedia Messaging Service (MMS) with map of suspected fall location, GPS coordinate and time etc. If a fall was suspected, an automatic MMS would be sent to preset people. The major advantage of the proposed system is the novel application of smartphone which already have the necessary sensors and can monitor fall ubiquitously without any additional devices.
