An Activity Recognition System For Mobile Phones
An Activity Recognition System For Mobile Phones
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DOI：
10.1007/s11036-008-0112-y
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发表时间：
2009-02-01
影响因子：
3.8
通讯作者：
Homanyi, Gergely
中科院分区：
文献类型：
--
作者：
Gyorbiro, Norbert;Fabian, Akos;Homanyi, Gergely
我们提出了一个新的系统，识别和记录的运动活动的人使用移动的电话。测量运动强度的无线传感器附着在用户的身体部位。感官数据由一个移动的应用程序收集，该应用程序可以实时识别预先学习的活动。为了有效地识别手势和姿势的运动模式，采用前馈反向传播神经网络。沿着介绍了该系统的设计和实现，并记录了我们的工作经验。结果表明，高识别率区分六种不同的运动模式。所识别的活动可以用作广泛的移动的存储器记录和共享项目中的附加检索密钥。提供无线通信的功耗测量和识别算法以表征系统的资源需求。
We present a novel system that recognizes and records the motional activities of a person using a mobile phone. Wireless sensors measuring the intensity of motions are attached to body parts of the user. Sensory data is collected by a mobile application that recognizes prelearnt activities in real-time. For efficient motion pattern recognition of gestures and postures, feed-forward backpropagation neural networks are adopted. The design and implementation of the system are presented along with the records of our experiences. Results show high recognition rates for distinguishing among six different motion patterns. The recognized activity can be used as an additional retrieval key in an extensive mobile memory recording and sharing project. Power consumption measurements of the wireless communication and the recognition algorithm are provided to characterize the resource requirements of the system.