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Social data shoes for gait monitoring of elderly people in smart home

机译:用于智能家居中老年人步态监测的社交数据鞋

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Gait monitoring technology has recently become of increasing interest in the biometric as well as biomedical fields for observation of the human movement, especially walking that can refer to physical status of individuals. For this objective, data shoes own many advantages such as cheaper cost and rich of direct information from the walking. In this paper, we have developed a data shoe system for gait monitoring in home area. To observe gait behaviors, the sensor suite includes five force sensitive resistors (FSRs) which were installed on the insole of the shoe. Zigbee wireless communication technology was used as low-cost data transfer between the sensor suite and the receiver system which is USB-connected to a computer. The summary of the gait data can be submitted and displayed on social media such as Facebook in order that relatives or care-takers can monitor the wearer closely. Principal component analysis (PCA) pattern recognition of the experimental data has shown that this system can classify normal and abnormal walking patterns in a group of elderly volunteers. The integration of sensors, wireless technology and social ability with computer software could make the social data shoe system monitor the gait behaviors during the wearing time.
机译:步态监测技术最近在生物特征学以及用于观察人类运动的生物医学领域中越来越引起人们的兴趣,尤其是可以指个人身体状况的步行。为了这个目标,数据鞋具有许多优点,例如价格便宜和来自步行的直接信息丰富。在本文中,我们开发了一种用于在家庭区域进行步态监视的数据鞋系统。为了观察步态行为,传感器套件包括五个力感应电阻器(FSR),这些电阻器安装在鞋子的鞋垫上。 Zigbee无线通信技术被用作传感器套件和通过USB连接到计算机的接收器系统之间的低成本数据传输。步态数据的摘要可以提交并显示在诸如Facebook之类的社交媒体上,以便亲戚或看护者可以密切监视穿戴者。实验数据的主成分分析(PCA)模式识别表明,该系统可以对一组老年志愿者的正常和异常步行模式进行分类。传感器,无线技术和社交能力与计算机软件的集成可以使社交数据鞋系统在穿戴期间监控步态行为。

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