Smart Clothing: Connecting Human with Clouds and Big Data for Sustainable Health Monitoring

Abstract

Traditional wearable devices have various shortcomings, such as uncomfortableness for long-term wearing, and insufficient accuracy, etc. Thus, health monitoring through traditional wearable devices is hard to be sustainable. In order to obtain healthcare big data by sustainable health monitoring, we design “Smart Clothing”, facilitating unobtrusive collection of various physiological indicators of human body. To provide pervasive intelligence for smart clothing system, mobile healthcare cloud platform is constructed by the use of mobile internet, cloud computing and big data analytics. This paper introduces design details, key technologies and practical implementation methods of smart clothing system. Typical applications powered by smart clothing and big data clouds are presented, such as medical emergency response, emotion care, disease diagnosis, and real-time tactile interaction. Especially, electrocardiograph signals collected by smart clothing are used for mood monitoring and emotion detection. Finally, we highlight some of the design challenges and open issues that still need to be addressed to make smart clothing ubiquitous for a wide range of applications.

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Acknowledgements

This work is supported by the National Basic Research Program of China (973 Program) (no. 2014CB744600), and the National Natural Science Foundation of China (no. 61572220). Thank Yixue Hao, Long Hu, Xiaobo Shi, Yongfeng Qian, Jun Yang, Ping Zhou, Wei Li, Yiming Miao, Lu Wang, Hang Ruan, Tong Han, Chuanbei Wu, Binjie Shi, Mengchen Liu, Chao Han, Zeru Wei, Yi Xu and Jiayi Lu to contribute in various aspects for building EPIC Smart Clothing testbed.

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Correspondence to Jeungeun Song.

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Chen, M., Ma, Y., Song, J. et al. Smart Clothing: Connecting Human with Clouds and Big Data for Sustainable Health Monitoring. Mobile Netw Appl 21, 825–845 (2016). https://doi.org/10.1007/s11036-016-0745-1

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Keywords

  • Smart clothing
  • Health monitoring
  • Wearable computing
  • Cloud computing
  • Big data