Physiological Informatics: Collection and Analyses of Data from Wearable Sensors and Smartphone for Healthcare

  • Jinwei Bai
  • Li Shen
  • Huimin Sun
  • Bairong ShenEmail author
Part of the Advances in Experimental Medicine and Biology book series (AEMB, volume 1028)


Physiological data from wearable sensors and smartphone are accumulating rapidly, and this provides us the chance to collect dynamic and personalized information as phenotype to be integrated to genotype for the holistic understanding of complex diseases. This integration can be applied to early prediction and prevention of disease, therefore promoting the shifting of disease care tradition to the healthcare paradigm. In this chapter, we summarize the physiological signals which can be detected by wearable sensors, the sharing of the physiological big data, and the mining methods for the discovery of disease-associated patterns for personalized diagnosis and treatment. We discuss the challenges of physiological informatics about the storage, the standardization, the analyses, and the applications of the physiological data from the wearable sensors and smartphone. At last, we present our perspectives on the models for disentangling the complex relationship between early disease prediction and the mining of physiological phenotype data.


Wearable sensors Smartphone Physiological informatics Participatory medicine Data mining for healthcare 



This study was supported by the National Natural Science Foundation of China (NSFC) (grant nos. 31670851, 31470821, and 91530320) and National Key R&D programs of China (2016YFC1306605).


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© Springer Nature Singapore Pte Ltd. 2017

Authors and Affiliations

  1. 1.Digital Department of LibrarySoochow UniversitySuzhouChina
  2. 2.Center for Systems BiologySoochow UniversitySuzhouChina
  3. 3.Collaborative Innovation Center of Sustainable Forestry in Southern China of Jiangsu ProvinceNanjing Forestry UniversityNanjingChina

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