Literature DB >> 25192566

Logic-centered architecture for ubiquitous health monitoring.

Jacek Lewandowski, Hisbel E Arochena, Raouf N G Naguib, Kuo-Ming Chao, Alexeis Garcia-Perez.   

Abstract

One of the key points to maintain and boost research and development in the area of smart wearable systems (SWS) is the development of integrated architectures for intelligent services, as well as wearable systems and devices for health and wellness management. This paper presents such a generic architecture for multiparametric, intelligent and ubiquitous wireless sensing platforms. It is a transparent, smartphone-based sensing framework with customizable wireless interfaces and plug'n'play capability to easily interconnect third party sensor devices. It caters to wireless body, personal, and near-me area networks. A pivotal part of the platform is the integrated inference engine/runtime environment that allows the mobile device to serve as a user-adaptable personal health assistant. The novelty of this system lays in a rapid visual development and remote deployment model. The complementary visual Inference Engine Editor that comes with the package enables artificial intelligence specialists, alongside with medical experts, to build data processing models by assembling different components and instantly deploying them (remotely) on patient mobile devices. In this paper, the new logic-centered software architecture for ubiquitous health monitoring applications is described, followed by a discussion as to how it helps to shift focus from software and hardware development, to medical and health process-centered design of new SWS applications.

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Year:  2014        PMID: 25192566     DOI: 10.1109/JBHI.2014.2312352

Source DB:  PubMed          Journal:  IEEE J Biomed Health Inform        ISSN: 2168-2194            Impact factor:   5.772


  3 in total

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Authors:  Ayyasamy Ayyanar; Maruthavanan Archana; Y Harold Robinson; E Golden Julie; Raghvendra Kumar; Le Hoang Son
Journal:  Med Biol Eng Comput       Date:  2019-08-29       Impact factor: 2.602

2.  An acute stroke evaluation app: a practice improvement project.

Authors:  Mark N Rubin; Jennifer E Fugate; Kevin M Barrett; Alejandro A Rabinstein; Kelly D Flemming
Journal:  Neurohospitalist       Date:  2015-04

3.  Bone metabolic biomarker-based diagnosis of type 2 diabetes osteoporosis by support vector machine.

Authors:  Chuan Wang; Taomin Zhang; Peng Wang; Xuan Liu; Liming Zheng; Lei Miao; Deyu Zhou; Yibo Zhang; Yezi Hu; Han Yin; Qing Jiang; Hui Jin; Jianfei Sun
Journal:  Ann Transl Med       Date:  2021-02
  3 in total

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