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. 2018 Jun 6;18(6):1851.
doi: 10.3390/s18061851.

Wearable Sensors Integrated with Internet of Things for Advancing eHealth Care

Jose-Luis Bayo-Monton  1 , Antonio Martinez-Millana  2 , Weisi Han  3 , Carlos Fernandez-Llatas  4   5 , Yan Sun  6 , Vicente Traver  7   8
Affiliations

Wearable Sensors Integrated with Internet of Things for Advancing eHealth Care

Jose-Luis Bayo-Monton et al. Sensors (Basel). .

Abstract

Health and sociological indicators alert that life expectancy is increasing, hence so are the years that patients have to live with chronic diseases and co-morbidities. With the advancement in ICT, new tools and paradigms are been explored to provide effective and efficient health care. Telemedicine and health sensors stand as indispensable tools for promoting patient engagement, self-management of diseases and assist doctors to remotely follow up patients. In this paper, we evaluate a rapid prototyping solution for information merging based on five health sensors and two low-cost ubiquitous computing components: Arduino and Raspberry Pi. Our study, which is entirely described with the purpose of reproducibility, aimed to evaluate the extent to which portable technologies are capable of integrating wearable sensors by comparing two deployment scenarios: Raspberry Pi 3 and Personal Computer. The integration is implemented using a choreography engine to transmit data from sensors to a display unit using web services and a simple communication protocol with two modes of data retrieval. Performance of the two set-ups is compared by means of the latency in the wearable data transmission and data loss. PC has a delay of 0.051 ± 0.0035 s (max = 0.2504 s), whereas the Raspberry Pi yields a delay of 0.0175 ± 0.149 s (max = 0.294 s) for N = 300. Our analysis confirms that portable devices ( p < < 0 . 01 ) are suitable to support the transmission and analysis of biometric signals into scalable telemedicine systems.

Keywords: IoT; Telemedicine; eHealth; integration; monitoring; services; wearable.

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Conflict of interest statement

The authors declare no conflict of interest. The founding sponsors had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, and in the decision to publish the results.

Figures

Figure 1
Figure 1
eHealth shield input/output pins [26].
Figure 2
Figure 2
Choreography integration.
Figure 3
Figure 3
System architecture including health wearable sensors.
Figure 4
Figure 4
Passive mode.
Figure 5
Figure 5
Active mode.
Figure 6
Figure 6
Choreographer track service.
Figure 7
Figure 7
Services for hosting and serving the webpage. The schema shows how the Choreographer is connected to the sensors through the Arduino module and the needed libraries to self host and serve the webpage, which is based on HTML5 + Java Script + CSS.
Figure 8
Figure 8
Sensor deployment.
Figure 9
Figure 9
Comparison of the delay in the communications for the system deployed on a desktop computer and a Raspberry Pi for the segment between the Arduino and the Choreographer for the active communication mode.
Figure 10
Figure 10
Comparison of the delay in the communications for the system deployed on a desktop computer and a Raspberry Pi for the segment between the Choreographer and the webpage with the active communication mode.
See this image and copyright information in PMC

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