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dc.contributor.authorRodríguez Rodríguez, Juan José
dc.contributor.authorCastillo García, Javier Ferney
dc.contributor.authorArgüello Prada, Erick Javier
dc.date.accessioned2020-10-23T15:36:48Z
dc.date.available2020-10-23T15:36:48Z
dc.date.issued2020-03-03
dc.identifier.isbn978-303042519-7
dc.identifier.issn1865-0929
dc.identifier.urihttp://repository.usc.edu.co/handle/20.500.12421/4504
dc.description.abstractAutomatic and remote monitoring of patients with pain may decrease treatment costs and improve the quality of care. In this sense, the Internet of Things (IoT) emerges as a suitable candidate for developing solutions enabling continuous and remote assessment of pain experience. However, only a few efforts have been devoted to adopting IoT-based solutions for pain assessment. In the present work, an IoT-based system for pain monitoring is proposed on the basis of a performance assessment of several communication protocols for IoT: TCP/IPv4, TCP/IPv6, UDP, MQTT, and HTTP. The peripheral blood flow and the skin’s ability to conduct electricity were chosen as the physiological parameters through which it is possible to measure pain. The capabilities of the aforementioned IoT communication protocols for transmitting the physiological data stream to a cloud server were evaluated by implementing each of those protocols and using the Wireshark protocol analyzer to compute the mean byte rate, the mean packet rate, the mean error value, and the network reliability for 1 h. Results show that the TCP/IPv4 and TCP/IPv6 protocols showed the highest packet transmission rate as well as the highest network reliability. Moreover, given the characteristics of the chosen physiological parameters, the proposed solution does not require a high transmission data rate, so there would be no limitation regarding the wireless communication protocol that could be used for implementing it. Nevertheless, a wider range of parameters needs to be considered in order to carry out a more rigorous performance assessment.en_US
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.subjectCloud serveren_US
dc.subjectInternet of Things (IoT)en_US
dc.subjectM-healthen_US
dc.subjectPain assessmenten_US
dc.subjectPhotoplethysmography (PPG)en_US
dc.titleToward Automatic and Remote Monitoring of the Pain Experience: An Internet of Things (IoT) Approachen_US
dc.typeArticleen_US


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