Authors:
Antonio J. Jara
;
Pablo López Martínez
;
David Fernández Ros
;
Benito Úbeda
;
Miguel A. Zamora
and
Antonio F. G. Skarmeta
Affiliation:
Faculty of Computer Sciences and University of Murcia, Spain
Keyword(s):
Internet of Things; Near Field Communications; m-health; Ambient Assisted Living; electrocardiogram; continuous monitoring.
Abstract:
Continuous and wireless transmission of vital signs is taking a high relevance in ubiquitous computing, ambient intelligence and Ambient Assisted Living (AAL). Integration of wireless communications technologies and embedded systems into health monitoring systems are tending towards solutions defined under the denominated Internet of Things (IoT). Specifically, IoT is based on technologies such as Radio Frequency Identification (RFID) to provide the capabilities for identification of devices/sensors, and the evolutions of RFID with Near Field Communication (NFC). NFC presents machine to machine (M2M) communication capabilities between sensors and personal devices. Thus, this allows to carry out the communication with just approaching the reader to the devices, i.e. contactless. This offers advantages mentioned in terms of easy use for elderly people in AAL environments, in addition to the mentioned ubiquity. For that reason, it is highly interesting for the development of AAL solutio
ns, but this also presents challenges for the performance and efficient data transmission because the constrained resources and capabilities from the devices, and the latency introduced by the NFC technology with the refresh readers to exchange NDEF records. These challenges appear since it was originally considered for identification, and not for continuous data transmission. This paper discusses the feasibility of developing a monitoring system for continuous data transmission from an electrocardiogram (ECG). ECG has been considered among the available clinical sensors because its complexity. This presents an example of NFC communication via a USB NFC reader and an Android OS Smart Phone with NFC support. Over that scenario are analyzed the problems found with the original data from the ECG, and consequently it is prepossessed a pre-processing technique for the ECG wave trace. This pre-processing analyzes the signal in order to detect possible arrhythmias and mainly to reduces transmission overload (compression) in order to make suitable the transmission of continuous data through NFC.
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